AI Showreel consulting-grade analysis, for everyone FR
← The index
Proof B Live confirmed

Bruna

AI-automated sales campaign plus Conversions API, measured incrementally by Conversion Lift, on a seasonal peak

IndustryRetail & e-commerceLeverAcquisitionFamilyOptimization / automationImplementationMartech platformStagediscovery -> purchase
Pattern proven in 8 industries still untouched in Media & entertainment, Travel & hospitality, Food & beverage +5 See the pattern map
50 %
Share of revenue generated via Meta technologies
"50% of revenues generated via Meta technologies" S1

In 2024, the Spanish brand Bruna generated 50% of its revenue and 38% incremental purchases via Meta Advantage+ and the Conversions API, measured by Conversion Lift over the wedding season in Spain, France, and Belgium.

Key points

  • AI-automated Meta sales campaigns (Advantage+ Shopping) over the wedding season.
  • Server-side Conversions API for measurement, incrementality via Conversion Lift, with the agency Roas Hunter.
  • 50% of revenue via Meta, 38% incremental purchases, 62% of add-to-cart events.
  • Evidence level B, confirmed active status.

Objective

Drive online sales during the wedding season, in a highly competitive sector, by measuring Meta's real contribution rather than attribution alone.

The deployment

Bruna, the Spanish brand of customizable jewelry and accessories, handed its sales campaigns on Meta to Advantage+ Shopping mode, where the AI chooses audiences, placements, and creatives from the product catalog. The account was connected to the server-side Conversions API to make purchase reporting reliable, then measured with Conversion Lift studies over the high-demand wedding period in Spain, France, and Belgium. The work was carried out with the agency Roas Hunter, a Meta partner based in Valencia. On this setup, 50 percent of revenue was generated via Meta technologies, 38 percent of purchases were incremental, and 62 percent of add-to-cart events came from Meta technologies.

Results Proof B

50 %
Share of revenue generated via Meta technologies
"50% of revenues generated via Meta technologies" S1
38 %
Share of incremental purchases attributed to Meta technologies
"38% of incremental purchases attributed to Meta technologies" S1
62 %
Share of add-to-cart events generated by Meta technologies
"62% of add-to-cart events generated by Meta technologies" S1

Official Meta partner case study (Meta Business Partners), quantified, backed by the Conversions API and Conversion Lift studies, with founder and agency named; single source published by the platform and its partner.

How it works

Documented architecture
boucle d'optimisation en incremental Catalogue produit +signaux d'achat Feed produit + Conversions API IA Meta : audiences,encheres, placements,creas Meta Advantage+ Shopping Feed Facebook / Instagram+ Advantage+ placements Achat en ligne Mesure incrementale Meta Conversion Lift

The stack in detail

  • plateforme Meta Advantage+ Shopping Campaigns Meta's automated sales format: the AI chooses audiences, bids, placements, and creatives from the catalog feed.
  • outil Meta Conversions API Server-side reporting of purchases and add-to-cart events, so the algorithm optimizes even when the browser blocks tracking.
  • outil Meta Conversion Lift Incrementality studies with exposed / unexposed groups, used to isolate the share truly generated by Meta.
  • integrateur Roas Hunter Meta partner media agency based in Valencia, which ran the setup with Bruna's e-commerce team.

How it runs, concretely

For ops teams
CadenceContinuous delivery, with a ramp-up on the seasonal wedding peak; incremental measurement in Conversion Lift waves.
Operated byThe agency Roas Hunter with Bruna's e-commerce team.
  1. 1
    Make purchase measurement reliable Agency / data team

    Server-side Conversions API so that each sale is reported even when the browser blocks tracking. This is the fuel for optimization.

  2. 2
    Deliver via Meta's AI Meta AI

    Advantage+ Shopping chooses audiences, placements, and creatives from the catalog. The team provides feed and visuals.

  3. 3
    Measure incrementally Agency / Meta

    Conversion Lift studies isolate the share truly generated by Meta during the wedding peak, to arbitrate the budget.

The signal that drives it

The purchases and add-to-cart events reported by the server-side Conversions API. Without that server signal, the algorithm loses conversions blocked by the browser and optimizes less well.

How your customers perceive this type of use

Sourced studies

Le 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).

68%
Consommateurs qui se sentent leses (taken advantage of) quand les marques utilisent le pricing dynamique (2024)
80%
Consommateurs d'accord pour dire que les marques aux prix constants sont plus dignes de confiance (2024)
79%
Consommateurs ayant vecu des situations de prix inattendues sur un an (surge pricing, frais caches, hausses imprevues) (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

See full acceptance: by country, by use, by generation

How to replicate

Inference, not sourced

Data prerequisites

  • Clean and up-to-date product catalog (feed)
  • Server-side Conversions API with reliable purchases and add-to-cart events
  • Sufficient volume for Conversion Lift studies

Org prerequisites

  • A seasonal peak or a concentrated budget to arbitrate
  • Agreement to steer on incrementality rather than last click

Possible stack

  • Meta Advantage+ Sales Campaigns + CAPI (server-side GTM, Shopify or partner)
  • Conversion Lift or geo-test as the arbiter
Team to operate1 Meta media buyer (in-house or agency) + 1 developer for the Conversions API.

The plan, step by step

  1. Step 1
    Connect the server-side Conversions API (server-side GTM, Shopify or partner) and check deduplication with the pixel.Deliverable: Purchases and add-to-cart events reliably reported.
  2. Step 2
    Clean the catalog feed: titles, images, prices, stock, and categories up to date.Deliverable: Catalog validated in the Meta catalog manager.
  3. Step 3
    Launch the Advantage+ Shopping campaign with the budget concentrated on the seasonal peak, without manual over-segmentation.Deliverable: Campaign in the learning phase.
  4. Step 4
    Let the algorithm optimize; monitor frequency, creative fatigue, and placement distribution.Deliverable: Stabilized campaign, log of adjustments.
  5. Step 5
    Measure the incremental share via Conversion Lift (or geo-test) and arbitrate the budget on that basis rather than last click.Deliverable: Incremental reading and budget decision documented.

First step: Connect the server-side Conversions API then launch an Advantage+ Shopping campaign, and measure its incremental share via a Conversion Lift on the seasonal peak.

Sources

  1. S1 Roas Hunter: Meta Business Partner Advantage+ Success Story - Bruna Interested party facebook.com · 2024 · accessed 2026-07-11 archive pending
  2. S2 Meta Advantage+ Sales Campaigns: AI Automated Shop Ads Interested party facebook.com · 2024 · accessed 2026-07-11 archive pending