Masai reduced dependence on
Influencer marketing for scaling

Masai's performance came from influencer marketing on Instagram, Twitter and LinkedIn. It did not scale, and growth stagnated. The job: scale performance marketing with cost per booking under control, and creative costs low.

Masai - India's fastest growing career schoolVidrow x Masai

~700 creator led ads in a period of 6 months each ad with different hook and communication unlocking different audience cohort

ClientMasai
Timeline10 Months
Result20x Scale, at same CAC
01·THE SETUP

Creative Volume

Masai runs online tech courses. Nobody buys one off an ad; they book a paid slot for Masai's entrance test first, so every ad in this account is bought and judged on test bookings. Masai already ran a large Meta engine with creative arriving from several sources, and Meta funds whatever performs.

01Window

6 Months

First 3 months for testing and 3 months scaling.

02Scope

9 Different Courses

AI & ML, product management, analytics, MBA and more.

03Reach

3 Languages

Hindi-English, Tamil and Telugu.

04Output

~700 Ads made

Each shipped with multiple hooks into the account across the six months.

02·THE GROWTH

Growth scaled 5x
in six months.

We partnered with Masai from Dec'25. Since then we've scaled Masai performance marketing engine to nearly five times while sustaining the CAC, and reducing the reliance on expensive influencer marketing.

Creator led performance marketing helped open new audience cohorts for Masai along with predictability on CAC

1X
Nov 2025
20X
Sep 2026
03·HOW WE DO IT

Our Creative Strategy

Three sources feed the Meta ads, the right creator carries it, and every concept ships with three different hooks as three separate ads. Meta decides which of them survive, and that answer sets the next batch.

Instagram trends
New concepts
Winner Double down

Right Creator

We keep the creators who convert and drop the ones who do not. Right face meant who would look as an edtech expert

Hook

Every concept goes out with three different hooks, each as its own ad.

Did not work → Discard
Meta decides which ad is winning and which doesn't scale
Worked → Double down
every result, win or loss, goes straight back into next week's batch

First 3 months went into deciding which are the winning communication angles across different courses and audiences. Next 3 months were spent in scaling it

04·WHAT WE WON

The Outcome

Even with scaling, the CAC didn't increase. In fact, even at scale we
were able to lower the cost per enrolment by 27%.

-27%Lower Cost per Enrolment
05·WORKS

Ads

More deep dives.

See all case studies