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A bunch of you messaged me after the recent Praktika post asking for a deeper dive into UGC strategy.

Here it is, just like I promised ;)

Quick context: I used to be a product manager at TikTok, and over the past few months, I’ve interviewed 10+ consumer founders who’ve scaled their growth engines with UGC at the core.

For this special post, I’ve teamed up with my friend Joseph Choi—a UGC expert and founder of the Viral App Founders Club, a community for top consumer app builders.

The playbook we’re sharing today is geared primarily towards consumer app founders, but honestly, it’s useful for anyone looking to tap UGC for growth and distribution.

Tldr for those busy founders:

UGC vs. Influencer Marketing: What's the Difference?

Before diving in, let's define some terms:

Influencer Marketing: Paying someone with an existing audience to promote your product to their followers. You're essentially renting their audience and the trust they've built.

UGC (User Generated Content): Content created by creators that doesn't depend on an existing audience. Instead of leveraging trust, UGC plays to platform algorithms to generate views organically. Essentially, you hire UGC creators to create organic content on your brand account.

Why does this distinction matter? UGC can be dramatically more cost-effective because you're paying for creative talent, not audience access. This works because short-form platforms like TikTok and YouTube Shorts reward quality content regardless of follower count.

Many creators with <50K followers often perform way better than accounts with 1M+ followers. Plenty of $$$alpha in this UGC land.

Why You Should Care About UGC Now

Both of us are super excited about UGC because we believe it’s still the most underpriced distribution channel for many consumer startups today.

While e-commerce brands have been exploiting this channel for a few years, most non-ecomm consumer founders are still sleeping on UGC's potential.

Consumer startups that have capitalized on this have realized massive gains recently:

• Jenni AI: Scaled to $10M ARR by mastering UGC when competitors weren't even in the game. Their "POV: You have an essay due" videos generated 300M+ views and $500K+ in revenue from a single format.

• Praktika: This language learning app found one viral format that generated tens of millions of views and 10x'd their revenue in just 4 months, reaching $12M ARR.

• Cal AI: Applied UGC to the fitness/diet niche that competitors like MyFitnessPal weren't using. They created viral videos showing their calorie scanner feature, scaling to $10M+ ARR.

*Join Viral App Founders Club to meet and learn from these founders!

The Complete UGC Playbook for Consumer Founders

I'll walk you through this entire framework using a language learning app as our example. Let's call it "LinguaLeap"—a language learning app that helps you speak English better.

Step 1: Content Research

What you need to do:

1. Scroll through content in your niche as a normal user.

2. Look for outlier videos with tons of views and engagement.

3. Find viral video formats that talk about a solution to a problem (a viral format where you could naturally integrate your product).

4. The winning content formula often has three key elements:

   1. Emotion (relatable, funny)

   2. Product showcase (central to the video)

   3. Repeatability (easy to reproduce with different creators)

Real example: Quizard AI's lecture hall sleeping format

1. Emotion: Lazy student in lecture

2. Product showcase: App is central to the video (recording lecture with AI)

3. Repeatability: No creator's face shown, easy to reproduce with different students (downside is that many competitors could easily replicate this format as well).

LinguaLeap example:

For our language learning app, we’d search TikTok for high-performing language learning content. We’d identify outlier videos with millions of views where creators share techniques or methods without promoting specific apps.

For instance, this video explains “multi-modal immersion techniques for language learning.” The creator, Rhea, discusses a potential solution without plugging a product. It received 16K+ likes and thousands of saves, making it a strong candidate for a viral format we could adapt for LinguaLeap.

One potential challenge with this format is repeatability. The video features Rhea speaking directly to the camera, and she brings credibility as a Stanford linguistics student. Other creators may struggle to replicate the same level of virality.

Tips:

• Find existing viral formats where you can seamlessly integrate your product.

• You could research competitor video formats, but the upside might be limited due to potential saturation.

• Pay attention to comments expressing frustration with existing solutions.

• Look specifically for videos presenting solutions (techniques, methods) that could be replaced with your app.

Common mistakes:

• Focusing only on high-follower creators

• Giving up early if you can't find an exact match for your product (consider adding a "viral feature" like Cal AI did with their calorie scanner).

Step 2: Find Creators for Video Production

What you need to do:

1. Target micro-influencers with under 50K followers but consistently getting at least 50K views just a rule of thumb—it varies based on the industry).

2. Look for under-monetized creators who aren't currently promoting many products.

3. Reach out to creators with a personalized message on all channels and be persistent.

LinguaLeap example:

Our geo-focus for LinguaLeap is English learners based in LATAM, so we'd first search for all the LATAM-based language learning creators on TikTok.

Our criteria:

• Micro: 1K–50K followers

• High performance: average 50K views in the past 2 months

• Under-monetized: not currently promoting other products at scale

It’s also helpful to look at the accounts those creators follow to get more leads.

After creating the shortlist, we’d reach out to them on TikTok and via email, explaining why we love their videos and asking if they'd be interested in creating content featuring our app's conversation practice feature.

Another approach is posting LinkedIn job posts recruiting content creators in LATAM.

Because they're under-monetized and in LATAM, it’s possible we could get them to create content for <$50 per video.

Tips:

• Don’t give up early. Response rates vary from 20–60%, so reach out to plenty of creators.

• If you are on a budget, testing it yourself is fine, but be mindful that you might be the wrong creator for your target audience.

• Ensure the creator’s target audience location matches the countries you are targeting.

• Joseph compiled a great list of scrappy ways to source creators. Check it out here.

Common mistakes:

• Paying based on follower count instead of engagement quality.

• Not reaching out to enough creators (it's a numbers game).

• Not being mindful of the creator’s geo-focus.

Step 3: Systematically Finding the Winning Formula

What you need to do:

The goal is to find a winning video format that works for your product by systematically experimenting with different variables, one at a time.

Variables include:

1. Hook (first 3 seconds)

2. Creators or people on camera

3. Filming and editing style

4. Call-to-action presentation

5. Overall video concept

When you're first starting with a new brand account, it’s important to warm it up for a week before posting a large volume of content to avoid shadow bans.

LinguaLeap example:

In the research phase, we spotted a couple of strong concepts worth testing. The next step is finding a winning formula with a structured testing plan.

For the first experiment, we’d spin up a fresh TikTok account just for this UGC push. Week one is all about warming up the account—watching videos, leaving comments, following creators—basically acting like a real person.

Come week two, we’d start posting UGC videos from our influencer partners. Every TikTok would also get cross-posted to IG Reels and YouTube Shorts to squeeze out max reach.

We’d shoot for 1–3 videos a day in the first month.

Goal: land that first viral hit and build from there.

Tips:

• Don't give up too quickly—it might take 30+ attempts to find a winner.

• Views don’t always translate directly to conversions; prioritize content that drives actual signups.

• Warm up your new brand account to minimize shadow ban risks.

Common mistakes:

• Changing multiple variables at once.

• Giving up too quickly on promising formats.

• Poor video fundamentals (e.g. blocked text placement, poor lighting, or audio quality).

Step 4: Replicate and Scale

What you need to do:

1. Once you’ve got a winning format, triple down (post 3x a day on that account).

2. Spin up new accounts for different audience segments or content styles.

3. Build a plug-and-play system so creators can crank out content on their own.

4. Keep tracking performance and tweak your playbook as you go.

LinguaLeap example:

After discovering that our "Duolingo frustration to conversation success" format works well, we'd create multiple variations: one for Spanish learners, one for business travelers, and one for students.

We'd set up separate accounts for different language focuses and post consistently on each. We'd also create a simple template for creators to follow, allowing them to produce variations efficiently.

Tips:

• TikTok algorithm works better when an account targets a consistent audience.

• Limit to three posts per day per account to avoid shadow banning.

• Don’t create multiple accounts on one device (limit to 5 per phone).

• Scale budget toward winning formats, but always keep testing new ideas.

Common mistakes:

• Abandoning experimentation once finding one winning format.

• Not creating systems that allow for consistent content production.

• Letting quality slip as you scale.

—-

If you are looking to learn more about UGC, I highly recommend joining Joseph’s Viral App Founders Club where you will get more in-depth courses, community support on this specific topic.

See you next week 🫡,

Leo Luo

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A little-known fact about me: back in college, a few friends and I built a social bartering app called Clipp. It was my very first attempt at building a startup.

The idea was to create a "Tinder for secondhand items", making it fun for college students to swap stuff they owned and reduce waste along the way.

Well… let’s just say it was quite a FLOP. We shut it down a couple of months after launch.

We made every startup mistake in the book, from taking forever to develop the MVP to building a massive team from day one.

Pickle is like the product Clipp could’ve become in an alternate universe.

In simple terms, Pickle is a peer-to-peer rental marketplace for things people own, starting with women’s clothing and accessories.

Pickle now has tens of thousands of monthly active users and recently raised a $12M Series A from Craft and FirstMark.

Here’s their playbook 👇

From social polling to peer-to-peer rental

Brian McMahon and Julia O’Mara met while working at Blackstone. They quickly realized they made a great team. Both were college athletes — Brian played football at Maryland, Julia played lacrosse at Penn — and shared the same competitive spirit and drive to push boundaries.

In 2021, they left Blackstone to build Pickle.

They initially started with a social polling app. Users could post outfit options, whether a new suit or a dress, and friends (especially those with similar style) could vote on what looked best.

It introduced social proof into the shopping process.

But it didn’t take off the way they hoped. However, they noticed something interesting — in the comments of polls, people were often recommending (and sometimes offering) items they already owned.

That sparked a lightbulb moment: what if people could rent or lend items directly to each other?

After whiteboarding it out, they realized they had an opportunity to create a true peer-to-peer rental marketplace and reshape how people consume and share in their communities.

Market timing and competitive landscape

To be clear, peer-to-peer rental isn’t a brand new idea. Many startups have tried (like Rentah) — but most never scaled.

What’s different this time? Market timing.

Pickle is riding three big waves:

• Courier Convenience: Same-day delivery platforms like DoorDash, Uber, and Relay make logistics seamless. Pickle can build on top of that infrastructure.

• Social Trends: Fashion moves fast, driven by social media. People want new looks without the long-term commitment of owning.

• P2P Familiarity: Platforms like Airbnb and Poshmark have made peer-to-peer transactions feel safe and normal.
  

Product positioning

Pickle is a hyperlocal peer-to-peer rental marketplace, starting with women’s fashion — especially trendy or high-end items.

Value for renters:

• Access: Rent expensive or sold-out items for 1-2 time uses.

• Convenience: Get last-minute outfits thanks to same-day delivery (if you are in a pickle!)

Value for lenders:

• Income: Earn money from underused items; top lenders make tens of thousands per year.

There are also social features. You can follow fashionable people in your neighborhood.

Strong value props on both sides (often the same user!) + sticky social features = high engagement.

In fact, 50% of Pickle’s monthly active users are also weekly active users.

As Brian puts it:

“Pickle has the engagement of a social app but the monetization of a marketplace.”

Average order value: $70.

Pickle takes a 20% service fee from the lender.

Hyperlocal marketplace growth playbook

1/ Solving the cold start problem

No one wants to use a marketplace with no inventory, just like no one wants to party in an empty club.

The clever thing? On Pickle, supply and demand can be the same person. That helps solve the chicken-and-egg problem. You don’t need to build both sides from scratch.

Their first market was NYC.

To seed the first 1,000 items, Julia personally recruited her most stylish friends. She went to their homes, helped photograph items, and uploaded them herself.

She also DMed stylish strangers to get them on the app.

To understand their users better, Brian and Julia personally delivered the first 2,000 orders.

2/ Free UGC cheat code

To get the next 10K users, Pickle tapped into NYC’s micro-influencer scene.

Instead of traditional sponsorships, they invited influencers to use the platform, turning them into both lenders and renters.

Micro-influencers are a perfect fit: they want extra income, need clothes for content, and love engaging with fans (who can now rent their outfits).

To sweeten the deal, Pickle offered free photoshoots with professional photographers. Influencers got high-quality content, plus beautiful images of clothes to rent out.

(A trick Airbnb also used in the early days.)

This strategy worked. Influencers like Madi Khan (20K+ followers) and Megan Crean (22K followers) joined.

Word of mouth spread fast in NYC’s tight-knit creator circles.

Here’s one video that went viral:

3/ Market expansion

Pickle takes a bottom-up market expansion approach.

Although it’s hyperlocal, users can rent across cities (items just get shipped).

The team watches organic shipping trends to spot potential new markets.

For example, in LA, they noticed lots of users renting LA-based items. Over time, those renters became lenders, which attracted more renters.

Once 8,000+ items were listed in LA, Pickle doubled down, investing in community activations and relationship building with local micro-influencers.

4/ Traction today

• Tens of thousands of MAUs

• 200K+ products from 2K+ brands

• Several thousand orders per week

My analysis of Pickle

What excites me most about Pickle is the team—Brian and Julia have worked together before and have the kind of scrappy relentlessness I love in early-stage founders. From personally delivering the first 2,000 orders to Brian teaching himself to code and building the platform from scratch, their grit is unmatched.

They also have a brilliant growth unlock with micro-influencers, who are perfectly incentivized to promote Pickle organically because they earn money, get free content, and create value by using the product itself.

In addition, the hyperlocal nature of the platform makes it incredibly sticky. It has the engagement of a social app and the monetization of a marketplace. Starting with women’s clothing, they’re already seeing demand for categories like ski gear, and even growing interest from men.

That said, as they scale, maintaining high-quality inventory and user trust will be crucial. Challenges like counterfeit items, fraud, and returns are classic marketplace growing pains, but hard ones nonetheless.

Still, Pickle is growing fast, executing with real focus, and I love their long-term vision of reshaping how communities sustainably share what they own.

Super excited to see how the story unfolds. Big shoutout to Brian for sharing Pickle’s story with me.

See you next Tuesday 🫡,
Leo

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This is the Squid Game-themed business card that helped Simplify land its first 10,000 users:

"There's a better way to make money. Discover your next internship at simplify.jobs"

Before we dive into the story behind this card, let's rewind to 2020 when the company was born.

Back then, Michael Yan was just another Stanford sophomore trapped in the exhausting internship hunt. He spent countless nights submitting over 150 applications, crafting 10 different resumes, and enduring awkward Zoom interviews during the height of the pandemic—only to be ghosted by recruiters.

Frustrated (and undoubtedly over-caffeinated), Michael decided he'd had enough.

He recruited his hallmate and a friend from a weekend hackathon to build a solution that would automate the mind-numbing job application process.

The initial intention was not to launch a startup. They just wanted to save themselves, and maybe some classmates, from the misery of repeatedly filling out the same forms and writing endless cover letters.

First 2000 users: one viral LinkedIn post

The initial idea was simple: create a Chrome extension to help students automatically fill out job applications.

