Emotional Intelligence for AdTech
Integrating Sliders.AI into Alphabet Inc. (Google)—the world’s most profitable AdTech platform—could generate $2.5B–$6B in cumulative net gain over five years by upgrading both the ad experience layer (frontend) and the data-intelligence stack (backend).
Frontend: Ad Personalization & Consumer Experience
1. Slider-Based Ad Preference Controls
Users slide to express “personalization vs. privacy,” “fun vs. functional,” or “brand vs. local.”
Outcome: Higher consent, more nuanced targeting
Impact: +5–10% lift in ad engagement and conversion
2. YouTube & Google Play Personalization
Sliders shape what users want to watch, buy, or skip more intuitively
Outcome: Higher click-throughs, longer session time
Impact: +2–4% lift in UX-driven ad revenue
3. Search Refinement Interface
Users control ad experiences via sliders (e.g., “latest vs. evergreen”)
Impact: Increased ad relevance → higher auction bids
Estimated 5-Year Frontend Gain: $1.5B–$3B
Backend: Ad Intelligence, Data, & AI Alignment
1. Emotion-Driven Ad Analytics
Sliders generate structured signal on tone, timing, and sentiment
Use Case: Creative matching, dynamic A/B testing at scale
2. Advertiser Tools: Audience Modeling
Brands use sliders to target nuanced segments (“price-sensitive vs. loyal,” “experimental vs. risk-averse”)
Outcome: Higher ROI per impression
3. AI & LLM Training
Sliders fuel more interpretable, bias-aware fine-tuning of Bard and SGE
Impact: More explainable, human-aligned AI
Estimated 5-Year Backend Gain: $1B–$3B
5-Year Total Opportunity
| Segment | Value Range |
|---|---|
| Frontend UX & Ads | $1.5B–$3B |
| Backend Data & AI | $1B–$3B |
| Total Impact | $2.5B–$6B |
Strategic Edge for Alphabet
- User-Controlled Targeting: Personalized without being creepy
- AI Signal Layer: Structured emotional data → smarter LLMs
- Ad Relevance Moat: Richer psychographics = better outcomes for brands & platforms