How Cal AI grows

Started with ~5 marketing assistants, grew to ~25, each pushed to contact 100 influencers a day (~2,000/day; real output 40-70 on bad days). Assistants hired through an outside staffing company. Outreach is by email, not DMs (DMs are rate-limited and work mainly with a big personal brand). Creators in the US, UK, France, Germany, Spain; not picky as long as the creator could fit the app into their video at a decent CPM. Assistants send a Calendly link for a manager call; managers close. Signing goals of 50+, later 100 creators a month. Funnel: ~10% reply, a few book a call, ~1 in 1,000 signs. Outreach tracked in an internal system.

Started with a required later second mark for the app integration so it wouldn't feel like an ad, then tested bringing it in earlier and earlier until finding the earliest point that didn't hurt views. For Cal AI that was 20-30 seconds in. A friend's app found 60 seconds. Test your own number.

TikTok and Instagram block messaging after a certain number of DMs per day, so Cal AI created about 20 extra Cal AI accounts, one per outreach specialist, each reaching out to hundreds of creators a day.

Sign large creators who post day-in-the-life vlogs. They show their day and quickly scan a meal with the app, often without saying its name. Aim for four videos per month per creator so followers see it repeatedly. Track with promo codes. Example: Jessi from The Secret Lives of Mormon Wives.

Discount offer used as an extra placement (on opening the app a second time, on transaction abandonment, or after a trial cancel). Instead of a plain '80% off' paywall, the user sees an animated spin wheel that stops on a discount ('You got 80% off. Tap to get it'); tapping continue opens the discounted paywall. Idea: add excitement and make the discount feel earned. Borrowed from e-commerce popups.

At launch, watch which creators and formats cause download spikes and what their comment sections look like, then use those patterns to judge content later. Early on there were no downloads on days without a creator video; later a ~100/hour baseline would jump to ~200 when a video went live. At scale, old videos keep getting views, so use data analysis and incrementality tests.

Split fitness into sub-niches: bodybuilders, gym bros, women's fitness, weight loss. Then tested mom influencers (expensive because they know they convert), and comedy/viral creators (e.g. the 'no door, no problem' drive-thru guy, signed to scan fries at McDonald's). Some niches only needed one video or one creator.

When a creator says they can 'easily get a million views', agree and add a minimum view clause a couple hundred thousand below that (e.g. 800K, or 700K after checking their page), framed as 'just for our safety' and 'so it's not stressful for you'. Payment is tied to hitting the floor each month. Check their actual numbers first so the floor is realistic and hit every month.

Message signed creators monthly: 'Do any of your friends want brand deals?' Pay ~$100-200 to the creator if a referred friend signs. Referred creators send a personal phone number, so you call the influencer directly, sometimes bypassing their management.

Picked the health and fitness niche, which is oversaturated with creators but has few brands (mostly protein powder and athleisure), so many creators had no way to monetize. Pitched them to show the app inside content they already make (what I eat in a day, losing weight, building muscle): before eating, scan the food with Cal AI on camera. Easy for creators and didn't disrupt their schedule. Then reached out to thousands of creators to sign them.

Don't force formats or scripts on influencers: only general guidelines on how to show the app, how many seconds in it should appear, and a tag to include in the caption. Otherwise full creative freedom. Reason: if a creator deviates from their usual format (infomercial-style 'let me tell you about Cal AI'), views collapse (e.g. 50K instead of the 1M the CPM was priced on); keeping the normal format lets you estimate average views with confidence.

Offer a deal like $400 for four posts and add, as a casual aside, that each post should be cross-posted on both platforms since the video already exists. Keep it low-key: if you make it a big deal, creators will too.

Managing a 10K-view creator takes as much work as a 1M-view one, so the floor is 25,000 average views per video. Very large creators (millions per video) have more general audiences that follow recommendations less; the sweet spot is 25K-1M views per video, where audiences are cult-like and convert best.