To gauge interest, Michael shared their MVP on LinkedIn (in fact, it was Michael’s first ever LinkedIn post), positioning it as a "common application for internships."

He was still new to the platform, without the coveted 500+ connections badge.

To everyone's surprise, it exploded overnight. The post garnered over 50,000 views and quickly built a waitlist of 2,000 eager students.

Seeing this overwhelming interest on LinkedIn, Michael and his team gained the confidence to pursue this idea further as a startup.

With their MVP and the initial LinkedIn hype, they applied to Y Combinator and landed a spot in YC's Winter 2021 batch. They subsequently dropped out of Stanford to pursue Simplify full-time.

Swimming in a Sea of Competitors

While getting their first 2,000 users seemed effortless, the journey to 10,000 proved to be an uphill battle.

The job-hunting market was saturated, full of jaded people sick of platforms promising to solve all their job search woes.

Most students just didn't want to sign up for ANOTHER job board.

To attract more users, they tried various marketing tactics, including the classic move of sending mass emails to college mailing lists (we've all been there LOL 😂). It was about as effective as shouting into the void.

Students either ignored the emails entirely or deleted them without a second glance.

Next 100K: Squid Game & personal brand on LinkedIn

Squid Game stunt

With frustration mounting, Michael and his team knew they needed something radically different.

At that moment, Netflix's "Squid Game" was taking the world by storm.

Seizing this cultural phenomenon, they printed 25,000+ Squid Game-inspired business cards.

With the provocative message, "There's a better way to make money. Discover your next internship at simplify.jobs," they stealthily distributed these cards across Stanford, MIT, Berkeley, Northeastern, and Harvard.

The marketing stunt worked and finally helped them get over the hump, surpassing the 10K user milestone.

Building a LinkedIn personal brand

While the Squid Game cards kickstarted their user acquisition, Michael understood that sustainable growth needed more than clever stunts.

It required a memorable brand.

Given Simplify's focus on job searching, Michael leveraged LinkedIn to establish himself as a 'job search expert,' building on the platform that had brought them their initial 2,000 users.

He maintained a consistent daily posting schedule, finding particular success with the 'sharing job list → comment your email' format, regularly generating tens of thousands of views.

It has paid off big time. Today, Michael has over 145K followers on LinkedIn.

Product iteration & current traction

What began as a Chrome extension for automating job applications has evolved into an AI copilot for the entire job search process.

Beyond the flagship autofill feature, the platform now offers:

• Job matches: match candidates with relevant job postings

• AI resume builder: use AI to tailor resume to fit the job description in a few clicks

• Job tracker: help candidates to track job applications and their status

For monetization, Simplify generates revenue from both sides of the marketplace. It charges companies to post and promote job listings on their platform. For job seekers, Simplify offers a premium subscription service called Simplify+, which provides users with advanced AI features to enhance their job search experience, including AI cover letter generator, AI response writer, and unlimited AI resume tailoring.

Current traction:

As the platform has matured, it has expanded beyond its initial student market. Today, over 70% of job seekers on Simplify are experienced professionals.

Since its founding in late 2020, Simplify has processed 70M job applications, achieved millions in revenue, and grown to 800K+ job seekers—all with a lean, scrappy team of fewer than 10 people.

Now it's your move.

Got a bold, unconventional strategy to capture your first 10,000 users? Are you pushing the limits, or could you go even further?

See you next Tuesday 🫡,

Leo

I hate boring market research reports (looking at you, Gartner!), so I'll keep this one light, and hopefully, interesting.

Read Time: 2 mins 43 secs

Wait what… Why are we talking about oral health?

For one thing, this topic touches everyone. Oral health is deeply connected to general health and quality of life. The World Health Organization estimates that oral diseases affect 3.5 billion people worldwide, making them one of the most common health burdens.

Poor oral hygiene doesn’t just cause cavities or gum disease, it can also increase the risk of systemic issues like heart disease, diabetes, respiratory infections, and even dementia.

In fact, untreated tooth decay is the MOST prevalent health condition globally. This means improving oral care has a ripple effect: preventing pain and tooth loss, and also supporting better overall well-being and chronic disease management.

I believe this is an amazing market for innovation for the right founders, here are my whys:

1/ Massive market with stable demand: In the US market alone, total spend on oral care amounts to over $170B every year. The dental healthcare sector remains stable due to its inelastic demand. Even during economic downturns, preventive and emergency dental services see consistent utilization.

For example, during the 2008 recession, dental spending declined by just 2.6% (compared to ~8% for overall healthcare) and rebounded quickly afterward, according to the ADA Health Policy Institute.

2/ Accessibility: Insurance coverage further stabilizes demand. Dental insurance among adults in the US has reached a 5 year high of 65%.

Roughly 77% of insured Americans receive dental benefits through employers, and government programs like Medicaid and CHIP cover dental care for 56 million children, ensuring affordability for vulnerable populations.

‼️ However, there is one curveball: the Trump administration's funding cuts and delays for community health centers are creating uncertainty in the dental care sector, potentially limiting access to affordable dental services for millions of vulnerable Americans, including low-income individuals and those relying on Medicaid.

3/ Rise of cosmetic dentistry: Cosmetic dentistry is a massive growth driver for the oral health industry, shifting from luxury to mainstream demand.

Valued at $33.6B in 2022, the global cosmetic dentistry market is expected to grow 2.6x by 2030. Surveys show 36% of U.S. adults are considering pursuing procedures like teeth whitening or veneers, reflecting rising consumer interest in aesthetic enhancements.

Two biggest markets in dental right now are:

• Dental Implants: $6B+ market driven by aging populations

• Clear Aligners: $4B+ market (e.g. Invisalign, SmileDirectClub) with saturation in direct-to-consumer play but there is growing opportunity forming partnership with orthodontists.

4/ Consolidation of DSOs: The rapid expansion of Dental Service Organizations (DSOs), driven by rising education costs and financial barriers for new dentists, presents opportunities for startups.

The number of solo dentists dropped from two in three to one in two from 1999 to 2019. As DSOs consolidate the market and streamline operations, they increasingly seek innovative technological solutions to boost efficiency and strategic growth. Unlike independent practices, DSOs have dedicated administrative roles, such as CTOs and heads of strategy, actively pursuing new technologies and operational improvements.

5 main segments for oral health startups

1/ Software: Digital tools for scheduling, billing, and workflow automation are modernizing dental practices. AI-powered diagnostics and patient monitoring are becoming key differentiators.

2/ Fintech: Startups are offering dental-specific financing and benefits platforms, such as pay-as-you-go dental memberships and AI-driven insurance claims processing.

3/ Biotech & Medtech: Innovations like saliva-based disease diagnostics, regenerative enamel treatments, and smart toothbrushes are gaining traction.

4/ Imaging & AI: AI-driven imaging, 3D printing for dental restorations, and intraoral scanning are reducing the cost and time required for dental procedures.

5/ Specialty Products & Services: DTC innovations like subscription toothbrushes, tele-dentistry, and custom oral microbiome care are reshaping oral hygiene habits.

💰 6 startup opportunities for consumer founders

1/ At-Home Disease Detection & Monitoring: Saliva-based diagnostics (e.g. Bristle, Viome) and real-time oral health monitoring wearables (e.g. Lura Health).

2/ Preventative & Personalized Oral Care: Custom oral care (Proclaim’s customized water powered interproximal cleaning) and early-stage cavity reversal treatments like Curodont.

3/ Remote Care & Tele-dentistry: Virtual consultations and AI-powered remote orthodontic supervision (e.g. Grin).

4/ Smart Oral Care Products: High-tech toothbrushes (e.g. Oralucent’s light therapy, Great Gums’ bioelectric brush) and connected oral health platforms.

5/ Consumer Education & Engagement – Gamification, personalized coaching, and microbiome-driven oral health guidance.

6/ AI agents - Automate billing, booking, insurance claims (e.g. Overjet, Pearl). Not a super consumer idea but worth mentioning since I know many of you are building AI agents.

Potential challenges and pro tips

Despite all the opportunities in the space, starting a business in the oral health space isn't easy.

Dental providers tend to be cautious about adopting new technologies. To minimize resistance, develop products with clear insurance reimbursement codes and ensure seamless integration with existing workflows, particularly electronic health records. A proven strategy for efficient adoption is to pilot your solution with DSOs, which can accelerate scaling and integration into dental practices. Additionally, focus on provider education and comprehensive implementation support can reduce friction as well.

Another important challenge is navigating regulatory hurdles. Getting FDA approvals, particularly Class II or III for diagnostics or therapeutic devices, can be a lengthy and costly process. Preparing for these requirements early can save significant time and resources.

The oral health consumer market can be crowded depending on the vertical, making it essential to clearly differentiate your product…but this is also true for many consumer markets. One approach to create differentiation in oral health is providing solid clinical validation (e.g. high-tech toothpaste backed by peer-reviewed research).

Finally, given the current fundraising climate, it's wise to adopt a capital-efficient business model. For instance, software-as-a-service (SaaS) offerings targeting Dental Support Organizations (DSOs) generally require less upfront investment compared to hardware-based solutions.

Special shout out!

Huge shout out to my friend Jeremy Krell for providing me with so much insight for this post. He is the managing partner at Revere Partners, a VC specializing in oral health. If you are a founder in this space, make sure to reach out to Jeremy.

🤝 NEW: founder matching

As promised last week, highlighting a few members of the Consumer Startups community who are actively seeking co-founders:

• Joel is a serial technical founder with experience bootstrapping consumer startups. Previously, he founded a bootstrapped consumer edtech business, served as VP of engineering at a consumer health AI startup (acquired), and worked as lead engineer & growth at a fintech (scaling it from $1M MRR to $10M MRR). He is looking for a business co-founder with a mature idea.

• Henry is the Director of Business Development at Splash Sports and former founder of Hedge. He is looking for a technical co-founder for a concept around public golf course loyalty rewards.

• Barakah is passionate about reimagining home as a healthcare space through her startup, CogAi. She was formerly a software engineer at Lockheed and a product manager at a Unicorn startup. She is looking for a high energy cofounder with a strong technical background in ML and interest in helping individuals with neurodegenerative disorders.

See you next week 🫡,

Leo

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🤝 New Experiment: Co-Founder Connect

Many of you have mentioned to me that you are looking for a business or technical co-founder, so I’m launching a new column to help match founders within this community.

If you're searching for a co-founder, just reply to this email with a one-liner about who you are and what you're looking for. I’ll feature it in an upcoming newsletter!

Imagine this: You’re trying to raise an $8M seed round for your startup. Instead of sweating through a PowerPoint pitch, you deploy a charming AI that calls investors on your behalf, spins a compelling story about your company, and—voilà—closes the deal.

Sounds wild? That’s exactly what happened with Boardy.

Boardy is your on-demand voice AI super-connector. It gets your goals and links you with the right people at just the right time.

Boardy’s seed round lead investors, Hanel Baveja and Simon Schmincke, first met Boardy on a Friday, knowing nothing about the founder or company. After experiencing Boardy’s knack for forging new connections, they were sold. They looped in their partners over the weekend, and by Monday, the investment was a done deal. Sure, the team had a few meetings, but Boardy handled about 80% of the heavy lifting.

It's insane 🤯.

p.s. Here is the deck Boardy used for the seed round.

From Clear Angel to Boardy

The idea for Boardy was born when founder Andrew D’Souza was running ClearCo, his previous financing startup. With early access to GPT-3, Andrew and his team built Clear Angel, a nifty AI startup coach designed to help founders grow their businesses. Although Clear Angel was eventually shelved to focus on ClearCo’s core operations, it lit a fire under Andrew.

That side project turned into an obsession. Andrew even stepped down as ClearCo’s CEO to dive headfirst into the AI world. When he discovered the latest voice models the following year, he saw untapped potential in voice interfaces. As he puts it:

"I don't think we fully grasp the impact that this modality is going to have on how we interface with software and applications. I'm also a voice person. I hate emails, I hate texts. I much prefer putting in my headphones and going for a walk and taking a phone call." - Andrew

Andrew believes that we are heading toward what he calls Conversational Singularity—the moment when AI interactions become more valuable than most human conversations.

He argues that as AI intelligence becomes widespread, your network of trusted relationships will become the key differentiator.

This insight led to the vision of creating a networked human intelligence. As Andrew explains in the seed deck:

If Boardy can route the right requests to the right humans at the right time, we might be able to solve most of humanity's hardest problems a lot faster, cheaper, and more efficiently. - Boardy Seed Deck

Boardy was created to become that trusted, networked human intelligence, guiding us toward this conversational singularity.

Tackling the Toughest Challenges in Human Connection

Boardy isn't just another networking tool; it's a bold attempt to replicate the nuances of human conversation through AI.

One major hurdle is contextual memory. Boardy's design deliberately avoids a traditional app interface—no dashboards, no logins. Instead, it communicates via phone, email, and LinkedIn. This creates an "amorphous" user profile where the AI must remember who you are and what you've discussed across different channels.

It’s not just about storing info; it’s about capturing the subtle threads that make every conversation unique.

Then there’s bi-directional matching. Sure, you can search for people on LinkedIn, but Boardy goes a step further by ensuring that both parties genuinely click—in terms of shared interests, credibility, and even personal chemistry. Think of it as a matchmaking service for your professional life.

Crafting the Best AI Voice Experience

One of the key challenges the team faces is managing the trade-off between latency and conversational depth. While faster models can deliver near-instant responses, they often lack depth and nuance. Boardy deliberately accepts a slight delay to generate more thoughtful and engaging responses, ensuring conversations feel authentic rather than mechanical.

The team also focuses on creating a truly human-like experience. They've invested in creative talent to develop Boardy's distinct persona, crafting a voice that's not only pleasant but also captures the subtle nuances of natural conversation.

With rapid advances in AI and voice tech, Andrew and his crew have been meticulously mapping out their roadmap. Their strategy focuses on building compounding advantages in areas that are crucial but overlooked by competitors.

"My CTO and I have spent a lot of time identifying the new capabilities likely to emerge in the next 6 to 12 months and where we can build a compounding advantage. We’ll get some things right and others wrong, but overall, we're focusing our energy on problems that others aren't solving—yet are on everyone's roadmap." - Andrew

Boardy’s Future

Since its October launch, Boardy has gained strong momentum. Tens of thousands of users have joined organically, attracted by its promise of authentic, human-like connections.

Despite the traction, it’s still early days. The network effect hasn’t fully kicked in, and the business model is still taking shape.

But I can’t help but wonder: what if it actually works?

As Andrew sees it, Boardy is far more than a networking tool. Boardy could be your AI co-founder, a digital partner that's always learning, never sleeps, and knows everyone. This goes beyond making introductions; it's about having an AI companion that's truly invested in your success.

