Cal AI’s Co-Founder Shares His App Growth Secrets

Co-founder Blake Anderson scaled Umax with influencer marketing at a smaller scale than Cal AI; the same principles were reused at Cal AI.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.