Finding PMF in the paying user cohort

ClientStealth App

TimelineJune to August

Result3 Lakh paying users

It was a brand-new content platform with no paying users till now. We had the responsibility to find the product-market fit and find the paying audience cohort where the CAC-LTV equation would make sense.

01STEALTH APP × VIDROW · CASE STUDY

Problem Statement

Stealth App is in the content space and had the app ready based on the earlier user research but it was unclear which features within the app and which audience cohort would be the power users. It was a brand-new content platform with no paying users till now. We had the responsibility to find the product-market fit and find the paying audience cohort where the CAC-LTV equation would make sense.

02THE OUTCOME

Zero to ~3 Lakh paying users in 80 days

When we arrived, product was ready but we had to find the right paying cohort for Stealth App. June was month one.

We executed our playbook for PMF within content. Across June to August we increased the paid user acquisition from 0 to 10,000 paid users per day while holding the CAC-LTV equation.

Paying users

3 Lakh

JuneAugust

03THE USER JOURNEY

We finalised the consumer journey and tested different price points

01The feature
One feature
2–3 different ads. Different hooks. Same destination.
02The ad
Sees Ad
Sees the feature in a way that speaks to them and clicks.
03The install
Downloads
Downloads the app directly from that same ad.
04The set-up
Set-up
Language & phone number. 2 taps and they are in.
05The landing
Launches
Opens on that feature. No home screen, no searching.
06The ₹1 trial
Takes Trial
Takes the ₹1 trial for a 3-day period.
07Conversion
Trial Run
Experiences the feature during trial. Product does the selling.
08The autopay
Paid User
Trial ends. Autopay charges the first payment automatically.

Every one of those ~3 lakh paying users came out of this flow. Autopay switching on is the moment we counted.

04HOW WE DID IT

We tested 12 features. Three came out as winners

With nothing proven, backing one feature would have been a guess with a budget attached. So every feature on the shelf went out with its own batch of ads, all judged on the same paid event and the cost of a paying user decided which ones earned more budget.

Test12

Total Features to talk about

We tested ads across each feature. 10 ad sets were tried for each feature separately

Measure1

Measure of Success

We only tracked the first autopay payment and nothing else

Pick3

Features worth Backing

At the end 3 features came out as winners and a very clear audience cohort emerged. We doubled down on scaling these features within the audience cohort

Scale77%

of All Paying Users came from these 3 features

came from the 3 features they first landed on.

05THE PRODUCT-MARKET FIT

The Ads found the Product Market Fit

Share of paying users from those three features

19%in June
56%in July
77%in August

What it unlocksLTV

The number they can finally plan against

Along with paying customers we also checked the paying cohort retention across different price points and arrived at a final product - price - audience fit.

06THE OUTPUT

The scale up phase 3 months later

The paying users are the result. What Stealth App keeps is the machinery that produced them: every feature priced by what a customer costs, every audience mapped, and a weekly loop that re-ranks the shelf on results.

Creative600+

ad sets made for 3 features during scale up phase

Customer payback period~3 Months

Paying users acquired3,00,000

Daily acquisition rate achieved10,000

paid users / day

Growing from here is no longer a guess. They know what to buy, and what it costs to buy it.