Case study: a women's handbag online store — ROAS up 2.3× in 3 months

An online store selling women's handbags, totes and belt bags made from eco-leather. Their own production in Ukraine since 2020, on the market since 2008, with an accumulated base of over 10 000 buyers. Advertising was running, but at the edge of profitability — every dollar invested barely came back.

Problems at the start

• ROAS held at ×2.1–2.3 — at the brand's margin the business was breaking even or running a small loss.
• High cost per order (CPA): the budget was going to non-targeted traffic.
• No end-to-end analytics — it was unclear which channels actually drove sales.
• The Meta and Google algorithms "couldn't see" purchases because of misconfigured events.

Three months on, every dollar invested started returning nearly $5 in revenue (ROAS ×4.8). Instead of "feast or famine" — a predictable flow of orders at a clear price, and the owner can see where every hryvnia goes. The budget stayed within $1800–2000/mo — only the efficiency changed.

No technical details — here are the four steps that lifted the return, and what each one gave the business.

1. First — honest analytics (CAPI)

We set up server-to-server delivery of order events (Conversions API for Meta and Google via GTM) — in real time, with deduplication, no losses or double counts. Once the algorithms saw real purchases, simply from the right data the visible efficiency of the ads grew by +15–20%.

2. We rebuilt the campaign structure

Before us, everything sat in a single campaign — the budget was spent inefficiently. On Meta we split "cold" traffic from "hot" retargeting, a split by category (handbags, evening models, totes, belt bags) and A/B creative tests; for product campaigns we turned on Advantage+ Shopping. On Google we laid out the structure by intent stage: Shopping catches people already looking to buy, while a search campaign on brand queries brings back those searching specifically for StarBags.

3. We recovered abandoned carts

We launched dynamic retargeting: anyone who added an item to the cart but didn't buy saw those exact handbags and a separate discount offer for the next 7–14 days. Abandoned carts are the most underrated source of sales: the share of repeat sales grew to 18% of ad-driven sales.

4. Creatives that sell

Instead of "grey" product cards — video (Reels and Shorts: unboxing, in-motion reviews, styling with outfits), photos of real buyers and seasonal time-limited offers. That more than doubled the click-through rate — and brought far more qualified buyers to the site, not random clicks.

Under the hood — Conversions API and transaction deduplication, a product feed in Merchant Center and passing order statuses from the CRM back to the algorithms, so the ads learn from real buyers. I'll gladly walk you through the technical details on a call.

The average order value stayed stable (~$70). The higher return came from the efficiency of the ads, not from inflating prices — the business earns more from the same range and the same $1800–2000/mo budget.

For the owner

Every dollar invested brings nearly $5 in revenue. Instead of chaotic spikes — a predictable flow of orders and full transparency: you see where every hryvnia goes and which channel drives sales.

For the team

The sales team is unburdened — the inquiries are now targeted and "hot". There's room to scale: the algorithms are trained on real buyers, so the budget can be raised carefully, tracking ROAS weekly rather than blindly.

• Meta Ads (Facebook/Instagram) — Conversions API, Advantage+ Shopping.
• Google Ads — search, Shopping ads.
• Google Tag Manager + GA4 — end-to-end analytics and transaction delivery.
• Google Merchant Center — product feed.
• CRM integration — passing order statuses back to the algorithms.

Within the same $1800–2000/mo budget, revenue grew 2.3×. Three things do the work. Correct analytics: without CAPI and GA4 the algorithms work blind — you pay for traffic, not for buyers. The right structure: a single campaign for everything spends the budget inefficiently, while a split by category and funnel stage lifts ROAS several times over. Cart retargeting: abandoned carts are the most underrated source of sales. On this project that approach reached ×4.8 ROAS and paid for itself within a few weeks — on a different store the figures will differ, but the logic is the same.

A quick word on money: the project had two budgets. The ad budget — $1800–2000/mo — was paid by the client straight to the platforms (Meta, Google) for impressions. The setup and management work was billed separately — a fixed fee, not a percentage of the budget, so there was no incentive to inflate the spend. Analytics, creatives and reporting were included in that fee.

Today akitalab's main focus is lead generation for service businesses: the Accelerator, a client-acquisition system. The same precision-tracking principles — CAPI, attribution, training the algorithms on real sales — apply there as well. Details on the Accelerator page.

Will you repeat the same ×4.8 ROAS in my store?

Honestly — the figures will differ. ROAS depends on margin, range and season: StarBags reached ×4.8, elsewhere it might be ×3 or ×6. What carries over isn't a magic setup but the logic — correct tracking (CAPI), splitting campaigns by funnel stage and cart retargeting.

Did the budget really stay the same?

Yes, it held within $1800–2000/mo — swings of up to $200 inside the test, with no extra money poured in. The higher return came from the efficiency of the structure and tracking, not a bigger budget.

Do you take on online stores right now?

akitalab's main focus today is lead generation for service businesses (the Accelerator). This case is proof of performance-marketing competence, not a separate e-commerce service. If you run a store, get in touch — I'll tell you honestly on a strategy session whether I can help.