DL-058 · Case study
Retail media incrementality measurement for a beauty group
A beauty group investing heavily in marketplace advertising needed to separate advertising-attributed sales from broader changes in retail demand.
- Client
- Name withheld
- Location
- France
- Industry
- Beauty and consumer packaged goods
- Capabilities
- 01Audit03Build
01
Challenge
- Advertising teams primarily reported attributed conversions and return on ad spend.
- Commercial teams lacked a consistent framework for evaluating incremental performance.
- Promotions, organic demand and retail media campaigns were analyzed separately.
02
Environment
- Amazon Ads, Amazon Marketing Cloud where authorized, and available retail reporting.
- Snowflake data warehouse and internal campaign planning records.
- Multiple brands and European marketplaces.
03
Intervention
- Audited existing measurement assumptions, reporting definitions and data availability.
- Designed standardized campaign, retail and promotional datasets.
- Built analytical models for controlled comparisons and experiment reporting.
- Established documentation distinguishing observed attribution from estimated incrementality.
04
Outcome
- A more rigorous retail media measurement framework.
- Comparable reporting across brands and campaign types.
- Better visibility into the limitations and uncertainty of advertising performance estimates.
- 01AMAZON ADSCampaigns→RETAIL DATASales
- 02RETAIL DATASales→MODELSnowflake
- 03MODELSnowflake→EXPERIMENTSComparisons
- 04EXPERIMENTSComparisons→DASHBOARDSDecisions
Stack and services.
Stack03
Services used01
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