I don’t know about you but this sounds amazing to me.

🎁 Other Voice AI opportunities

(For founders interested in the AI voice space) Andrew also highlighted a few other voice AI opportunities worth exploring:

• Inbound Sales Calls: Handle incoming sales inquiries, reducing response time. This serves as an ideal entry point compared to outbound calls while voice quality technology matures

• Candidate Screening: Enable candidates to share their stories naturally through voice interactions, significantly reducing workload for recruiters and hiring managers

• Therapy & Mental Health Support: Address loneliness and mental health challenges through empathetic AI conversations; challenges here might lie in legal and compliance hurdles

P.S. If you’re interested in the VC perspective on AI voice, I highly recommend this article from my good friend Olivia Moore.

If you are finding this newsletter valuable, share it with a friend, and consider subscribing if you haven’t already.

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See you next week,

Leo

Hey fam,

Life update: I'm joining a16z as a scout!

When I started this newsletter, my goal was to create content that can be helpful for early-stage founders and operators, whether by sharing the latest trends and insights relevant to different consumer verticals or by highlighting the unique playbooks and tactics used by the fastest-growing companies. Now, through my partnership with a16z, I'm thrilled to expand this vision by providing founders with financial capital, albeit modest amounts, to help realize their ambitions.

At the same time, I'll be doubling down on my content! I am committed to providing weekly digestible startup case studies, along with occasional long-form deep dives into specific consumer trends and growth strategies. I am excited to offer more in-depth insights into the consumer world—not just from the perspective of a journalist, but also as an investor.

I owe a special thanks to Olivia Moore for bringing me on board. I first met her in early 2020 when I reached out about collaborating on her newsletter, Accelerated. We connected instantly. While she was investing at CRV, I would share promising startups with her, and that relationship continued after she moved to a16z. Through Olivia, I’ve met other fantastic consumer investors on the team, including Justine Moore (her twin sister!) and Bryan Kim. These relationships ultimately led to this exciting opportunity with a16z.

As a scout, I’ll be writing small checks to early-stage companies, often as their first investor. While I’m passionate about consumer opportunities, I’m also eager to explore compelling B2B ventures. As an optimist who has covered over 100 startups across various niches, from marketplaces to prosumer apps, I look forward to partnering with ambitious founders who are deeply passionate about their problem spaces and have a unique perspective on the world.

If this resonates with you, please reach out by replying to this email (if you received this post in your inbox) or by contacting me at leoluo2017@gmail.com.

It's time to build 🚀!

Leo

Read time: 2 min 20 sec

I need to tell you guys about my buddy Zibo.

I met Zibo a few years ago when I first started writing this newsletter. He had just quit his consulting gig and told me about his plan to launch a product studio with the goal of shipping fun mobile apps that can bring joy to people.

Fast forward to today, he has shipped 10+ consumer apps, from AI astrology app to friendship bracelet trading app targeting Taylor Swift fans aka swifties.

He had a moderate level of success in the first couple of years in terms of revenue and users, but nothing really surpassed 50K DAUs.... until he stumbled upon the idea of Soundmap, which blew up and grew to millions of users and 400K+ DAUs in one year.

This success also led to a $1.7M seed investment from A16Z Speedrun, Gold House, Brooklyn Bridge Ventures, and more.

How Zibo validated Soundmap

Most of the apps Zibo and his team launched weren't born from groundbreaking insights or hidden market secrets. Instead, they focused on shipping products that might bring people joy. However, most of the ideas shared some common threads:

• Built for Gen-Z fan culture

• Games (particularly trading-based mechanics)

• Music-focused applications

Soundmap's eventual success wasn't just about the idea itself - it came from Zibo's ability to recognize and abandon shit projects. Unlike many founders who become emotionally attached to their first idea and persist too long, Zibo took a more pragmatic approach:

"We are very honest with the numbers and confident with our read of the numbers. We try to use data to help inform our decision, quickly get to a conclusion, and do the right things as quickly as possible." - Zibo

When evaluating a newly launched app's performance, he looks at three key metrics*:

1. Acquisition cost - Run paid ads to test CPC/CPI, targeting under $0.5 per install in the US market.

2. Retention - Monitor user retention at day 7, 30, and 6 months. The retention curve should flatten as early as possible. While 30% retention at month 6 is ideal, lower rates can work but make maintaining the user base more challenging.

3. Monetization - Build monetization features into the product from day 1. Within 5 updates, you should have a clear picture of whether your app is successfully converting users.

*For those interested in learning more about industry-specific retention and conversion benchmarks, check out Lenny's excellent posts on retention and conversion.

When making the final go/no-go decision, he combines these quantitative metrics with qualitative feedback from the user community. Users' excitement (or lack thereof) about your product is typically quite evident.

How Soundmap works

Soundmap is a digital playground for music fans—it’s like Pokemon Go for your favorite tracks. Instead of hunting for creatures, you’re exploring a map to discover song “drops,” each tagged with a rarity level from common to epic.

As you roam around (or explore virtually), you collect these musical treasures and trade them with other fans, building a personal collection that reflects both your taste and status.

The platform primarily attracts Gen-Z music enthusiasts in high school and college, giving them a unique way to showcase their fandom. While these users might not have significant financial status in the real world, Soundmap provides them with a virtual space to build pride and collect virtual coins, creating a genuine sense of accomplishment.

Simply put, Soundmap turns music into a game that’s as exciting to play as it is to hear.

How they got their first 1000 users

#first 1000 customers

Soundmap’s journey from a three-week build to a thriving platform is a testament to smart community leverage. The team built their MVP in just three weeks and immediately tapped into their existing network—launching to Discord groups from previous projects like Friendship Bracelets and Decibel, which together had 30K-40K users. This strategic approach quickly delivered their first 1,000 customers.

#next 1M customers

From there, the growth engine kicked into high gear. They built a clever invite loop with an irresistible incentive: invite eight friends, and you unlock free premium forever—a perk that normally costs about $20.

This viral mechanism, combined with engaging Reels and TikTok videos showcasing the app’s interactive nature, accelerated user adoption.

Today, their user acquisition breaks down to 35% from invite loops, 35% through organic word-of-mouth and social sharing, 25% from paid ads, and 5% from SEO.

Notably, around 70% of Soundmap users operate in single-player mode, proving that local user density isn’t crucial for success. The platform functions more like a music bartering game than a social app.

As of February 2024, Soundmap boasts over 400K daily active users, with 60% using the platform 5 days a week.

Community = double-edged sword

Running an app filled with die-hard fanatics is as thrilling as it is challenging. On one hand, these passionate users spread the word like wildfire—boosting your K-factor and sharing the love for Soundmap everywhere. On the other, their intensity can sometimes tip over into negativity, making community management feel like a tightrope walk.

Balancing what the community wants with what the product needs isn’t easy. Zibo’s team is always juggling feedback from Reddit, Discord, and Facebook. At the end of the day, managing this unpredictable fan club means really listening to their demands without losing sight of Soundmap’s vision. It’s a delicate balancing act, but it’s also what keeps the app dynamic and deeply connected to its audience.

While some might view Soundmap's success as pure luck, Zibo and his team actually created their own opportunities through persistence and strategy.

They expanded their chances of success by consistently shipping new apps at a rapid pace. More importantly, they maintained objectivity by systematically evaluating each app's performance and weren't afraid to kill underperforming products.

This disciplined approach to product development, combined with their relentless execution, turned seemingly random luck into predictable success.

I am excited to see what new apps Zibo launches next.

Leo

Read time: 2 mins 9 seconds

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The AI writing landscape has exploded recently, transforming how we approach the written word.

On one end, marketing powerhouses like Jasper and Copy.AI churn out quick copy, while Grammarly remains our trusted companion for grammar polishing. ChatGPT and similar general-purpose models excel at brainstorming but sometimes miss that human touch. In academia, Jenni AI has found its groove, helping students and researchers manage citations and research effectively.

AI writing tools typically fall into three distinct categories:

Incumbent doc editors with AI features: Google Docs, Notion, and Word now enhance their traditional editors with AI capabilities like rewrite, summarize, and writing copilot features—think of your familiar word processor with AI superpowers.

AI native writing tools: Platforms like Jenni AI, Type.ai, and Jasper were built with AI at their core. Each serves a specific niche—Jenni AI for students, Type AI for serious writers, and Jasper for enterprise marketing needs.

General purpose AI tools: ChatGPT, DeepSeek, and Claude provide chat-based writing support. While powerful, they lack the specialized features found in dedicated writing tools.

Type.ai: An Insider’s Look

I recently sat down with Stew from Type.ai to peek behind the curtain of this innovative writing tool.

Founding story

A lifelong entrepreneur with a passion for weekend writing, Stew tried every available tool—from basic note-taking apps to various document editors. While these tools excelled at organizing knowledge and enabling collaboration, none addressed the real challenge: generating fresh, creative ideas and finding the right words to express them. His eureka moment came when he first experienced GPT-3.

“I just had my light bulb moment. I realized that language models were finally advanced enough to help with both ideation and expression. If writing was the only thing you cared about, what would the ideal product look like?”

This revelation sparked Type. Instead of creating another generic content generator, Stew envisioned a tool that seamlessly blended a familiar document editor with sophisticated AI assistance—perfect for dedicated writers who want to remain deeply involved in the writing process.

How Type.ai Stands Out

Type positions itself as the premier writing tool for serious writers—people who write extensively throughout their week. It offers three key advantages:

• Deep Integration: No clunky add-ons here. Type’s AI writing and editing features deeply integrate with a familiar document interface. Simply highlight text, click “Improve,” and receive personalized suggestions right inside your draft.

• Empowering Your Creativity: Rather than writing for you, Type focuses mostly on helping with the ideation and editing process. As Stew explains, “Your personal trainer can’t do your workouts for you, nor should your AI do all of your writing for you. We’re here to enhance your creativity, not replace it.”

• Quality Over Quantity: While competitors focus on output volume, Type.ai prioritizes meaningful, context-aware suggestions. This makes it ideal for editing and refining pieces of writing until they fit your authentic voice.

Their diverse user base includes unexpected adopters—from Catholic priests refining weekly sermons to college professors crafting lectures and content marketers creating engaging copy. The common thread? Writing forms a crucial part of their daily routine.

Growth Strategies and Market Realities

Stew shared valuable insights about navigating the competitive AI writing space. Type.ai launched as an ”AI document editor,” carving out a distinct niche from general content generators.

This strategic positioning, combined with well-timed exposure through Twitter demos and a Product Hunt launch during the GPT-3 boom, helped build a waitlist and attract over 120,000 free users. Personal recommendations drive about 20% of new signups.

While acknowledging that giants like Google Docs and Notion are adding AI features, Stew notes they lack the specialized writing experience professionals need. General-purpose models, though powerful, often miss the mark on depth. This creates an opportunity for specialized tools like Type.ai—though capturing this market presents its own challenges.

The platform walks a fine line between flexibility and specialization, aiming to serve everyone from legal writers to novelists. While this broad appeal makes targeted marketing challenging, the focus remains on helping writers who value quality and authenticity.

The Road Ahead

Looking forward, Type.ai plans to enhance its contextual understanding—improving its ability to learn an individual’s writing style and improve at subtler elements of good writing, like humor. The future focuses on developing smarter, personalized editing suggestions that feel like a natural extension of your writing process.

Have you experimented with any AI writing tools that changed your workflow? What do you think about the idea of having an AI as your creative partner? Would love to hear what you think!

Cheers,

Leo

p.s. fill out this reader survey and enter to win a $50 gift card.

Read time: 2 min 06 seconds

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The AI development tool space is heating up faster than a cup of ramen in a dorm microwave. With each new innovation, these tools promise to make coding faster, smarter, and more accessible.

One of my favorite AI development tools is Lovable, an AI copilot enabling users to build full-stack applications through simple chat interfaces.

I recently attempted to build a real-time translation app for fun. I started with Cursor, but after 4 hours and getting stuck, I turned to Lovable.

In under two hours, I had a fully functional app up and running. It’s insane:

// Origin Story

Lovable’s journey starts with two ambitious entrepreneurs from Stockholm, Sweden: Anton Osika and Fabian Hedin. Osika, who began developing apps at age 12, co-founded Depict AI, a startup that graduated from Y Combinator and raised $20M. Hedin, a developer who coded at SpaceX and founded multiple companies, brought his expertise in creating scalable solutions.

Together, they launched an open-source project called GPT Engineer.

GPT Engineer allowed users to describe app features in natural language, generating production-ready code. While it garnered over 50,000 GitHub stars and cultivated a loyal community on Discord, monetizing the project proved challenging.

However, it laid the foundation for something bigger.

// GPT Engineer to Lovable

Recognizing the limitations of GPT Engineer, Osika and Hedin rebranded and rebuilt it as Lovable, an intuitive, visually appealing application designed for a broader audience, including non-technical users.

During my recent chat with Anton, he shared that the rebranding was critical to broadening their audience:

“We wanted Lovable to feel approachable, even for those without coding experience.” - Anton

The key upgrades included:

• Improves over time: Unlike competitors, Lovable’s system is finely tuned to ensure new code doesn’t break existing solutions.

• Seamless Integrations: The platform seamlessly works with tools like Stripe, Supabase, Shadcn, and Resend, enabling covering all desired functionality for building a commercial application without bugs.

• Intuitive Interface: Lovable avoids terminal-based or code focused and abstracts it into a much more user-friendly interface.

// Rapid Growth and Monetization

Lovable’s growth has been nothing short of remarkable.

Within six weeks of its subscription launch, the platform grew from $0 to over $6 million in ARR — the fastest of any European company to date.

Lovable stands out by simplifying app creation for both developers and non-technical users.

It allows users to describe their app ideas in natural language while handling the rest as the world’s first AI full-stack engineer, seamlessly integrating front-end and back-end development. Its integration with Supabase ensures reliable database management and real-time functionality, while continuous improvements in error handling and system evaluations guarantee high-quality output.

“We’re building for the 99% of people who don’t know how to write code. Lovable is the fastest way to collaboratively build an application.” - Anton

// Competitive landscape and positioning

The AI development tools space is getting crowded, but after testing a few standout players, here’s my take on what sets them apart and when to use them:

• Lovable: Perfect for non-developers who want to quickly spin up a full-stack production app. Bonus: it integrates smoothly with GitHub and Supabase.

• Bolt: Similar to Lovable but gives users more control over the code—ideal if you like a bit more flexibility.

• V0: Great for generating beautiful UIs in a snap, though it’s not a full-stack solution.

• Replit: A powerful online coding environment that’s expanding its features to help users create full-stack production apps.

• Cursor: Coding copilot built for developers who need help improving productivity with AI and want more control over their codebase.