Compare comment sections: a real community (long personal replies, people replying to each other) converts far better than fire-emoji spam. To catch fake engagement, click the profiles of good commenters: bots have zero posts, follow ~10 people and have zero followers, and the same fake accounts show up on every video.

Built an internal tool: one click sends the contract; once signed, the creator is added to the platform and gets a text with the content brief asking which day they will post; the reply is piped into a content calendar; each morning the team gets a batch of texts to send to creators scheduled to post that day.

Outreach accounts carry a person's name so creators know they aren't talking to a faceless brand. Instead of a wall of text, send a voice memo so it feels like a real person; record one generic memo and copy-paste it to every creator.

When a creator replies 'what's your budget?', don't lead with price. Explain the deal first: seamless videos, long-term partnership, no script, 'keep doing what you're doing and sneak our app in'. Once they seem interested, ask to jump on a call to finalize; discuss rates only on the call. Manager runs the same script on every call, starting by getting to know the creator. Deals are declined if the creator won't come down to a profitable price.

Pick creators who can fit the app's 'golden moment' (snap a photo of food to log calories) into their normal video. No script and no heavy ad read; creators often just show themselves scanning a meal without naming the app. The app must appear within the first 15 seconds.

With Jessi (The Secret Lives of Mormon Wives), timed a couple of posts just before season 3 was released and a couple just after, when everyone was visiting her page. Deal landed through a team member's relationship with her influencer manager.

Monthly competitions: prize (cash or voucher) for the assistant who contacts the most influencers, and for the one whose referrals (tracked by 'referred by' on signed deals) sign the most.

Ignore follower counts; judge creators by average views per video. Target creators who average huge views but have few followers (e.g. new accounts going viral): they're not used to big brand-deal fees because brands pay on followers, so they accept reasonable rates.

Add paid ads once cash flow allows, because influencer/UGC views are volatile while Meta spend gives steady ROAS. At first, reused influencer/UGC videos as ads (the only content they had). Once funded, built a paid ads department with dedicated ad creators: ads bring the product in early and hard-sell, since you pay for every view and there is no algorithm boost to protect.

At launch the app was unknown, so aim for the lowest CPM to reach as many people as possible, assuming the first exposures won't convert ('seen seven times' rule). As more creators promote it and viewers recognise it, raise what you pay per deal. Goal: sign as many influencers as possible and saturate the fitness space.

Worked with recipe, normal cooking and mukbang creators on the assumption that food viewers think about calories. Cut them early; healthy-meal creators were kept but converted only moderately.

Team member built a relationship with an influencer manager for the Mormon Wives cast, which led to deals with Jessi. When working through agents, push to have the influencer added to the shared group chat so you build a direct relationship, even though agents often refuse. Keep in touch with creators long-term.

After one creator paid $20K for a month drove $120K of signups (~$100K profit), signed another creator in the same niche.

Four co-founders each owned one domain: CEO (Zach), co-founder/investor/advisor (Blake), CMO/COO for marketing and operations (Jake), CTO managing the tech team and product (Henry). Complete trust to handle their area; team said this avoided fights.

Product-led growth features: progress photos users can post to Instagram stories showing weight lost/gained; shareable meal cards showing calories tracked with Cal AI; milestone badges for consecutive days logged (e.g. a full year) to post on stories.

Cal AI pays many creators (and puts spend behind some posts) for TikTok day-in-the-life videos: workout, come home, snap a photo of a meal, get calories, move on. Shows the core differentiator (logging by photo) as part of normal life rather than as an ad.

After health and fitness, kept testing new creator sub-niches; new moms worked. Continuous testing ('always be testing').

Tested mukbang creators and UFC fighters as new sub-niches for the calorie app.

Did a couple of day-in-the-life videos with UK Love Island's Harry Cooksley. Tried to also sign his partner Shakira through him, but it never happened.

Zach, with childhood friend Henry, sent a DM to Blake, who had already built AI apps, and they formed Cal AI; later offered a COO role to Jake after seeing his work at StudyBuddy. Blake says he would not have replied to a copycat pitch.

