GM: AI-Personalization Drove Triple-Digit HVB Lift for Lyriq and Sierra | MMA / Marketing + Media Alliance

GM: AI-Personalization Drove Triple-Digit HVB Lift for Lyriq and Sierra

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Key Stat: 
+139%
Key Stat Supporting Text: 
Cadillac Lyriq HVB Lift
Key Stat Footnote: 
Conversions per person exposed
Key Stat: 
+228%
Key Stat Supporting Text: 
GMC Sierra HVB Lift
Key Stat Footnote: 
Conversions per person exposed
Key Stat: 
144
Key Stat Supporting Text: 
Creative Versions
Key Stat Footnote: 
36 versions × 4 sizes
Key Stat: 
6 weeks
Key Stat Supporting Text: 
Person-Level RCT
Key Stat Footnote: 
65/35 earn-learn allocation
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The Hypothesis

Aligning creative elements (image, headline, offer, CTA) to audience motivations via AI—then adapting mid-flight—will substantially increase HVBs vs randomized rotation and sustain/improve over time.

This application of AI/ML works by identifying cohorts and optimizing pre-approved elements and creative to each. MMA's approach uses two ML techniques combined with unsupervised learning:

  • One-Hot Encoding
  • K-Modes Clustering
Experiment Design

RCT Type: Person-level with 65/35 earn-learn

Creative: 36 versions × 4 sizes = 144 total

Flight: 6 weeks with GenAI creative refresh

KPIs: HVBs, Vehicle Details Page Views

144
Total Versions
× 1,852,200
Audience variations
✓ DMA ✓ Time ✓ Day of Week ✓ Device OS ✓ Connection Type ✓ Segment ✓ Other Data Signals
= 266,716,800
opportunities to find value in the interactions between message & audience

 

GM: Ad variations

The Impact

Lyriq achieved +139% HVB and +138% VDP lift; Sierra achieved +228% HVB and +229% VDP lift (conversions per person). Lift increased as the AI learned; no creative wear-out observed.

Key Learnings
  • Message-to-mindset alignment mattered: luxury-focused creative beat performance-focused for Cadillac; mid-flight shift added late lift
  • Changing ad copy mid-campaign revealed a new high-performing audience segment that contributed a 19% incremental KPI lift. GM and MMA also introduced a new ‘towing’-themed creative mid-campaign, based on what it had learned so far.
  • GenAI analysis suggested storyboard changes (e.g., comfort/safety emphasis for retired empty nesters) while preserving performance angles for affluent professionals with families
  • GM has industrialized an ~8-week test-to-deployment motion in always-on creative ops