Context
Shaz & Kiks sells Ayurvedic haircare into the US market, led by a turmeric (haldi) shampoo. I ran Meta end to end for six months — campaign structure, scaling, optimisation, and weekly creative direction. Meta drove approximately 90% of store revenue during the period.
Problem
Ayurvedic haircare is an education-first category in the US. The ingredients are unfamiliar to most of the target audience, which means a conventional product-led ad has to overcome a comprehension gap before it can overcome a purchase objection. Direct-response creative that simply showed the bottle and the offer did not carry that weight.
The commercial constraint was tight: monthly spend started at $1,500. There was no budget to buy reach and let frequency do the work. Efficiency had to come from the creative.
Hypothesis
If the audience doesn't know what haldi is, the ad has to teach before it sells. Founder-led educational video explaining the ingredient — what it is, where it comes from, what it does for hair fall — would convert better than product-forward creative, and would hold CPA as spend scaled, because education compounds where offers fatigue.
What I did
Founder-led ingredient education. Recorded video with the Indian founders explaining haldi directly: its origin, its traditional use, and the mechanism behind its effect on hair fall. This became the primary creative engine rather than a supporting asset.
Influencer application and results content. Before-and-after application videos from creators, used to close the credibility gap that founder education opened.
Video-only creative strategy. Every ad in the account was video. Static was not competitive in a category that requires explanation.
Weekly creative iteration and winner scaling. Reviewed performance weekly, identified winning angles, and scaled behind them rather than rotating a fixed creative set.
Launch and waitlist mechanics. Built new product launches around waitlists, which concentrated demand at launch and gave the account fresh, high-intent audiences to scale into — a second lever on CPA beyond creative alone.
Result
| Metric | Mar – Sep 2024 | Change vs prior period |
|---|---|---|
| Total store revenue | $230,389 | +23% |
| Orders | ~2,500 | +19% |
| Sessions | 108,690 | +7% |
| Conversion rate | 1.98% | +16% |
| Average order value | ~$92 | +3% |
Meta economics:
| Metric | Value |
|---|---|
| Monthly spend | $1,500 scaling to $3,500 |
| Total spend | ~$16,500 |
| Meta-reported ROAS | ~7x |
| Blended MER (store revenue / total ad spend) | ~14x |
| Blended CAC | ~$6.60 |
| CAC to AOV ratio | 1:14 |
Meta drove approximately 90% of store revenue over the period. Platform-reported ROAS sits well below blended MER, which is the expected gap under post-ATT attribution — the account was the primary revenue driver by a wide margin regardless of which figure you read.
The number that matters most is the split between traffic and conversion. Revenue grew 23% while sessions grew only 7%. Conversion rate contributed roughly twice as much to revenue growth as traffic did. Monthly spend more than doubled over the period and conversion rate went up 16% — the opposite of the usual pattern, where scaling into colder audiences costs efficiency.
Educational creative was the reason. Traffic arriving from a founder explaining the ingredient already understood what it was and why it worked, so it converted at a materially higher rate than traffic bought against a product shot.
Source data
Shopify analytics, Mar 1 – Sep 30 2024, compared against the preceding period.
What constrained the result
The sharp drop across all metrics in late September was a stockout, not a media failure. The hero SKU went out of stock and I had to redirect spend onto secondary products that had not been proving out. Revenue and conversion rate fell together, which is the signature of an inventory problem rather than an account problem.
The account had been scaling cleanly to that point. With inventory held, the trajectory in the charts through mid-September was the real run rate.
What I'd do next
- Build creative around the second and third SKU before they're needed. The stockout exposed a single-product dependency. The educational format was proven; it just hadn't been applied to the rest of the catalogue in time to absorb the shock.
- Test subscription on the hero product. A $92 AOV at $7 CAC with a consumable product is an obvious subscription case, and it would have made the stockout far less damaging.
- Segment by education depth. Founder-led and influencer content almost certainly serve different stages of awareness. Splitting them by audience temperature rather than running both broad is the next efficiency gain.
- Formalise the waitlist mechanic. It worked and was run manually. Systematised across every launch, it becomes a repeatable audience-building channel rather than a one-off tactic.
What this demonstrates
- Efficiency at scale, not just scale. 2.3x spend increase with conversion rate improving 16%.
- Creative strategy as the growth lever. The account's performance came from an education-first creative thesis, tested and scaled weekly, not from budget or bidding.
- Category insight. Recognised that an unfamiliar-ingredient product in a new market is a comprehension problem before it is a conversion problem, and built the account around solving that.
- Honest attribution. Store-wide figures, with Meta's ~90% share stated rather than implied.