At end of 2024 the team received low eight-figure offers; co-founders called each other constantly and reached a collective decision not to sell because they saw more growth ahead. Later sold for an undisclosed larger amount.

Cal AI's main growth is influencer marketing with fitness creators: there are very many, they are reasonably priced, and a calorie tracker doesn't conflict with the coaching they sell. Contrast with Sway, where dating coaches sell profile feedback themselves, and beauty creators, who are expensive because of makeup brand deals.

Started with a scrappy app that did not fully do what the marketing claimed, sold it through strong distribution, then built out the underlying tech. Priced at $29.99/year.

Cal AI hit a major inflection when it seriously ramped paid ads on top of influencer marketing; same pattern at Sway. No detail on platforms or spend.

Base rate of $350-$450 for four posts, plus a couple of unlockable view bonuses. Cap bonuses, usually at 1M views: profit comes from the one or two viral videos a month, so you need to keep their upside; people don't perceive much difference beyond a million; and very viral views reach a broad, less-targeted audience that converts worse.

Take the creator's 20 most recent videos, pick the 5 (or 10) worst performers, average their views, and base the CPM price on that worst-case average. Be careful with very recent videos that may still be growing.

Sideshift is the easiest source (post a job, creators apply) but ~99% of applicants aren't good. Preferred: type 'UGC creator' into the explore page and scroll for people who feel real, not scripted. Pay a base of ~$25-30 per video for all videos (~$600/month) plus a view bonus; one 1M-view video a month brings the effective CPM to ~$1.50-2.

Ignore target CPMs; compute RPM (revenue per 1,000 views) from past creator videos, then price each influencer deal on expected views so CPM stays under RPM. Paid ads can afford the highest CPM (direct link, least friction), influencers need a lower CPM (viewer must go search the App Store), UGC accounts lower still (no audience trust). High-LTV categories like clothing or telehealth can outbid a typical consumer app on CPM.

UGC creators open new TikTok/Instagram accounts dedicated to the app (e.g. jake.eats, jake.tracks) where every video is about Cal AI. Unlike influencers, micromanage them and copy formats already proven to go viral. New accounts are shown mostly in the creator's own country, so hire creators in the country you target.

Where an influencer lives doesn't matter; where their audience is does. Ask for audience demographics when signing; skip a creator with ~1% of views from your target country.

Shipped a groups feature (community feed) where friends log food and stay accountable together, with leaderboards showing longest streaks; later added public topic groups (weight loss, bulking, recipes and meal prep), inspired by Strava and Ladder. Aim: retention plus a network effect that the many Cal AI clones can't copy.

Because Cal AI grows mainly through influencer videos, and every video shows the same three screens (camera, loading screen, food detail page), design work focuses on making those three screens as easy to understand on camera as possible.

Main paywall has a free-trial toggle; turning it off does not change the price, it just lets users who want to buy now do so and feel in control. Guest uses this for high-intent apps (health and fitness, weight loss) and the discounted version for lower-intent or younger audiences; advises testing both.

Built an internal system where, after an assistant sends the first outreach email, AI handles the replies and initial negotiation/persuasion, then hands the creator off to a manager for a call.

Early on, a creator (Dawson) with his own personal brand made UGC and posted on the Cal AI page. Stopped once influencer deals gave better CPMs. Now restarting UGC because agents have pushed influencer prices up. Guest would run UGC and influencers side by side for a new app: UGC gives cheaper views but likely lower conversion.

MyFitnessPal acquired Cal AI not for its tech but for its top-of-funnel skill (Zach and team are strong distributors), aiming to keep new users coming in and eventually graduate them to MyFitnessPal's fuller feature set. Guest's reading, prompted by the host.

Focus on getting users through Cal AI's 3-day trial without cancelling: fix bugs and redesign the screens people touch all the time when logging a meal (food database, camera, food detail page).

Added streaks so users come back daily to log meals, modeled on highly retentive apps like Duolingo.