Case study: fashion accessories, Poland
One product, worn many ways, and an account that wasn’t getting the most out of it. In the first two months with Kliks, WhyNot’s Meta ads delivered a 7.4x ROAS, tripled monthly orders and cut cost per purchase by 59% compared with the start of the year.
- 7.4xROAS, Sep–OctUp from 3.3x in Jan–Aug 2026
- −59%Cost per purchaseVersus the Jan–Aug average
- 3xOrders per monthVersus the Jan–Aug average
- +32%ROAS year-on-yearVersus Sep–Oct 2025
- 2+Months and ongoingSince September 2026
The challenge
Great product. Uneven results.
WhyNot sells the otulacz: a multi-way wrap that works as a scarf, a hood and a layer in one piece. It is a genuinely useful product with a clear selling point, and it sells hardest when the weather turns cold.
In the first eight months of 2026 the paid account didn’t reflect that. Return on ad spend swung from under 2x to over 6x from one month to the next, and both volume and revenue were running well below the year before.
Challenge
Seasonal demand
Most of the year’s sales land in the cold months. The account had to be ready before the season started, not catching up halfway through it.
Challenge
No stable baseline
With ROAS jumping around month to month, there was nothing reliable to scale from. Budget decisions were guesses.
Challenge
Shrinking volume
Spend had been pulled back and orders followed. The brand needed more sales, not just a better ratio on fewer of them.
The objective
Three goals. One season.
Win the winter season
Be fully set up and scaling before peak demand, so the brand’s strongest months are also its most profitable ones.
Lower the cost of every order
Make each złoty of spend buy more sales, measured on real purchase economics rather than clicks.
Build a creative pipeline
Fresh photography and formats ready to test, so winning ads can be replaced before they wear out.
The approach
Four moves. One engine.
A season-first account structure
We stopped spreading budget across leftover summer campaigns.
Spend was consolidated into one winter campaign built for the cold-weather range, so the algorithm learned from a single, focused stream of purchase data instead of several thin ones.
Before
- Budget split across summer campaigns
- Several thin data streams
- Volatile month-to-month ROAS
After
- One focused winter campaign
- Consolidated purchase signal
- Stable 7x+ ROAS
Product-led creative
The product’s best argument is that it does several jobs. The ads say exactly that.
Creative leads with the “one wrap, many ways” idea and shows it on real people outdoors, in real weather, so the use case is obvious within the first second.
New photography, tested by format
Fresh images went in as a structured test, not a guess.
New autumn photography launched in its own test campaign in October, run across formats so we can see which images and placements earn more budget before peak season.
Scale, hold, cut
Every ad gets a verdict within a set window.
Budget moves toward the ads with the lowest cost per purchase and away from the ones that stall. No ad keeps spending without earning its place.
The results
The jump that tells the story
Through January to August 2026, monthly ROAS bounced between 1.9x and 6.1x. In September, the first month with Kliks, it moved to 7.3x, and October held at 7.5x on higher spend. Orders per month roughly tripled, and cost per purchase fell to well under half of what it had been.
Compared with the same two months of 2025, ROAS is up 32% and cost per purchase is down by a third.
ROAS is shown as a ratio, Meta-reported purchase value over spend. Revenue and spend figures are confidential. October covers 1–29 Oct 2026.
ROAS trajectory
Jan → Oct 2026, Meta (Facebook & Instagram)
Monthly ROASBreak-even: 1.0xKliks from Sep: 7.3–7.5x
Before Kliks
3.3x
Average ROAS, Jan–Aug 2026
- Cost per purchaseIndex 100
- Orders per monthIndex 100
- ROAS range1.9x – 6.1x
- Account structureFragmented
After Kliks
7.4x
Average ROAS, Sep–Oct 2026
- Cost per purchaseIndex 41 (−59%)
- Orders per monthIndex 301
- ROAS range7.3x – 7.5x
- Account structureSeason-first
Revenue trajectory (indexed, Jan = 100)
Relative growth shape. Absolute figures confidential.
Index relative to January 2026 Meta-attributed revenue. Shape reflects real month-over-month movement; October covers 1–29 Oct.
The build
How it moved, month by month
- Jan–AugROAS 1.9–6.1x
The starting point
A capable product with an unpredictable account. Spend had been reduced and summer campaigns were still splitting the budget.
- SepROAS 7.3x
Winter campaign live
Budget consolidated into one cold-weather campaign. ROAS more than doubled the Jan–Aug average and orders tripled.
- OctROAS 7.5x
Held on higher spend
Spend increased and efficiency held. New photography launched in its own format test to feed the next round of winners.
- NextPeak season
Scaling into the holidays
Black Friday and Christmas are the brand’s biggest weeks. The structure and creative pipeline are in place to scale into them.
What makes this different
Not just ads. A sales system.
Most agencies focus on
- Keeping every old campaign running
- Spreading budget thin across ad sets
- Reacting to the season once it has started
- Reusing the same images for months
- Reporting reach and clicks
This engagement focused on
- One focused campaign per season
- Concentrating spend where the data is
- Being ready before peak demand
- A steady pipeline of tested creative
- Real purchase economics: CPP, ROAS, orders
Key impact
What actually changed
A stable, scalable account
ROAS went from swinging month to month to holding above 7x, giving a reliable baseline to scale from.
Three times the orders
Monthly orders roughly tripled against the Jan–Aug average, without the efficiency dropping.
Cheaper customers
Cost per purchase fell 59%, so every złoty of spend now buys more than twice as many orders.
Ready for peak season
A focused structure and a tested creative pipeline are in place before the brand’s biggest weeks of the year.
Conclusion
From uneven results to a reliable engine
WhyNot didn’t need a new product or a bigger budget. It needed its spend focused on the right season, its best selling point put front and centre, and clear rules for what gets more budget.
With those in place, the same account produced more than twice the return and three times the orders, and it is set up to scale into the busiest part of the year.
The system was built on
- Season-first structure
- Product-led creative
- Systematic testing
- Data-first decisions
- Not guesswork.
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