• Windsurf: Think Cursor, but designed for professional teams. It comes with a sleeker UI and team-friendly features.

// Lovable’s future roadmap

The team at Lovable isn’t slowing down. Their upcoming features aim to push boundaries even further.

For those who love design tools like Figma, Lovable is set to simplify prototyping by enabling AI to generate UIs that closely mirror Figma files. In addition, they’re working on agentic capabilities, empowering the AI to autonomously run tests, gather user input, and execute tasks seamlessly. Collaboration is also getting a boost, with plans to facilitate interdisciplinary teamwork between developers, designers, and operators—turning what feels like a single-player game into a true multiplayer experience.

When I asked Anton about the future, he said he wanted Lovable to be the "last piece of software" anyone would ever need to build apps.

I’m inspired by the prospect of a future where anyone, regardless of technical skill, can effortlessly bring their ideas to life.

Leo

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Read time: 1 min 15 seconds

I love SaaS.

No, not software-as-a-service. I mean serendipity-as-a-service.

If you’re like me (and most of my friends), you’ve probably deleted Instagram or TikTok multiple times, sworn off doomscrolling, and tried hacks like turning your phone to greyscale—hoping it would help you focus. Spoiler: it didn’t.

We’re in a world where our attention feels more like a public commodity than a personal choice. Instead of meaningful time with loved ones, we spend hours glued to screens, half-distracted and doomscrolling our way into oblivion.

Loneliness is everywhere. In 2021, over 12% of Americans said they had no close friends. Back in 1990, that number was just 3%. It’s a trend that feels… pretty depressing.

During the pandemic, I tried Lunchclub. At first, it was fun—I got to meet people from all over the world. But after a while, virtual networking felt transactional and exhausting. It turns out that meaningful connection can’t be fully digitized.

That’s where serendipity-as-a-service apps come in. These platforms are all about creating real-life connections, minus the awkwardness of formal networking or the pressure of dating apps.

Here’s the basic playbook:

1. Take a personality quiz. Let the algorithm do its thing.

2. Sign up for an event. Usually something around a meal plus some activities.

3. Get matched with a group. Your social fate is now in the hands of the app.

Here are a few standout players in this space:

1. 222: A Gen Z favorite, combining meals with fun events like rooftop jazz or karaoke. Their app onboarding is top-notch—seriously, give it a try (just trust me!!)

   

2. Timeleft: Focused on Wednesday dinners. Why Wednesdays? Who knows, but it seems to work for them.

   

3. The Breakfast: Start your day by meeting someone new over breakfast.

   

These apps are catching on in a big way. For example, Timeleft grew from 0 to 1.5M users in just 11 months.

So why do they work?

For starters, they’re low-pressure. Think of them as social dining apps rather than networking or dating apps. Everyone has to eat—even if you don’t love the people you’re matched with, you still get a good meal out of it. No strings attached, no expectations.

Second, they’re effortless to use. You sign up for an event, and the app handles everything: matching the group, booking the restaurant, and even providing icebreakers. All you have to do is show up, eat, and enjoy.

That said, I wonder about their long-term retention. Most of these platforms charge a monthly membership fee, but how often do people need a regular dose of dining with strangers? I see these apps thriving among people who’ve recently moved to a new city and are eager to build connections.

Have you tried any serendipity-as-a-service apps? If so, I’d love to hear your thoughts!

🎁 Bonus:

Since you made it to the end (congrats!), here are two free gifts:

1. I’m curating a free directory of B2B newsletters and podcasts. It’s great for content recommendations and finding collaborators for marketing campaigns. Check it out and let me know what you think!

2. I’ve also got a list of 350+ places to post your startup for free backlinks. Reply to this email, and I’ll send it your way.

See you in two weeks,

Leo

Read time: 1 min 25 seconds.

Last month, I watched a video about Blake Anderson, a 23-year-old entrepreneur who made over $5M in one year with two AI apps: UMax and RizzGPT. UMax rates people based on their attractiveness and provides them with tips to maximize their appearance, while RizzGPT helps dating app users know what to say to their matches.

What do those two apps have in common, you may ask?

Well... besides the fact that they primarily target single men looking to up their dating game, they are both lightweight GPT wrapper apps focusing on a consumer niche. They were simple - in fact, they were coded by Blake (a business student from Tulane) using ChatGPT in just a month 🤯.

More broadly speaking, they are considered AI consumer utility apps.

These apps have a few common characteristics:

1. Consumer utility: Apps that target a real consumer pain point (not social apps).

2. AI wrappers: Typically built around some LLMs or AI models.

3. Lightweight product and team: Only 1-2 killer features, built by a very, very small team.

4. Growing trend: Capitalize on a growing trend (e.g., lookmaxxing for UMax and rising dating app usage for RizzGPT).

For AI models, I’ve seen the following being used the most:

I believe there will be an increasing number of these lightweight AI consumer utility apps popping up over the next few years, as the barriers to building these apps continue to drop (thanks to AI coding agents). Slow-moving incumbents risk losing market share to an influx of AI-native apps with better features, UX, and distribution channels.

Below are some of these apps I’ve seen recently, by category:

PRODUCTIVITY

PDF.AI: Instantly chat with or summarize PDF documents

• Revenue: $50K+ MRR

• Team: 1

• Target users: Students, researchers, and professionals

Caktus AI: AI homework helper for students

• Revenue: $100K+ MRR (based on my estimate of their web traffic — no source here)

• Team: <10

• Target users: Students

Cal AI: Track your calories with AI

• Revenue: $600K+ MRR

• Team: <5

• Target users: Fitness and health enthusiasts

CREATIVITY

PhotoAI: Help people save time and money taking photos with an AI photographer

• Revenue: $100K+ MRR

• Team: 1

• Target users: People who need to take photos of themselves

InteriorAI: Redesign your interiors in seconds with AI

• Revenue: $30K+ MRR

• Team: 1

• Target users: Interior designers, homeowners

Musicfy AI: Use AI to create music with your voice or other voices

• Revenue: $150K+ MRR

• Team: <5

• Target users: Artists, content creators

Crayo AI: Easily create short-form videos with AI

• Revenue: $300K+ MRR

• Team: <5

• Target users: Content creators

InstantUpload: Generate AI Video Stories With Text To Video.

• Revenue: $14k MRR

• Team: 2

• Target Users: Content creators

InkGen AI: Generate tattoo designs with AI

• Revenue: $10K+ MRR

• Team: 1

• Target users: Tattoo enthusiasts and artists

COMMUNICATION

Plug AI (aka RizzGPT): Know what to say to matches on dating apps

• Revenue: $200K+ MRR

• Team: <5

• Target users: Dating app users

BoldVoice: Reduce accents when speaking non-native languages

• Revenue: $500K+ MRR

• Team: <15

• Target users: Non-native speakers looking to improve pronunciation

Are you also building in this space? I’d love to hear from you :)

Leo

It’s been a minute. Sorry for the absence, but I’m finally back!

A lot’s happened in the past couple of years, and I’m excited to fill you in on some big life updates. Plus, I’ve been cooking up something special for Consumer Startups that I can’t wait to share with you all.

Life Updates

Here’s a quick recap of what has happened in my life since my last post in March 2023:

I joined TikTok’s Creative AI team as a product manager. It was a wild ride—I helped launch and scale AI dubbing and the TikTok Symphony Creative Studio. I got an inside look on how AI is democratizing the creative process for many creators and advertisers.

This fall, I decided to go back to school. I’m now studying Design Engineering at Harvard. It's been a fun challenge where I have had more time to work on my technical chops and tinker on some of my own products, ranging from AI pet portraits to performance wearable device for elite swimmers.

The most recent experiment I launched is InfluencerB2B, a directory of newsletters and podcasts from different B2B niches. The idea is to create an easier way for B2B marketers to find influencers to partner with for marketing campaigns. Hit me up if you are interested in learning more！

Trends that excite me recently

There are three trends I am closely following recently and will continue to unpack in my future posts.

The Rise of Solopreneurs

There’s been a noticeable surge in interest around solopreneurship (check out the Google Trends chart below). Personally, I’ve seen more and more of my entrepreneurial friends shifting gears—moving away from the ambition to build VC-backed startups, and instead, embracing the solopreneur route. Many are diving into building micro SaaS and consumer utility apps.

It makes sense when you think about it: There’s now a growing ecosystem of tools that make it easier to launch quickly and automate much of the back-office work. Starting and scaling a business on your own has never been more achievable—especially with so little overhead required.

Empowering Non-Technical Builders

On an related note, I’m also really excited about how non-technical people are now able to build products faster than ever with LLM powered coding apps. Tools like Cursor and Lovable are empowering people to create MVPs with AI. It's changing the game.

Here’s an example of a tweet I came across that highlights how people are using these tools to move fast:

It would be interesting to monitor the secondary effects derived from the rise of solopreneurs and non-technical builders:

• Niche Products: With more individuals building solo, we could see a rise in highly niche products that cater to smaller, underserved markets. This creates a unique opportunity for people who can connect or integrate these products into larger ecosystems.

• Support Services and Platforms: As the number of non-technical builders grows, so will the demand for supporting services—whether it’s mentorship, no-code tools, app templates, or specialized integrations. If you can build a product that helps these new founders move faster or get better results, there’s a huge market waiting.

The Era of AI Consumer Utility Apps

There’s a trend I’m really keeping my eye on: AI-driven consumer utility apps. It’s clear that the next wave of apps won’t just be “fun AI” features—they’ll be apps that revamp existing consumer apps and tools.

One perfect example is Cal AI, an AI-powered calorie tracking app. With a photo or a quick barcode scan, Cal AI can instantly help you calculate calories and nutrients so you don’t have to do it manually on My Fitness Pal like in the old days.

There will be more and more AI native apps that will replace those traditional consumer utility app incumbents.

Take this tweet from Greg Isenberg that perfectly sums up the idea:

What’s Coming Up

I’m returning to a regular biweekly posting schedule, and here’s what you can expect:

First, I’ll be diving into the latest consumer trends, with a particular focus on consumer AI. I’ll explore how AI is reshaping the products we use every day and what’s coming next in this space.

Next, I’m excited to break down the stories of the fastest-growing consumer startups today. Just like before, I’ll unpack how they got their first 1000 customers, the mistakes they made along the way, and the key lessons that other founders can learn from their journeys.

Lastly, I’ll be sharing more about the various projects I’m working on (e.g. InfluencerB2B)—and building in public with all of you.

That’s it for now. Looking forward to connecting more in the coming weeks!

Cheers,

Leo

p.s. If someone forwarded you this email, make sure to click here to subscribe to this newsletter

Here is a hot take: in the next 5-8 years, most tech companies in the US will move 50% of their business functions offshore.

The why

COVID has shown us that many jobs can be done remotely without a decrease in productivity. 

As remote work becomes more prevalent, it's hard to imagine that companies won't tap into the global talent pool to get the best return on their labor costs.

It’s already happening. Check this out:

In 2000, the business process outsourcing (BPO) industry in the Philippines accounted for only 0.075% of the country’s GDP. During the pandemic, it contributed to at least 7% of the Philippine economy. This sector grew 10.6% in 2021 alone and recorded over $29B in revenue.

Hiring offshore is a no-brainer for companies for two main reasons - 1) cost arbitrage 2) quality global talent pool

1. Cost arbitrage:

Let’s do some simple math. 

Say you have a startup that needs 3 salespeople, 2 marketers, and 5 customer support professionals. 

Here's how much you could save by hiring from the Philippines vs the US:

That's a significant amount of savings, especially in the current economic climate.

2. Quality global talent pool

There are good workers in every part of the world; you just have to find them. 

At the startup where I work, I've had the pleasure of working with many talented people from over ten countries, ranging from India to South Africa. They are equally driven & competent as their American counterparts and often bring unique perspectives helpful to the business.

Corporate America is doomed for a rude awakening. 

Who’s taking advantage of this?

Global HR software is an obvious one. Managing the benefits and payroll of international employees/contractors is challenging due to complex compliance and regulations in different countries. 

Deel has emerged as one of the market leaders in the global HR software space, surging from just $4 million ARR in 2021 to $295 million in January of this year.

I have also seen many companies making a killing in the offshore talent matchmaking space. 

Here are some models:

• Freelance marketplaces

• Managed marketplaces

• Headhunting biz

1) Freelance marketplaces

Freelance marketplaces match companies with freelancers for short-term projects or part-time gigs. Many marketplaces today are quite established, including Fiverr, Upwork, and Toptal.

They are often horizontal platforms covering projects from data entry to design.

2) Managed marketplaces

This is the model where I have seen the most adoption in the past two years.

Managed marketplaces are deeply involved in the relationship between the customer and the talent. They vet the talent supply and work closely with their customers to find the right talent and serve as a mediator if any future issues arise.

One company that I am a big fan of is Lemon.io. They have a network of engineers from Europe and Latin America, and their team has already tested and interviewed every candidate.

With Lemon.io, companies can have an engineer start working on your project within a week instead of months, and they don't have to waste time on candidates that are not qualified.

Some other interesting examples are Growth Assistant, SupportNinja, and Boldly.

3) Headhunting biz

Companies in the headhunting space focus on sourcing offshore talent. They only charge a one-time fee for each talent acquisition project, and their main value-adds lie in their access to offshore talent and their vetting ability. 

To differentiate, these firms often focus on a specific geography for sourcing. For example, Support Shepherd focuses on the Philippines, while Remotely Talent focuses on Ukraine.

Alright - that’s all from me. What are your thoughts on this hot take? And what are some other interesting opportunities that you have seen? 

If someone forwarded you this email, make sure to click here to subscribe to this newsletter & keep getting hot takes and nerdy startup stuff from me.

Leo

Welcome to the 547 founders and investors who have joined the Consumer Startups family since the last send!

A quick message from my friends at Lemon.io…

Ready to take your startup to the next level but struggling to find the right developers? Check out Lemon.io.

They have a network of engineers from Europe and Latin America, and every candidate has already been tested and interviewed by their team.

With Lemon.io, you can have an engineer start working on your project within a week instead of months, and you don't have to waste your time on candidates that are not qualified.

Hire developers smarter with Lemon.io

It's Sunday evening and I'm faced with the daunting task of tackling my towering pile of dirty laundry. Despite being a relatively simple process, I can't help but dread the three hours it takes to wash, dry, and fold everything. But that's where Sudshare comes in.

Think of it as Uber for laundry. With just a few taps on your phone, you can connect with a personal launderer, or "Sudster," who will pick up your clothes and return them clean, dried, and folded by the next day. The pricing is simple, with customers paying $1 per pound of laundry and Sudsters earning $0.75 per pound (plus tips). The platform takes the rest.

