AI in the platform
- The AI Shelf
- AI title optimization
- AI categorization
- Feed audits
- ChatGPT Feed
- Perplexity Feed
AI resources
P
AI agent
Perplexity's shopping answers favor products it can verify - structured, accurate, current. GoDataFeed keeps your catalog machine-readable, so assistants can find your products, trust them and recommend them.
Agent conversation
Q
Best waterproof trail runners under $140?
1
TrailFlux GTX
2
Ridgeline 2
3
Summit Lite
How answer engines choose
An answer engine stakes its credibility on every recommendation. It favors products with complete attributes, valid identifiers and prices that check out - and quietly skips the rest.
Attributes, categories and identifiers built for parsing, not just for browsing.
Price and availability current on schedule, so recommendations hold up at the click.
GTINs and MPNs validated across the catalog - the anchors assistants match products on.
The same data behind your channels serves every answer engine that emerges.
Get agent-ready
01
Attributes, identifiers and categories built out across the full catalog.
02
Data is checked against spec before it publishes anywhere.
03
Scheduled syncs keep what assistants read aligned with your store.
1
governed catalog behind every answer engine recommending products.
40+
channels and surfaces one connection can feed.
0
chance of being cited from data an assistant cannot parse.
Questions, answered
How does Perplexity find products?
Through structured, machine-readable product data it can parse and verify - the same discipline your shopping channels already reward.
Do I need a Perplexity-specific feed?
No. One engineered catalog serves the shopping ecosystem AI assistants draw from.
What makes a product citable?
Complete attributes, valid identifiers and accuracy that holds up when the assistant checks - structure first, then trust.
Other AI agents
Light closer. Renders for AI agent type only, which spends its dark beat on the hero.