If 1,000 customers search "removable liner?" and the widget can't answer, that signal feeds back into the enrichment pipeline. The next enrichment run targets that specific data point. The widget gets smarter from being used. Commerce learns.
The Core Loop
Central isn't a static system. Every customer interaction creates a signal, and every signal improves the system:
- Better enrichment → richer product intelligence profiles
- Better widget answers → more customer engagement
- More engagement → more signals about what matters
- More signals → targeted enrichment of missing data
- Targeted enrichment → even better data
- Cycle repeats → compounding improvement
This is the Data Flywheel. It's the reason Central gets better the more it's used — and the reason a competitor starting from scratch can't replicate the advantage.
Widget Interaction Signals
Every interaction with the Product Intelligence Widget generates intelligence:
- Search queries — What questions are customers asking that the widget can't yet answer?
- FAQ clicks — Which questions are most important to buyers in each category?
- Spec comparisons — Which specifications do customers look at most?
- Smart Negative engagement — Do honest limitations increase or decrease purchase intent?
- AI Advisor queries — What complex questions require natural language answers?
- Drop-off points — Where do customers leave the widget without finding their answer?
Each signal tells the system what to prioritize in the next enrichment run. The data doesn't just grow — it grows in the direction that matters most to buyers.
External Data Sources
The flywheel extends beyond widget interactions. External data sources compound the intelligence:
- Google Search Console — What customers search before landing on the product page
- Google Trends — Trending attributes by category, enabling predictive enrichment
- Marketplace performance data — Which keywords actually index, which listings get rejected
- Review platforms — Fresh review themes that update FAQ answers
- Customer support tickets — Pre-sale questions that reveal information gaps
The Moat
After 12-24 months, the system knows exactly which 15 attributes drive 80% of purchase decisions in each product category. It knows which questions buyers ask in which order. It knows which Smart Negatives increase trust and which cause unnecessary concern. It knows the difference between a specification that drives conversion and one that's just noise.
A competitor starting from scratch cannot replicate this. They don't just need the technology — they need the accumulated interaction data. The data that reveals what matters. The data that took 24 months of real customer interactions to collect.
This is how commerce learns to improve itself. Not through manual optimization. Not through A/B testing individual pages. Through a system-level learning loop that compounds automatically, gets smarter every day, and builds a moat that deepens with every customer interaction.