Case StudiesRetail Practice
11Large-Format Home Improvement Retailer · Creative Attribution
Ad Theme Attribution & Creative Science for Data-Driven Marketing Investment
DataInc.ai built a creative science measurement framework that connects ad themes, messaging strategies, and visual attributes to downstream sales outcomes for a large-format home improvement retailer — enabling marketing leadership to make investment decisions based on attributed revenue, not just engagement proxies.
Creative AttributionAd ThemesCreative ScienceSales LiftContent IntelligenceMMM
01
Situation · Solution · Outcomes
Situation
→Creative decisions based on engagement proxies — marketing teams optimized ad creative based on CTR, view-through rate, and brand recall — metrics that correlated poorly with actual sales outcomes
→No link between themes and revenue — despite significant investment in seasonal, project-based, and brand campaigns, there was no methodology to attribute revenue outcomes to specific creative strategies
→MMM inputs lacked creative dimension — the existing marketing mix model treated all impressions as equivalent regardless of creative quality, missing a significant source of performance variance
Solution
→Ad theme taxonomy — developed a structured classification system organizing all ad creative by campaign theme, messaging strategy, product category, and visual attribute
→Creative attribution model — built an ML model that connects theme-tagged impressions to downstream conversion events, attributing sales credit to specific creative strategies beyond channel-level MMM
→Creative science dashboard — delivered a visualization platform enabling the creative strategy team to explore theme performance, identify winning patterns, and prioritize production investment
Outcomes Delivered
→Top-performing creative themes identified — DIY project tutorials consistently outperformed seasonal promotional themes on attributed ROAS by 31%
→MMM inputs enriched with creative dimension — theme-level impressions now feed the marketing mix model, improving R² and channel attribution accuracy
→Creative production investment reallocated — budget shifted toward high-ROAS themes, improving overall media efficiency without increasing total spend
02
Before & After
Before — Engagement-Proxy Creative Optimization
CTR as primary success metric — creative ranked by click and view rates regardless of downstream sales impact
No theme-level attribution — all impressions treated as equivalent in measurement models
Seasonal bias in production — budget allocated based on calendar intuition rather than attributed performance
Creative and media teams siloed — no shared data connecting creative decisions to media measurement outcomes
MMM blind to creative variation — model could not explain variance driven by creative quality vs. spend changes
After — Revenue-Attributed Creative Science
Attributed ROAS by theme — every creative strategy ranked by downstream sales contribution, not engagement proxies
Theme taxonomy in production workflow — all creative tagged at briefing stage, enabling consistent measurement
MMM enriched with creative signals — theme-level impression data improves model fit and attribution accuracy
Unified creative + media decision loop — creative, media, and analytics teams share a single performance view
Production investment guided by data — theme-level ROAS directly informs content production budget allocation
03
Solution Architecture
End-to-End Data Flow
Creative Assets
Ad Themes — Campaign type taxonomy
Visual Attributes — Format, style, imagery
Copy Signals — Message & CTA patterns
Tagging Layer
Auto-Classification — ML-based theme tagging
Manual QA — Human review queue
Version Control — Asset-level audit trail
Attribution Model
Impression Matching — Theme to exposure join
Conversion Attribution — Sales credit by theme
Incrementality — Theme lift estimation
Outputs
Theme ROAS — Revenue per theme
Creative Ranking — Performance index
MMM Inputs — Enriched media signals
Creative Assets → Tagging Layer → Attribution Model → Outputs
04
Platform Capabilities
Theme Taxonomy
Structured classification system organizing all ad creative by campaign theme, message strategy, and visual attribute
Auto-Tagging ML
Automated creative classification model that tags new assets at upload with theme and attribute labels
Attribution Engine
Connects theme-tagged impressions to downstream conversion events with fractional sales credit by theme
Creative Science Dashboard
Self-serve visualization enabling the strategy team to explore theme ROAS, identify winning patterns, and guide production investment
05
Results & Impact
31%
Higher attributed ROAS for top-performing DIY project themes vs. seasonal promotional creative
100%
Ad inventory theme-tagged — all impressions categorized before entering measurement models
R²+
MMM model fit improved after creative dimension added as an explanatory variable
$3.4M
Estimated annual media efficiency gain from reallocating production budget to high-ROAS themes
Top-performing creative themes identified by attributed ROAS — production investment reallocated to high-performing strategies
MMM inputs enriched with creative dimension — theme-level signals improve model accuracy and channel attribution
Creative strategy and media planning teams now operate from a shared performance dataset for the first time
Auto-tagging pipeline ensures all new creative assets are classified at upload — no retroactive taxonomy effort required
Creative science dashboard enables self-serve exploration of theme performance across campaigns, formats, and seasons
Next Steps
DataInc.ai is extending the creative science framework to include video creative analysis and integrating theme performance signals into the automated media buying workflow.
01Video Creative Analysis — Extend theme attribution to scene-level video creative attributes
02Real-Time Creative Scoring — Score new creative assets against ROAS predictions before campaign launch
03Production Workflow Integration — Connect theme ROAS signals directly to the creative brief template
04Cross-Channel Creative Attribution — Extend the model to attribute theme performance across search, social, and CTV simultaneously
About DataInc.ai
DataInc.ai is the marketing data reliability platform built for enterprise teams with $5M+ in annual media spend. We monitor measurement pipelines across connectors, mapping, taxonomy, observability, and alerting — eliminating data risk before it impacts decisions.
Proprietary & Confidential · Retail Practice · 2025