Founded as a family business in 2018, Sudshare has since exploded in popularity and now operates in over 500 markets in the US, providing income for over 200,000 Sudsters. Last year, it raised a $10 million Series A round led by Headline. I recently had the opportunity to chat with CEO and Co-Founder Mort Fertel to learn more about the story of building this successful startup, and I can't wait to share it with you. 

Let's dive in!

Genesis

Mort Fertel has been killing the entrepreneurship game for over 30 years. After getting his degree from UPenn, he hit the ground running with his first business in the direct mail advertising space, which he sold in 1995. But he wasn't done there - he then turned his focus to helping couples save their marriages and created programs like Marriage Fitness Tele-Boot Camp. And now, he's back at it again with Sudshare - the latest in a long line of successful ventures born from daily frustrations.

Mort has a big family of seven - that’s a lot of laundries! But, even with all the advances in technology, Mort's wife Ari found herself still spending hours on laundry just like her mom and grandma before her. 

“I was homeschooling five kids, so we had a ton of laundry. I could tap an app and get to the airport, FaceTime someone on the other side of the world, and deposit a check without going to the bank, but I was still spending hours doing laundry as my mom and grandma did.” - Ari

Their teenage son, Nachshon, recognized the need to solve the laundry problem and created Sudshare – an Uber for laundry. With just a few taps on their phones, people can now get their clothes cleaned.

Nachshon, who taught himself coding as part of his homeschooling curriculum, spent two years developing the product and launched it in Baltimore in February 2018. Mort joined as a mentor and later became a co-founder. Several of their other children have also joined the family business to help it grow.

Growth Journey

Demand side

Sudshare's success with its customers is driven by its compelling value proposition. It offers families a much-needed break from the weekly chore of doing laundry and does so at an affordable price of $1 per pound.

They used Google Ads to get the first 10 customers and since then growth has been overwhelmingly driven by word-of-mouth. Once folks tried Sudshare and realized they could say goodbye to laundry forever, they couldn't stop raving about it.

Due to the nature of laundry, Sudshare serves a diverse range of customers, from RV-dwelling families to busy business travelers. Not only does it save time but it also provides a convenient solution for those without access to washing machines and dryers nearby. 

Today, it operates in over 500 markets in the US and was reported to have over 80K customers in early 2022. It's safe to say that this number has likely grown significantly since then.

Supply-side

Value prop:

The value proposition of Sudshare is attractive to those looking for a way to make money from home. Anyone can become a Sudster, provided they have a washer and dryer and can pick up and drop off laundry bags. According to Mort, it is the first work-from-home manual labor job, making it an ideal option for stay-at-home moms who want to work but can't leave their homes often.

Sudshare provides a great opportunity for earning supplemental income. Most sudsters make around $15-20 per hour, while top performers can earn up to $2,000 a month and some have reported earnings of up to $5,000.

Product iteration:

Since its founding, Sudshare has primarily focused its product development efforts on the supply side, with the aim of delivering the best laundry experience to its customers.

First, the company invested in training, creating numerous instructional and best practices videos to help Sudsters excel. These resources are integrated throughout the platform and in communication emails.

Second, they established a tiered points system to incentivize exceptional customer service. New Sudsters can only accept one order at a time, but as they accumulate more points and advance in rank, they can accept more orders per day and earn additional benefits, such as early payment.

Sudshare also fostered a close-knit community for Sudsters by creating a Facebook Group, where Sudsters can receive support from their peers and share best practices. With over 11K members and 1,000 monthly posts, the group has proven to be a valuable resource.

These investments on the supply side have paid off and attracted over 200K Sudsters from all walks of life seeking to earn additional income working from home.

Laundry industry and product differentiation

Laundry is something we all have to deal with. On average, American families wash 300-390 loads of laundry a year and spend around $170 on it. The US laundry & dry-cleaning market is worth over $10B in 2021, with coin-operated and retail services making up more than half of it. There is significant room for growth in this market, with the potential for a 10x better solution, similar to what the ride-sharing market has achieved.

"Uber for laundry" has been tried before but without much success. Washio was one of the more well-known examples, raising around $16 million from investors like Canaan Partners and Ashton Kutcher. They relied on outside laundries and employed drivers to pick up and deliver laundry. But it all came crashing down due to high expenses for drivers and marketing.

Sudshare is different, though. Instead of using dry cleaners or professional companies, they use gig workers aka Sudsters to do the laundry. Instead of doing the laundry in commercial facilities like Washio, Sudsters often do it from home. This has allowed them to grow without the need for big marketing budgets or partnerships with laundry companies when expanding to new markets. Plus, by focusing on just laundry and not dry cleaning, Sudshare can offer a better experience and margins for both their platform and Sudsters.

Vision for the future

In the next three to five years, I envision Sudshare becoming an elite consumer brand, used by a substantial portion of the population. The hallmark of our achievement would be the growing number of households that choose to transform their laundry rooms into dedicated storage spaces. The only people with washers and dryers will be Sudsters. - Mort

That’s it for this week!

See you soon 👋,

Leo Luo (follow me on Twitter @_leoluo)

Welcome to the 715 founders and investors who have joined the Consumer Startups family since the last send! If you haven’t subscribed, join thousands of other consumer founders and investors by subscribing here:

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Starting a startup can be an exciting and thrilling journey, but it can also be a costly one. As a first-time founder, finding ways to save money is crucial. For today’s post, Ali and I have teamed up to find you the best deals and unexpected ways to save money for first-time startup founders. 

From cloud credits with Google and AWS to advertising credits, productivity tools like Notion and Miro, and even email and SMS services, we've got you covered. However, saving money isn't just about finding the best deals, it's also about being resourceful and thinking outside the box. So, buckle up and get ready to learn some unconventional ways to save money and extend your runway. 

Let’s dive in!

Finance and Legal Deals 

Incorporation (Stripe Atlas, Doola, Clerky)

We have found the YC startup school program (YC SUS) to be the best avenue to get discounts on products that help founders incorporate in the US. The program is easy to join and does not have any barriers. It has partnerships with Stripe Atlas, Doula, and Clerky. 

• Stripe Atlas - YC SUS founders can receive Stripe Atlas business formation for $250, instead of $500.

• Doola: YC SUS founders can receive the“Start Your Business” package for $225, instead of $500 (55% off)

• Clerky: YC SUS founders can get access to Company Lifetime Package for only $699 instead of $4781; this package includes incorporation and other company legal products (e.g. fundraising, hiring, etc)

Cap table management (Carta)

The most popular cap management software in the market right now is Carta. Fortunately, it is free to use for startups with up to 25 security holders and up to $1M raised through its Carta Launch program.

If you don’t qualify for the free version, you can also get 20% off your first-year fee by being a customer of either Ramp or Stripe corporate cards. Alternatively, you can also get this 20% through AWS Activate. 

Insurance and compliance (Embroker, Vanta)

If you are looking at Embroker as a business insurance vendor for your startup, you can use this coupon code to get 20% off.

If you are looking to up your compliance game, Vanta is likely the platform to go. We found two deals for you. If you are a Ramp customer, you can get 25% off a Vanta subscription; however, if you don’t have Ramp, you can use this coupon code to get $1000 off your payment. 

Accounting (Quickbooks, Xero, Pilot)

The best deal for Quickbooks is for founders who are customers of Brex, in which case you get 30% off your first year. 

The best deal for Xero is for founders who are customers of Ramp. Ramp customers get a 25% off Xero Business plan. You can get similar deal by being a Carta customer.

For Pilot, both AWS Activate and Stripe Corporate cards offer 20% off for the first six months.

Banking/expense management (Brex, Mercury, Ramp, Expensify)

If you are looking to get Brex, the best deal is a $1000 sign-up bonus and waived card fees through Segment’s Startup Program. The segment startup program requires an application but it is open to most startups that are incorporated less than two years ago and raised no more than $5M in total funding. 

If this deal does not work out,  go through YC startup school. You can get $500 Brex cash after spending $3K and another $100 after spending $3K on a Brex card. 

Similarly, you can secure discounts for Mercury if you have access to either YC startup school or Segment’s Startup Program. Segment offers a slightly better deal;a $500 signing bonus with no spending requirement. With YC SUS, you must spend $10K on your debit card within 180 days of approval. 

Honorable mentions:

Ramp - Free platform plan + $500 after you spent $10K if you are a Carta customer

Expensify - 50% off for six months if you have Stripe corporate cards

People and Ops Deals

HR and payroll (Rippling, Deel, Gusto, Guideline)

From employee management software to employee benefits platform, there are a variety of deals and discounts available to help founders keep their expenses in check. 

Here are the ones we found:

• Rippling: Stripe Corporate Card customers and Carta customers get 6 months free to try out Rippling. If you want a good discount instead, being a Ramp customer helps. Ramp customers get 10% off all Rippling products.

• Deel: the best option is with Ramp - 50% off contractors and 20% off full-time employees for 12 months. YC SUS also offers favorable discounts - 3 months free, then 30% off for contractors, and 20% off full-time employees for 12 months. If neither works, try AWS Activate. You can get the first month free for contractors and 10% off for full-time employees.

• Gusto: Brex can get you 50% off the first year for Brex customers while Stripe Corporate Card can offer 3 months free. 

Honorable mention:

Guideline 401K: Stripe Corporate Card customers can get fees waived for the first three months

Recruitment (Lemon, Gun.io, Revelo, LinkedIn Premium)

We found some great coupons for three popular platforms for recruiting engineers.

• Revelo: they help you hire vetted remote devs from LatAm. You can get 20% off the first three months using this coupon.

• Lemon: Lemon matches companies with vetted engineers. You can get 15% off the first month using this coupon.

• Gun.io: Another platform to find and hire quality developers. You can get $250 off your first dev hire using this coupon.

If you prefer to reach out to potential candidates yourself, consider joining Microsoft for Startups, which will qualify you for three-month subscription to LinkedIn Recruiter Lite, Sales Navigator Core, and LinkedIn Premium Business.

Customer Support (Freshworks, Zendesk, Intercom, CleverTap, Helpware)

For Freshworks, the best deal is $10,000 credits split across its eight product lines. This same deal is offered through multiple channels:

1. Member of Freshworks for Startups 

2. Brex customer

3. YC SUS member 

4. AWS Activate

For Zendesk, the best deal is a free subscription to Zendesk for six months. You can get this deal by applying to Zendesk for Startups (requires that you have raised some outside funding including Angel). Alternatively, you can also get the same deal by being either a Ramp customer or a Stripe Corporate Card customer.

For Intercom, you can get 100% off your first year by being a Stripe Corporate Card customer or an AWS Activate member. Alternatively, you can get 95% off if you participate in Intercom’s Startup Program. To qualify for this startup program, you can’t have more than $1M in funding or more than 5 employees.

Honorable mentions:

Clevertap: get 50% off the first year by being a part of their startup program or being a member of AWS Activate.

Helpware: $1000 off coupon code here

Communication software (Slack)

The best deal for Slack is 30% off on your first year using AWS Activate. Alternatively, you can get 25% off on your first year of Slack Pro or Business+ if you use this special promo link. 

Brex or Ramp customers get the same 25% off.

Product Deals

Cloud/hosting (AWS, Google Cloud)

Hosting and cloud services can be a significant expense for startups and small businesses. Both AWS and Google Cloud offer various programs for startups and small businesses.

To navigate these programs, we broke them into two categories:

• For Funded Startups

• For Bootstrapped and/or Side Projects

1. For Funded Startups:

Google Cloud Startup program is a simple and straightforward option for funded startups. 

It offers up to 100k in credits for companies that raised equity funding (from pre-seed to Series A). Startups can apply directly on Google's website without the need for external affiliations.

AWS, on the other hand, offers up to 100k in credits for startups through AWS Activate. These companies must have:

• Raised more than $500k 

• Not yet raised a Series B

To receive the full credit, apply through Carta's startup program, Silicon Valley Bank, Mercury (with a minimum deposit of 250k), Ramp, Brex or an affiliated investor/accelerator.

It's important to note that when redeeming credits, it's best to use smaller credits first. AWS will not accept a credit that is equal to or less than one that has already been received.

As an added bonus, sign up for the Amazon BusinessPrime Card to get an additional 5% cashback on all AWS spending, or use Rho to get 1.75% cashback!

2. For Bootstrapped Startups / Side Projects

We recommend using AWS for bootstrapped startups and small businesses looking to reduce their hosting and cloud service costs. 

Segment's Startup Program offers the highest amount of credit with up to $25k in AWS credit, while companies incorporating through Stripe Atlas can receive $10k credit.

For those not planning to incorporate or use Segment, the alternatives are: 

• AWS Activate for Founders program (up to $10k, depending on usage)

• AWS Proof of Concept program ($1k)

• CreditHero (up to 2k/month shared by indie developers with excess credits)

Additionally, you can sign up for the AWS Educate series and receive $100 in credit or develop an Alexa skill and receive $25.

If none of these options work for you, there are paid subscriptions that offer AWS credit perks such as:

• Secret Startup Deals Subscription

• Product Hunt Pro Ship Subscription

• Startups.com 

• Techcrunch+ Subscription.

Alternatively, you can use Google Cloud and receive $2,000 in credits by applying directly on their website, without needing external affiliations.

Analytics (Mixpanel, Amplitude & more)

For event-tracking, the two go-to players, Mixpanel and Amplitude, offer a generous deal for startups. 

Mixpanal offers $50,000 in credit for 1 yea best accessed through their startup program. Whilst Amplitude offers its own startup program that offers $40,000 in credit for one year. For session replays, heatmaps, and more, you can receive 1 year of free FullStory using Segment’s startup program or use PostHog's generous free plan.

Honorable mention:

CrazyEgg: 3 months off any plan (Paid)

Productivity (Notion, Coda, Airtable, Miro & more)

For all-in-one productivity tools, you can go with Notion, Coda or Airtable:

Notion offers $1000 of credit for startups, best accessed directly on their website. Beyond, you can layer an additional 50% cashback (up to $5000) using Stripe Corporate’s Card. 

For companies with more than 20 employees, a better deal is 50 free seats for 12 months, available through Product Hunt’s Founders Club. Founders Club costs $720 and offers a variety of other perks.

If Notion is not your thing, you can receive a $1000 credit from Coda using their competing startup program.

As for Airtable, it is best to go through AWS activate or Carta’s Startup Stack. Both offer $2000 in credit instead of the standard $500 offered through Airtable’s startup program.

For prototyping and brainstorming your options are Miro, Invision or Figma:

Miro is best accessed through AWS activate where you get $1000 in credits compared to the standard $500 on Miro’s website. A fallback option is using Founderpass to get the same $1000 deal. However, this route will cost $99. 

For Invision, the best deal is 6 months off which you can get using this link. Figma has a generous free plan and doesn’t offer startup discounts.

