Sinsay
automated advertising catalog (Advantage+) measured across channels
In 2025, Sinsay (LPP Group) combined Meta's Advantage+ catalog ads with omnichannel ads, achieving in a lift test 9.5x omnichannel purchases, +54% incremental ROAS, and -43.3% cost per incremental purchase in the Czech Republic.
Key points
- Omnichannel social advertising via Meta's Advantage+ catalog ads and omnichannel ads.
- Meta Advantage+ stack (catalog, audience, placements) and Conversions API for measurement.
- Omnichannel purchases x9.5, incremental ROAS +54%, cost per purchase -43.3%.
- Evidence level B, measured in a conversion lift test (Czech Republic, Oct-Nov 2025).
Objective
Increase the omnichannel purchases (web, app, store) generated by paid social while maintaining ad budget efficiency.
The deployment
Sinsay, the fast-growing fashion brand of Poland's LPP Group (women, men, kids, present in about 26 markets), shifted its social advertising to a fully omnichannel approach. The brand combines Advantage+ catalog ads, whose machine learning function automatically pulls personalized visuals of relevant, shoppable products from the catalog feed, with omnichannel ads covering web, app, and store. Advantage+ audience lets the algorithm go beyond the brand's core targeting parameters, and Advantage+ placements automate delivery. Tracking runs through the Meta Conversions API to connect online and offline events. The brand validated the contribution through a multi-cell conversion lift test comparing Advantage+ catalog ads alone with the catalog + omnichannel ads combination, run in the Czech Republic from October 14 to November 11, 2025.
Results Proof B
Quantified platform (Meta) case study, results from a dated and named conversion lift test, corroborated by established press on the brand's scale and momentum.
How it works
Inferred typical approachThe internal detail is not public. Here is a proven approach that leads to the same result, to adapt to your stack.
How it runs, concretely
For ops teams-
1Feed the product catalog data / e-commerce team
Maintain an up-to-date catalog feed (visuals, prices, availability) that Advantage+ machine learning draws on to compose personalized ads.
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2Connect omnichannel measurement data team
Send online and offline events via the Meta Conversions API to connect in-store purchases to campaigns.
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3Launch Advantage+ catalog + omnichannel ads marketing / paid social
Activate catalog ads, Advantage+ audience and placements, let the algorithm broaden targeting beyond the core audience.
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4Measure by conversion lift marketing / paid social
Compare in a multi-cell test catalog alone versus catalog + omnichannel to isolate the incremental contribution.
The omnichannel purchase events (web, app, store) sent via the Conversions API; without this signal, the optimization loses the measure of incrementality and omnichannel steering breaks.
How your customers perceive this type of use
Sourced studiesLe pricing algorithmique est le terrain le plus inflammable : 68% des consommateurs disent se sentir leses quand les marques utilisent le pricing dynamique et 80% jugent plus dignes de confiance les marques aux prix constants (Gartner, 2024). L'equite percue varie selon le secteur : le pricing dynamique n'est juge juste que par 33% a 40% des repondants selon qu'il s'agit de concerts ou de cinemas (YouGov, 17 marches). Le prix personnalise par les donnees individuelles est le plus rejete : 47% des Americains s'y opposent fermement (Consumer Reports, 2024).
Acceptance conditions
- La constance des prix comme signal de confiance : 80% jugent plus fiables les marques aux prix stables (Gartner 2024)
- Le secteur conditionne l'equite percue : le pricing dynamique est mieux tolere pour les cinemas (40% le jugent juste) que pour les concerts (33%) (YouGov 2024)
Red lines
- Le pricing dynamique percu comme abus : 68% se sentent leses (Gartner 2024)
- Le prix individualise a partir des donnees personnelles : 47% d'opposition ferme (Consumer Reports 2024)
- Les frais caches et hausses imprevues, vecus par 79% des consommateurs sur un an et associes a la perte de confiance (Gartner 2024)
Sources: Gartner 2024 · YouGov 2024 · Consumer Reports 2024
How to replicate
Inference, not sourcedData prerequisites
- A clean, up-to-date product catalog feed (visuals, prices, availability)
- Tracking of online conversion events via pixel / Conversions API
- The ability to send in-store purchases (transaction ID, offline matching)
Org prerequisites
- A physical store network to justify omnichannel measurement
- Alignment of data / e-commerce / paid social on a shared definition of incremental purchase
- A legal basis and GDPR consent for event sharing
Possible stack
- Meta Advantage+ catalog ads
- Meta Advantage+ audience and placements
- Meta Conversions API
- The platform's native conversion lift tool
The plan, step by step
- Step 1Structure and make the product catalog feed reliableDeliverable: Synchronized catalog usable by the machine learning
- Step 2Deploy omnichannel measurement via the Conversions API (web, app, store)Deliverable: Unified and attributed purchase events
- Step 3Activate the Advantage+ catalog campaigns and the omnichannel adsDeliverable: Automated delivery broadened beyond the core audience
- Step 4Frame a multi-cell conversion lift test to isolate incrementalityDeliverable: Readout of the real contribution of the omnichannel setup
First step: Verify that in-store purchases can be sent to Meta via the Conversions API: this is what makes omnichannel measurement possible.
The same pattern, proven in other industries
Allwyn
AI-driven omnichannel programmatic buying with retail data activation
Nivea
genAI testing and optimization of creative elements + automated localization at scale
Clarins
AI-automated sales campaign plus dynamic catalog ads, evaluated on incrementality via Conversion Lift against last-click
Sources
- S1 Sinsay Clothing: driving omnichannel growth with Advantage+ and omnichannel ads Interested party archive pending
- S2 Poland's Sinsay opens 91 stores in 19 countries in record 1-week rollout Established press archive pending
An error, newer info, a source?
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