Honorable mentions:

Grammarly: 20% using this link

Fellow (meeting management): $1000 credit using this link

Docsend: 90% using AWS activate

1password: 25% off of Family plans using this link

Sales and Marketing Deals

Ad Credit (Snapchat, Linkedin, Tiktok)

We explored various deals and offers and found the most promising ones in Snapchat, LinkedIn, and TikTok:

• Snapchat:  Snapchat is offering a valuable $3000 credit for Ramp customers. An additional 5% cashback is available for those using a Stripe Corporate Card. Even for those who may not qualify for these offers, Snapchat still has an introductory promotion where users can claim a $375 credit after spending $350. 

• Linkedin: startups can claim a generous  $1000 credit available through the Microsoft for Startups program. Additionally, everyone is eligible for $100 off their first campaign when using this link.

• Tiktok: startups can claim $100-$500 by creating a Shopify account. While the process may be a bit cumbersome, it is worth it.

Honorable mentions:

Reddit: $100 credit, no-spend requirement

Bing: $500 credit after you spend $250

Google: $500 credit after you spend $500

CRM (Salesforce, Hubspot, Pipedrive)

Salesforce, Hubspot, and Pipedrive, three major players in the CRM market, have all rolled out programs and discounts specifically tailored to startups:

• Salesforce: Use their Startups Program to get 50% off first year. Other startup programs or discount sites we looked at were either on par or worse. 

• Hubspot:  Use their startup program directly to get 90% off the first year. However, you will need to be associated with one of their partners. Luckily F6s is a Hubspot partner. You can create a free account here.

• Pipedrive: If you are looking for an affordable CRM down the line. You can get 50% off the first year through AWS Activate. If you don’t qualify for AWS active, use this link for 30% off. 

Honorable mention:

Close: an up-and-coming CRM for startups with under 100 sales reps, offers $1200 credit for startups with under $2m in funding.

Emails & SMS (TinyEmail, Customer.io, Hubspot)

We've both evaluated different Email and SMS services in our respective jobs. With many undifferentiated offerings, it can be an overwhelming process to navigate.

Here are the best providers (& deals) we've found:

• TinyEmail If you are looking for the most affordable email marketing solution(as we were), nothing will beat TinyEmail’s $49 lifetime offer available through Appsumo.

• Customer.io If you are looking for the most comprehensive automation solution go with Customer io. You can get 100% off their basic plan or 90% off their premium plan through several partners/programs. Segment’s startup program is the easiest one.

• Hubspot: For everyone else, we recommend Hubspot. You can get 90% off the first year on their Marketing automation product using Hubspot for Startups program.

Honorable mention:

SendinBlue: 75% off using Secret (Costs $19)

*Special* AI deal

OpenAI, the company behind ChatGPT and GPT-3 offers every new signup $18 in trial credit. However, by signing up for Microsoft’s for Startups program you will receive an additional $2,500 in credits, which equates to around 7m+ words generated by their language models.

That is all we have for today. Talk soon.

Leo Luo & Ali Abouelatta

Happy new year!

Welcome to the 523 founders and investors who have joined the Consumer Startups family since the last send! If you haven’t subscribed, join thousands of other consumer founders and investors by subscribing here:

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During the holidays, I reconnected with some old friends and discovered that ChatGPT, a new AI chatbot by OpenAI, has become a major part of their daily workflows. 

If you haven't heard of it, ChatGPT is like having a super smart pal who always has an answer for you. It's insane how people are using it - some for debugging code and others even for creating speeches. Unlike a lot of other AI products I've seen, ChatGPT can be useful for anyone, regardless of their profession. And the best part? It's free to use. Although, I bet it'll start monetizing soon since it’s estimated to cost over $100K to run per day. 

For today's post, I would like to share different ways to use ChatGPT to improve your life, whether you're a consumer, founder, or stay-at-home mom. Each of the ideas will fit into one of the following categories - creativity, productivity, planning/advice, and entertainment.

Just a heads up, ChatGPT is still in the research phase and shouldn't be trusted for factual responses. It's better for answering questions where there might not be a clear-cut right or wrong answer, like coming up with ideas for a trip.

If you're short on time, you can check out this post in a table form in this notion table.

Productivity

1)Write an investor update

ChatGPT can assist founders in saving time by generating updates for investors. Simply provide ChatGPT with high-level ideas about the content you want to include in the update. Ed Sim from What's Hot in Enterprise IT/VC utilized ChatGPT to create investor newsletters, including an explanation for a less-than-stellar performance of an enterprise VC fund and a prediction for a stronger year in 2023.

What's Hot in Enterprise IT/VC

What's 🔥 in Enterprise IT/VC #318

OK, I couldn’t resist and had to share some of the fun I’ve had with ChatGPT from OpenAI. It’s incredible and you must try it here. Here are a couple investor newsletters I asked it to write for me - one explaining why an enterprise VC fund performance was less than stellar and another on why 2023 will be a better year…

Read more

4 years ago · 7 likes · Ed Sim

2) Improve writing quality

ChatGPT can help you instantly improve your writing. In fact, I used it to improve the introduction of this post. It saved me so much time proofreading.

3) Fix bugs

ChatGPT can help you understand why your code is not working and give you recommendations on how to potentially resolve the bug.

Here is an example:

4) Build an app

What’s better than fixing code? Help you build an app from scratch.

Here is an example:

5) Translation tool

ChatGPT can be a handy translation tool.

Here is one example of how you can translate a sentence from English to Chinese.

6) Help understand a complex concept

Feeling like a fish out of water during your Zoom call with an investor? Don't let financial jargon make you feel like a novice. With ChatGPT by your side, you can quickly get up to speed on any concept they throw your way. No need to play dumb - let ChatGPT boost your financial vocabulary and help you hold your own in any conversation*.
*This paragraph was generated by ChatGPT

Here is one example:

7) Summarize a book

Don’t have time to read the book but need to get the gist for your book club meeting? Try ChatGPT.

I asked ChatGPT to summarize the book Little Bets for me (highly recommend checking out the book btw):

8) Create a title for an article

ChatGPT can help you brainstorm different title ideas for your next blog post.

Here is an example prompt I used for this article:

9) Write a Twitter thread

ChatGPT can help you grow your Twitter following by generating Twitter threads content. Many creators are already doing it.

Here is an example:

@theronmckie#greenscreen Day 2 - using #chatgpt to grow a Twitter following #emailmarketing #digitalproducts

Tiktok failed to load.

Enable 3rd party cookies or use another browser

10) Write marketing content

Not only can ChatGPT create a Twitter thread, but it can also be useful for creating all marketing content. Here is a good thread on 11 ways to do so:

Creativity

11) Recipe generation

ChatGPT has been extremely helpful in generating recipe ideas. Previously, I would spend a significant amount of time scouring the internet for meal ideas that utilized ingredients I had on hand. However, ChatGPT simplifies this process and makes it much more efficient. It has been a great tool for coming up with quick and easy meal ideas based on ingredients I already have in my fridge.

Here is one example of how I used it for recipe generation:

12) Name generation

ChatGPT is great for brainstorming ideas. It can be especially helpful for brainstorming names, whether it’s for a newborn or for a consumer startup you are starting. I used it to come up with a cute name for a dog I am thinking about adopting.

13) Create speeches

My friend Yash Ramchandani organized a cabin retreat with friends in Yosemite this past month. He used ChatGPT to create a speech script for the end of the retreat.

Here is the prompt Yash used:

14) Gift idea generation

I used ChatGPT for this exact use case earlier this week. I am visiting my parents soon in China and would like to bring them some gifts from the US. I wanted to come up with some creative gift ideas. ChatGPT did not disappoint.

15) Generate a breakup text

Hey.. you do you. If you are looking to break up over text with your significant other, ChatGPT can certainly help. Somebody from Reddit did it.

Planning/Advice

16) Create a workout plan

ChatGPT can be great at creating a workout plan for you as well. Alex Cohen (Product Leader/Investor) used ChatGPT to get fit.

17) Create a travel plan

Not only is ChatGPT great at creating workout plans, but it can also be useful for planning your next trip. I used it to brainstorm some ideas for my recent trip to Korea. I did quite a few things from ChatGPT's recommended itinerary.

18) Project management and prioritization

As a PM, I deeply understand the pains around project prioritization. Allie Miller, one of the big influencers in the AI space, gave a great example of how to use ChatGPT for project prioritization.

19)Get feedback on a startup idea

ChatGPT can be great at giving feedback on the merits and risks of an idea. Definitely consider giving it a try if you are currently evaluating some startup ideas.

For example, I asked ChatGPT to give me feedback on this offsite marketplace idea.

20) Interview preparation

Job seekers can certainly benefit from using ChatGPT, especially for interview prep. You can use it to brainstorm interview questions, come up with appropriate responses, or get feedback on your answers.

Here is an example of someone on Twitter using ChatGPT to prepare for their Google interviews:

21) Get career advice

ChatGPT can serve as a career coach and give you some solid advice. Leo Xu from Twitter used it to get some help with LinkedIn networking.

22) Relationship advice

Besides career advice, ChatGPT can provide you with relationship advice as well. Here is an example:

Entertainment

23)Tell a joke

I asked ChatGPT to give me some jokes I can tell at a party (with a bunch of startup people).

24)Provide companionship

ChatGPT can be a great companion as well.

24)Give a motivational speech

Need a hypeman or someone to give you a much-needed motivational speech? ChatGPT got your back. This is a fun one I saw on Reddit.

That’s it for today.

See you soon 👋,

Leo

As the year comes to an end, I wanted to express gratitude to all of you who have been following this newsletter. It started as an experiment at the beginning of 2020, and 2.5 years later, it’s still going strong. The consumer startups community has grown 4x in the past 12 months. There are almost 8000 of you today!

In 2022, we have covered a broad range of topics, ranging from consumer trends deep dives to startup stories featuring fast-growing consumer companies.

To wrap up this year, here are the top five most shared articles, in no particular order.

*Before I continue, I do have a big favor to ask. If you have enjoyed Consumer Startups so far, please share it with your friends, colleagues, or relatives who might enjoy learning more about startups and trends in the consumer world in 2023.

Share Consumer Startups

Let’s dive in!

1) 🎁 Drops

Product drop works because it leverages FOMO, social proof, and scarcity to create a sense of urgency for consumers to purchase a product or service. This post covers the evolution of product drops and the four main modes of drops and how consumer founders should best use drops to their advantage.

Read this post

2) 🏌️Curated

Curated empowers experts/enthusiasts to make money from talking about their biggest passions and helps shoppers to make the right purchase with the guidance of a domain expert. In this post, we dive into the back story of Curated, the economics of Curated’s business model, along with its unique expert-led growth framework. A great read for folks in e-comm/marketplaces.

Read this post

3) 🎨 Figma

Figma, one of the biggest tech darlings of 2022, was recently acquired by Adobe for a whopping $20B. This post dives into Figma’s genesis, its main differentiators compared to other competitors and its secret community-led growth engine. This post is my personal favorite. A ton of great learnings for founders who want to build a brand with a cult-like following.

Read this post

4) 🦸Superhuman of x

Superhuman, known for creating the fastest email experience, is the category-defining company in the productivity space. Not only did they revolutionize how to build a superior user experience, but they also pioneered the frameworks for how to build product-market fit and onboard customers in a delightful way. Since then, many “Superhuman of x” startups have entered the space - they are using superior design, better collaboration, and useful integrations to disrupt old-school productivity tools that had not changed much in the past decades. 

Read this post

5) 🤖 Opportunities in generative AI

Generative AI has the potential to be another massive platform that will propel the next generation of startups. We are hitting an inflection point where you no longer need tons of money or be a Stanford AI Ph.D. to create a high-quality AI-powered application. This new technological advancement will unlock tons of entrepreneurship opportunities for consumer founders. This post dives into opportunities in the space.

Read this post

See you in 2023 👋,

Leo

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I love traveling, but I dread the planning and logistics part of a trip. Since prices of flights and hotels fluctuate so much, I would often spend hours refreshing the pages of Bookings scouring for the best deals. I refuse to pay 50% more than the guy sitting next to me on the same flight.

I was excited to learn about Hopper during the pandemic, an AI-powered app that can help me monitor flight and hotel ticket prices and recommend the best time to purchase them. It gets me good deals, but most importantly, saves me tons of time.

Hopper has quietly become one of the most popular travel apps. It had over $2B in travel sales in 2021 and skyrocketed to the number one most downloaded travel booking app in Q3 of 2021 as travel demand started to recover (as shown in the graph below). It was recently valued at $5B from a secondary share sale, which took place just five months after its $175M Series G round of funding. 

Hopper did not have the meteoric rise that we have accustomed to seeing with tech startups in the past few years. Quite the opposite - the Hopper team worked on the wrong product for more than half a decade before pivoting to the Hopper we know today. 

For today’s Consumer Startups, we are diving into Hopper and taking a look at:

1. Hopper’s genesis

2. Hopper’s pivot and journey finding product market fit

3. Hopper’s growth journey 

4. Hopper’s unique growth drivers - push notifications, contextual recommendations, and custom ads engine

Let’s do it!

Hopper’s genesis 

Hopper’s founder Frederic Lalonde is no stranger to the travel tech industry. He built Newtrade Technologies in 1997 to help hotels connect their reservation systems with other online distribution channels, such as Expedia. Seeing great potential synergies, Expedia acquired Newtrade in 2002 to accelerate its growth and connectivity within the hotel vertical. Lalonde stayed on to lead Expedia’s hotel and packages business.

At Expedia, Lalonde witnessed the boom of the online travel booking business, which stands at over $350B globally today. However, these online travel products have remained similar, a search engine for consumers to compare prices and purchase travel products online. At the same time, Lalonde also saw the rise of Big Data. There had been a ton of content and data about travel, but there was no product built around it. 

This insight gave birth to the initial idea for Hopper, a travel planning tool that helps you discover destinations and travel activities using keywords such as “hikes around the world”. In 2007, Lalonde left Expedia and teamed up with a former Expedia and Newtrade engineer, Joost Ouwerkerk, to start building the V1 of Hopper.

The pivot 

How hard could it be to build a travel discovery tool? 

It turned out to be quite a monumental task. Lalonde and his team spent 7 years building the product in stealth, trying to create a proprietary technology that can crawl the web to find travel content (in blog form) and return ones that are the most interesting for consumers. 

Over that 7-year time span, Lalonde and his hopper team put their heads down building the travel planning and search product. They had raised $22M up to that point from the likes of OMERS Ventures, Bright Ventures, and Atlas Ventures. After burning through millions of dollars, they finally released their web-based platform to the public in 2014. 

After launch, the site started seeing some traffic from Google Search and Facebook. However, growth was slow and somewhat stagnant. It dawned on the team that they still did not have a product-market fit after 7 years of building.

Luckily, they caught a major break when Hopper got featured in a New York Times article. To everyone’s surprise, the article was not about the core travel discovery website they launched, but it was about a small tool they built buried at the bottom of the website. It was a simple tool that could give you tailored advice on what day and time to book the cheapest flight ticket based on the flight route of your choice.

“Take a very popular route, like J.F.K. to Los Angeles International Airport, for which Hopper’s report uses 57 million fares quoted in the last month. Turns out you’d be crazy to book Thursday through Monday, since, according to the graph I got, you would save an average of $45 or so by booking on Wednesday (Tuesday is somewhere in the middle). You’ll also find that returning

Tuesday will save you an average of $35 over returning Thursday through Sunday. ” - NYT

It went viral and Hopper’s future started looking a lot more promising.

However, just as they were seeing substantial growth, Lalonde decided to shut down the website and relaunch Hopper as a mobile app 🤯. 

The idea was to double down on that viral tool that had built and create an app that helps travelers to monitor ticket prices and recommend the best time to purchase, based on billions of historical flight price data. At the time, it was a controversial decision because the website product had just started to gain momentum on the back of the NY Times article. In addition, mobile only accounted for 12% of the online travel category in terms of transactions. This pivot also meant killing all the content and SEO they had built throughout the years. 

Lalonde made this call because he saw an opportunity to build a truly differentiated product in a fast-growing mobile segment. He worked in India previously and witnessed firsthand how online travel went from 12% mobile to 60% in just one model as cheap Android phones hit the market. They had to move fast to benefit from this tailwind!

Ballsy move but it worked.

Hopper’s growth journey

Phase 1 - Reaching PMF

Despite not having any iOS engineers at the time of the pivot, they still somehow made it work and launched the app in 2015. The app is a more elaborate version of the viral tool they built previously, using data and analysis from billions of historical flight prices to tell travelers when they should buy their flight tickets. 

This time, the launch hit it out of the park and the Hopper team could barely handle the growing demand from its users. By September 2016, just a year and a half post-launch, Hopper reached the following milestones:

• More than 20M downloads 

• Sold over $600 million worth the flights in the app

• Added one million new users each month 

• Ranked #1 travel app in over 37 countries 

According to Lalonde, the biggest validation for product-market fit is when you can deliver that wow factor - a moment when a user understands the value of your product and tells all their friends about it. Hopper app has that wow factor.

“The wow factor for Hopper is that when we deliver a push notification to your phone for something you asked for and suddenly you saved a ton of money from airfare. 

It's not about the savings but it's because at that moment you realize that you never ever have to plan your own airfare again and shop 13 websites until midnight. You know you can just tell Hopper what you want and they will deliver the good.” - Frederic Lalonde at ScaleupFest

Nothing matters in the early stage of a company until you can find that fit and deliver that wow factor.

Phase 2 - Horizontal growth

As Hopper seemingly took over the online flight booking world by storm, it also started eyeing the next big travel segment - hotel bookings. Similar to flight tickets, hotel prices also heavily fluctuate based on real-time demand. 

Fortunately for Hopper, the same proprietary price prediction engine they developed for flights works well for hotels as well (with some tweaks). For travelers, the value proposition remains the same - Hopper helps you predict hotel pricing and tell you when to buy or wait to get the best hotel deal. Additionally, unlike airlines, travelers can sometimes get private rates that aren’t easily accessible on the web. Hopper can monitor both public rates and private rates to ensure traveler gets the best price. 

In late 2017, Hopper launched this hotel segment in New York City, and in 2019, Hopper rolled out this offering to over 200 countries with over 270,000 hotels. 

In recent years, after seeing the success of hotel expansion, Hopper has also expanded to car rentals and short-term home rentals to increase the stickiness of the platform and become the go-to app for all travel needs.

Phase 3 - Building a travel super app

Super apps are quite common in Asia. They help users to fulfill all their needs with just one app. For example, the biggest social app in China, WeChat, not only has social networking features but is also a popular app for payments, grocery shopping, and even investments. Hopper has the opportunity to become the super app for all travel needs.

It has a strong suite of product lines that cater to most travel needs from flights to car rentals, but it has also expanded vertically to offer a thoughtful list of services that make travel less stressful for travelers. 

During the peak of the pandemic, travel was extremely stressful. Flights were getting canceled left and right due to staff shortages and covid outbreaks, and it was incredibly frustrating for travelers to deal with immense uncertainty. To address these issues, in 2020, Hopper launched its suite of fintech products to ease those headaches. With a small fee, travelers can get access to:

1. Refundable Booking - flexibility to cancel and get 100% of booking value back for future bookings

2. Flexible Dates - Change the date or time of your flight for any reason up to 24 hours prior to departure. 

3. Missed Connection Rebooking - allow travelers to rebook the next flight to their destination no matter the airline

4. Flight Delay Protection  - if your flight is delayed for more than 1 hour, you will immediately receive a credit to book a new flight on any airline to your destination so that you can get on your way sooner.

These options offer travelers peace of mind and help Hopper create additional revenue streams. According to Lalonde, Hopper generates nearly 40 percent of its roughly $1.3 billion annual revenue comes via fintech products. 

Hopper’s unique growth drivers

There are many reasons for Hopper’s strong growth today. Besides having a strong product market fit, another huge reason lies in its ability to grow efficiently without throwing away massive amounts of marketing dollars. According to Hopper’s ex-Head of User Acquisition, Simon Lejeune, industry incumbents, such as Bookings and Expedia, spend Hopper’s entire annual marketing budget in just a few hours.

In a conference hosted by Appsflyer, Simon pointed out three killer growth drivers that have contributed significantly to Hopper’s growth engine - push notifications, contextual recommendations, and custom ads engine.

1. Push Notifications

When Hopper first got started, it used to only send push notifications when it was time for users to place a purchase. The team soon realized those notifications were getting lost and people were not sure if the app was even working. To create that trust with users, Hopper started sending a lot more notifications to inform users whenever there is a noticeable price movement. For example, they would say ‘Your flight to SF went down but you should wait longer for a better price.’ This proactive communication approach lets users have peace of mind to know the app is working and increases conversion when the app is pushing the user to make a purchase. Today, Hopper sends out over 1B notifications to users every year.

2. Contextual recommendations

Hopper’s biggest advantage is the amount of data it has on its global user base. It can create accurate cohorts, predict a user’s travel preferences, and use those data to recommend other relevant flight routes or hotels. For example, after noticing a user has been monitoring a flight to Rome for two weeks, the app might send out a notification to the user about a flight deal to Milan based on travel behavior from similar users. This contextual recommendation engine has contributed to 20% of Hopper sales according to Simon. Another surprising fact is that Hopper users convert 2.6x more with trips recommended by the system than the ones they searched for in the app themselves. 

3. Custom ads engine

Hopper found that custom ads related to a specific deal perform the best in acquiring the right users. To scale this process, they have built their unique Hopper ads engine to create tailored ads for users. Every day, it pulls the top deals on the platform, generates image assets based on those deals like “Fly to Paris from $448’, and then sends them automatically to ads platforms like Instagram and Snapchat through API integration. Ads budget also gets automatically adjusted based on performance. As a company built on top of big data, Hopper has also leveraged data science to optimize its performance marketing. Quite an impressive feat.

What do you think about Hopper? Please reply directly and let me know what you think. I would love to hear from you :)

See you soon 👋,

Leo

Follow me on Twitter @_leoluo

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Last time, I wrote about some emerging consumer AI startups that caught my attention. Since that post, I have gotten many replies from the community wanting to learn more about the space, specifically B2C opportunities in AI. 

One of the most significant breakthroughs in AI in the past decade is arguably generative AI, a topic that has seemingly taken over the entire startup universe in the past few months. In layman’s terms, it’s an AI program that can generate some output content, such as text, image, video, speech, or code from some input. For example, I was able to generate the picture below by typing ‘A robot writing on a computer with a dog, sitting in a garden, green, oil painting’ in Midjourney, a text-to-image AI program. 

Many startups have already started to monetize this technology at scale. Jasper, an AI writing tool for marketers, just announced its $125M Series A at a $1.5B valuation and is expected to make $90M in revenue by the end of 2022. Many indie builders have also found success with building with generative AI. One of the legendary indie hackers, Pieter Levels (who also goes by @levelsio on Twitter), reached $5K MRR with its AI interior design generator platform interiorai.com in just a few weeks.

Generative AI has the potential to be another massive platform that will propel the next generation of startups. We are hitting an inflection point where you no longer need tons of money or be a Stanford AI Ph.D. to create a high-quality AI-powered application. This new technological advancement will unlock tons of entrepreneurship opportunities for consumer founders. For this post, I teamed up with my good friend, Markus Mak, to dive into this topic. We will cover the following:

1. The history of generative AI

2. Top generative AI models and their capabilities

3. Generative AI ideas for consumer founders

4. Risks and opportunities

Let’s jump right in.

History of Generative AI

Before discussing some of the opportunities in the consumer space, let’s first understand what generative AI is and how we got to where we are today. 

Generative AI refers to AI models’ ability to create something new. Generative AI is powered by deep learning, which is a technique that underlies most artificial intelligence these days, ranging from self-driving cars to recommendation engines. Generative AI is propelled by two major advancements in deep learning research: Generative Adversarial Network (GAN) and Generative Pre-trained Transformer (GPT).

Here’s all you have to know about the history of Generative AI.

Before 2014, CNN, the best image model at the time, could only do classification tasks, i.e. it could tell you whether a picture is a dog but couldn’t create a dog image on its own. Old language models, such as RNN, struggled with remembering the context when generating long sentences or paragraphs. 

In 2014, Ian Goodfellow proposed the GAN after dreaming up the idea of pitting a neural network against another. GANs gifted computers with the ability to create hyper-realistic images, such as those images of people who don’t exist. In 2017, the Google Brain team introduced a revolutionary transformer architecture for language in Attention is All You Need, outperforming RNN. This is because RNN processes sentences word by word while transformers process sentences together, allowing transformers to remember the context better when generating long paragraphs. Transformers are now used to power most state-of-the-art models, such as GPT-3. 

The biggest problem with GAN is that it can only generate images with limited variety. To solve the problem, some models utilize the transformer architecture but extend their applications to image data, such as Dall-E (2021) and Dall-E 2 (2022). Some other models, known as latent diffusion models (LDM), leverage another class of models called diffusion models and combine them with GAN and transformers. This is the underlying architecture that powers models like Stable Diffusion. 

Why now?

• Low computing cost: the computing cost has dropped significantly over time, making the training cost and usage of large generative models affordable for mass adoption. New models such as Stable Diffusion further lower the hardware requirements to run the model such that everyone can do it with their personal computers.

• High-quality models: these large-scale generative models, like GPT-3, perform very well across a wide range of tasks; some can even perform previously unimaginable tasks, such as creating an AI-generated podcast between Joe Rogan and Steve Jobs. 

• Ease of implementation: since these large-scale generative models are pre-trained and are for general purposes, they can be used straight out of the box. Model users only have to run the model by supplying inputs to the model, which can be achieved with a handful of lines of code. Most models also have a no-code option on their website as a lightweight option for users to play around with.

Generative AI landscape and opportunities

The opportunities within generative AI are immense. There are four main segments based on the output form factor of the generative AI model - text, image, speech, and video. There are numerous applications associated with each one. 

For example - with generative text, marketers can use it to create contextually relevant blog posts based on some keywords to save time. With generative images, interior designers can use the technology to generate design ideas for their clients to augment their own creativity. With generative speech, newsletter writers can convert a written post into a podcast, unlocking additional distribution channels. With generative videos, teachers can create video content from images or text, making learning more engaging for students.

For the next part, we will discuss each of these four output form factors, unpacking the leading AI models that companies are using along with their capabilities, different applications in the market today, and startup opportunities for consumer founders. 

(1) Text 

AI Models

Language is the most fundamental mode of communication that transcends space and time and permeates the fabric of our everyday lives. The launch of GPT-3 in 2020 shocked the public with the machine's ability to generate hyper-realistic human-like texts, drawing attention to the potential of these large-scale language models. Some state-of-the-art models include:

1. GPT-3 is developed by Open AI with 175 billion parameters and costs $12M to train. New users get $18 in free credit for the first three months to experiment with the API. Afterward, the entry model costs $0.0004 per 1k tokens, which is approximately 750 words. You can access it via its web app or its API.

2. EleutherAI is an open-source alternative to GPT-3, meaning it’s free to use! Its GPT-Neo-20B has 20 billion parameters and has a similar implementation to GPT-3. GPT-J-6B uses a different model architecture with 6 billion parameters. You can access it via its web app or API.

3. Bloom by Hugging Face is the largest open-sourced multilingual language model with 46 natural languages and 13 programming languages trained with 176 billion parameters. You can access it via its web app or API.

AI Capabilities

We divide the capabilities of language models into three levels. The first-order capabilities are the fundamental features of most models, including text completion, insertion, and editing. Second-order capabilities are some of the more dynamic use cases or applications of the first-order capabilities, including chat, Q&A, translation, parsing data, and classification, such as sentiment analysis. Third-order capabilities refer to the concept of ‘embedding’ – using the result of a language model as an input to other machine learning algorithms to create even more complex use cases. This opens up more advanced abilities, such as smart search and recommendation engines.

Startups in the Space

Opportunities

There are three main types of writing:

1. Fact-based writings that are descriptive or narrative

2. Creative writing, such as writing a story 

3. Reasoning writing that focuses on developing complex logic

The current models are capable of creating most fact-based writing (Q&A search engine, Wordtune), followed by basic creative and reasoning writing capabilities accompanied by human intervention for quality control (e.g. Copy.ai, AI Dungeon, GPT-3 Spreadsheet). As the models mature, there will be more opportunities to replace higher reasoning and creativity-demanding tasks. 

Some ideas below: 

1. Marketer: AI-generated articles with different marketing focus/optimizations (e.g. SEO optimized articles)

2. Writer: vertically optimized writing assistance focusing on niche use cases such as homework assistance/correction, blogging, creative writing, grant writing, and more

3. Entertainment: script/story writing, interactive and fully customized storyline for each audience

4. Knowledge assistant: summarize knowledge, generate new knowledge, automatic knowledge map builder…

(2) Image

AI Models

Image generation has generated a significant amount of buzz lately, propelled by OpenAI’s public release of Dall-E 2. Besides Dall-E 2, there are several world-class AI models used to generate images, including Midjourney and Stable Diffusion. Each of these could be useful depending on the use case. 

1. Dall-E 2 is an AI model released by the leading AI research lab, OpenAI. It attracted over 100K beta users even before the September public release. First-time users get 50 free credits to try it out and can buy more for commercial usage. You can access it via its web app or API

2. Midjourney is an AI model created by an independent AI lab, Midjourney. It currently operates using a Discord bot, but it already has an active community of 1M+ people. Users can generate images based on a discord command. Like Dall-E 2, you have a certain amount of free usage limits, and then you have to pay 

3. Stable diffusion is an open-source AI model released by Stability AI. It is free to access and does not have as many restrictions as Midjourney and Dall-E 2. However, it only has basic safety features (e.g. preventing offensive content) 

AI capabilities

Depending on the model, there are different capabilities. The first common capability is text-to-image. You can generate an image based on a text description, such as “an astronaut lounging in a tropical resort in space, pixel art.” The second capability is image editing. You can replace or add certain elements to an image from a text caption. The third common one is image variant generation. By uploading an image, the AI can create variants of the same image. 

Below is an illustration of how you can put these three together using Dall-E 2:

Startups in the space

Several startups are making waves in this space by leveraging this image-based generative technology. 

Opportunities

The AI generative image space is relatively blank. We have not seen many major commercial successes just yet. However, we expect to see more vertical creator tools that focus on serving niche communities. 

Here are some ideas:

Product designers: AI version of Dribbble. Tools or plugins that help product designers to find design ideas for their features

Graphic designers: AI asset creation and editing tool. Making it easy to create, edit, and create variants of a specific icon or image asset. 

Photographers: AI-powered image editing platform to reduce the time it takes to edit professional-grade photos. 

Creators: cover image generator. Generate a cover image based on an article. 

Marketers: 10x easier ways to create social media assets 

(3) Speech

AI models 

Even though most speech AI models today focus on transcription(e.g. OpenAI’s whisper), there are still many models that enable text-to-speech(TTS). Hugging Face offers 200+ open-source TTS models for different languages, from English to Ukrainian. They have a user-friendly interface where you can also test out the speech outputted by the model.

One of the most liked and downloaded models from Hugging Face TTS is the Fastspeech2 model released by researchers at Meta AI. 

AI capabilities

The core capability of TTS is to convert text into different voices. However, when combined with other models, such as AI speech-to-text transcription and transcription, there could be many more possibilities.

Startups in the space

Opportunities

Speech generation can be helpful in many settings.

Here are some ideas:

Real-time audio translation: make it easier to have audio conversations in different languages in real time. Language is no longer a barrier, no matter where you live. 

Podcast generation: generate a podcast from an essay. It can be especially useful for newsletter writers or bloggers who are looking to expand distribution channels but don’t have the bandwidth.

Nostalgic chatbot: exchange audio messages with a bot that sounds like a late family member.

Language buddy bot: the best way to learn a language is to speak it. It would be cool to practice a language by exchanging audio messages with a language buddy bot.

(4) Video

AI models 

Video generation AI is still in its infancy due to the significantly greater complexity compared to the aforementioned form factors. To quote from a recent post by Mark Zukerberg, “it's much harder to generate video than photos because beyond correctly generating each pixel, the system also has to predict how they'll change over time.”

The model that received the most media attention recently is Meta’s Make-A-Video, which has text-to-video capability. However, it cannot generate clips that are longer than 5 seconds with resolutions higher than 768x768 pixels at 16 frames per second. Currently, the only publicly available text-to-video model is CogVideo, which also has many limitations, such as the length of the video. The model Phenaki, recently released by Google Brain in September 2022, can generate longer coherent stories with different concepts. We would expect more mature infrastructure to pop up in the near future. 

AI capabilities

Mainly basic, short, low-resolution video generation since the technology is still in the early phases of research.

Startups in the space

Opportunities

Marketers: create videos that optimize your marketing objectives and metrics, e.g. virality, clickthrough, …

Entertainment: huge opportunities in the entertainment industry once computers can generate hyper-realistic videos, e.g. generate movies/shows

Risks and opportunities

Risks

“With great power comes great responsibility.” Generative technology is immensely powerful, and with misuse, it can cause great harm to society. AI research companies like OpenAI are doing a good job of including safety features in their released models, such as filtering out discriminatory content; however, many AI models today are open-sourced and are not equipped with needed safety features. They are subject to misuse, and there have already been instances where generative technologies are being used to distribute misinformation and harmful content. 

Opportunities

There are many new opportunities with the rise of generative technology. Generative technology has the potential to increase efficiency for marketers, improve creativity for designers, enable more distribution channels for content creators, and create new opportunities for many, many more.

With companies like Jasper, we are just starting to see what is possible with generative technology. We have reached a point where not only are the models getting really good, but they are also accessible and affordable. With just a few lines of code and some training data, you can start unlocking the potential of generative AI. The key now is to find real problems that can be solved with generative technology.

Given how easy and cheap generative AI capabilities are, it is important to consider how your idea builds a moat (e.g. data, network effects, switching cost…) to maintain long-term competitiveness. James Currier from NFX has a great 4-question framework for thinking about what is a good generative tech idea:

1. How can it have network effects where every new user adds value to every other user?

2. How can it embed itself in a business or someone’s life so they don’t want to stop using it in the long run? This is Jasper’s job in 2023 to figure out.

3. Where are the hyper-local data sets for your AI model that you can own and maintain your data network effects despite competition coming in later?

4. Where can you plug into existing workflows, a browser, or an app?

It’s time to build!

Useful generative AI articles to check out:

• Generative AI: A Creative New World by Sequoia Capital - Link

• Generative Tech Begins by NFX - Link

• Who Wins the AI Value Chain by Napkin Math - Link

• Hugging Face - Link

That’s it for this week! See you soon 👋,

Leo & Markus 

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A few days ago, I read a tweet about a new AI model called Action Transformer (ACT-1), launched by Adept AI. In simple terms, it’s a model trained to use digital tools. By reading some high-level user requests, ACT-1 can execute the tasks on a web browser, such as finding you a home on Redfin. It blew my mind.

There have been several other breakthroughs in AI, such as OpenAI’s new language models like GPT-3 and Dall-E. One main driver for this progress in AI lies in increasing corporate investments in AI. In 2021, companies globally invested $176B into AI, with a significant portion of those coming from private investments. By comparison, there were just around $5B in investments 8 years prior.

Despite all the new developments, the majority of the AI applications we see are still concentrated in the B2B world, specifically enterprise software. Out of the 10 newly minted unicorns in the AI space this year, all of them are B2B companies.

However, in the past couple of years, I have seen more and more AI companies disrupting B2C sectors as well. Besides the big ones like TikTok and Duolingo, many emerging consumer startups are leveraging deep learning and other AI technologies to deliver their core value prop.

For this post, I would love to share some of the interesting ones I have found. Let’s dive in!

1. Welcome

Unique insight: it’s hard to find cool, authentic experiences when you travel to a new city. When searching online, consumers mostly find results that are advertised placements.

Product: It’s like Tiktok meets Google Maps. Welcome is an AI-powered personalized travel guide that recommends experiences based on the user’s interests and the people they trust. When the user gets on the app, they can see a TikTok-like feed of videos about places around them and across the world (curated by Welcome’s street team), and the user can save them to a map for later. Over time, Welcome learns about the user’s interests based on their interactions in the app and makes more relevant recommendations in real time.

Traction: Welcome has acquired over 50K beta users across more than 350 cities globally. It has raised $4.2M to date from investors like Accel and Lakestar Ventures.

2. Lunchclub 

Unique insight: Sometimes, a casual conversation can change a person’s life. The right introductions and meetings can lead to companies being started, new ways to think about ideas, and collaborations on new projects. 

Product: Lunchclub started as an in-person, one-on-one coffee chat matchmaking platform and pivoted into a virtual networking platform that connects people to have conversations without borders. The magic behind Lunchclub is its machine learning-powered matching platform. The platform builds a comprehensive profile for each user by collecting information about their interests and goals and uses those information to match relevant people for a casual chat. After each match, it also collects feedback from each user, which serves as another piece of data for the AI to improve matching quality and precision in the future. 

Traction: Launched in 2017 in the US, Lunchclub created 1M connections and grew 15x in 2020 alone according to Business Insider. It raised a $30M Series A at a $100M valuation from investors like Lightspeed, a16z, and Coatue. 

3. Boomy

Unique Insight: The music industry hit a growth inflection point in 2016 due to the explosion of demand for streaming music. However, only people with resources and music education could benefit from this rapidly growing industry since music production tools can be expensive and turning ideas into tracks requires tons of skills. The Boomy team started the company with the goal of leveraging AI to democratize music creation for everyone.

Product: Boomy operates as a vertically integrated indie music label, powered by AI. Boomy users can come to the platform and use AI to generate songs by selecting different genres and styles they like. Based on the output, the user can either reject it or edit it themselves before publishing them to streaming platforms like Spotify. Users get to keep 80% of the streaming revenue their songs create and Boomy takes the rest.

Traction: Boomy is a seed-stage company that started in 2018. Boomy users have created more than 9 million songs, around 9.28% of the world's recorded music. 

4. Finesse

Unique Insight: The fashion industry is an inefficient industry that has not been touched by technology for a very long time. Fashion companies set up themselves to produce merchandise cheaply without knowing what will sell. As a result, the fashion industry is the second-largest polluter in the world - 85% of everything produced ends up in landfills. However, with the increase in big data, specifically social media data, there is an opportunity to reliably predict consumer demand and address this inefficiency.

Product: Finesse is a vertically integrated fashion house that uses social media data and machine learning, along with community feedback, to decide what style to create and how much they want to produce. The Finesse AI engine has a two-step process. It first collects data from millions of social media comments, learns about what shoppers are looking for in clothes, and catches trends before they go mainstream. Once trends are identified, it creates 3D designs of merchandise which are shown to the Finesse user community. Users can then vote on the designs that they like. The final voting result can also inform the team on consumer demand and how many pieces they should produce.

Traction: Finesse recently raised an $11.3M Series from TQ Ventures, Cherry Ventures, and many more. They have a strong fanbase on social media, with 400K+ followers on TikTok and 340K+ followers on Instagram.

5. Hopper

Unique Insight: It’s not a secret that airlines charge different prices depending on when the ticket is purchased. Every traveler wants to buy their tickets at the best price; however, it’s hard to do so due to constant price fluctuation and information asymmetry.

Product: Hopper is an OTA that uses its machine learning prediction engines to help travelers decide whether they should buy their flight tickets now or wait for a better price. It accomplishes this by tracking all the flight tickets and using data to predict future price volatility. Combined with some other factors, such as the flexibility of the traveler and their risk aversion level, Hopper recommends the best time for the traveler to purchase their flights. It also has the same capability for hotel booking. Watch this video if you are interested in learning more about Hopper’s AI engine.

Traction: One of the fastest growing players in the travel space, Hopper has had over 70M downloads to date and booked $2B+ on travel sales in 2021. It recently did a secondary transaction that values the company at $5B.

6. Justpoint

Unique Insight: Legal services are archaic and inefficient. It’s hard for people to find the most suitable lawyers for their specific needs, ones that will most likely win them the case. 

Product: Justpoint is an AI-powered platform that connects people with the right litigation lawyer and tools, with a focus on the personal injury space. It helps plaintiffs to find the lawyer that is best suited to solve their case based on historical cases. It also helps lawyers by taking on back-office tasks while improving litigation discovery using machine learning so that the lawyers can quickly understand the merits of the claim and obtain the best results. Lawyers on Justpoint work on contingency and get paid based on a percentage of the settlement amount. Justpoint makes money by taking a cut from that percentage. 

Traction: Justpoint works with 1000+ law firms and receives over 100 cases per day. It raised a $6.9M seed round earlier this year from investors like Divergent Capital, Charge Venture, Weekend Fund, and many more.

7. Photomath

Unique Insight: Tutoring is a multi-billion dollar market for parents to seek out supplemental education for their children outside of the traditional classroom. However, private tutoring tends to be expensive and inaccessible for many families. As a result, many students tend to turn to their parents or the internet for answers- neither could provide the students with the adequate resources they need to understand the concepts behind the problems. 

Product: Photomath is an AI app that helps students to solve tough math problems and explains the methodology so that students can understand the principles and concepts behind the answers. To use the app, students first need to snap a photo of the problem with their phone. The image then gets analyzed by Photomath’s neural network, which provides the formula for the scanned problem. After determining the formula, Photomath applies a problem-solving algorithm to the formula to provide the solution with a step-by-step explanation. Photomath makes money by offering a premium paid subscription called Photomath plus, which offers more support for the students. 

Traction: Photomath has gotten over 300M app downloads and solves 2.2B problems per month. It raised a $23M series B last year led by Menlo Ventures.

8. Tonal

Unique Insight: Traditional strength training requires many unwieldy weight plates to create resistance. Tonal founder, Aly Orady, realized that you can leverage electromagnetic technology to create resistance that’s comparable to weights. Combined with AI, this technology would allow you to create a smart, electronic strength machine that you can place in your home. 

Product: Tonal is a smart home gym machine powered by electromagnetic technology and AI. It has three main components - smart workout equipment, personalized training software, and training content. The equipment is an all-in-one workout machine with a touch screen display along with accessories you need for the workout, such as handles and bars. The software uses machine learning to provide users with personalized training, recommending users the most suitable workout and weight level based on previous workout data. In addition, Tonal has a large and growing content library with workout classes that users can watch on demand. 

Traction: In 2021, Tonal raised a $250 Series E led by Dragoneer at a $1.6B valuation. It has expanded to 54 physical sales stations across the US after a recent partnership with Nordstrom.

9. Whisper AI

Unique Insight: According to Johns Hopkins, more than 38M Americans suffer some form of hearing loss and many of them require hearing aid support. However, most hearing aids today require thousands of dollars in upfront cost and do a poor job of adjusting to the noises in different environments. There is a big opportunity to create a modern hearing aid company to address these pain points.

Product: Whisper is an AI-powered hearing aid product that adjusts the sound quality based on your surroundings and improves over time from software updates. Whisper’s hearing system has three components - 1) hearing aids that fit on the ear 2) a pocket-sized external box called Whisper Brain that works wirelessly with the earpieces to enable a proprietary AI-based sound separation system 3) a smartphone app that you can use to update the software on the system so you don’t have to worry about replacing them every few years. The main AI sound separation engine uses deep learning to distinguish and separate different sounds even in the most challenging environments, such as restaurants or any crowded places, making it easy for users to still hold conversations in those environments. In addition, to increase affordability, Whisper offers a monthly payment option of $69 per month, instead of charging $2000+ upfront.

Traction: Whisper raised a $35M series A in 2020, led by Quiet Capital, with participation from Sequoia Capital, First Round Capital, and IVP.

This is part 1 of this topic. Please reply directly if you would like to see part 2 where I plan to dive into more consumer AI startups and some potential opportunities in the space.

See you soon 👋,

Leo