Introducing Max: AI-powered revenue analytics. Read the announcement →
SuggestAPI Integration
SuggestAPI is the discovery layer. Convertmax is the revenue intelligence layer. Together they show which demand you should invest in.
Join SuggestAPI searches, recommendations, and agent commerce handoffs to Convertmax visitors, campaigns, orders, and LTV—so internal search and AI discovery stop being a dark funnel.
Search queries and agent requests are first-party declarations of intent. Convertmax measures what that intent is worth.
What the integration does
Discovery events in the Revenue Graph, agentic attribution on conversions, and Max questions against search-to-revenue outcomes.
Keep campaign → visitor → SuggestAPI query → product → order → revenue in one journey instead of stopping analytics at search → click.
Aggregate queries against source, campaign, product, customer, and revenue so marketing can see which intent actually converts.
Attach what agents searched and recommended to Convertmax agentic source, protocol, and channel on the conversion.
Discovery events sit next to acquisition, identity, orders, and LTV—not in a separate search dashboard.
Once search and agent events land in Convertmax, Max can answer which queries, campaigns, and agents created revenue.
Send conversion rate, revenue per search, margin, and LTV back into merchandising and ranking instead of optimizing on CTR alone.
Built for revenue-focused attribution
SuggestAPI answers what customers and agents are trying to find. Convertmax answers what creates customers and revenue. The join is which demand you should fund.
Keep the catalog and search you already run. Add SuggestAPI for shoppers and agents. Let Convertmax show which of those journeys pay—and feed revenue outcomes back into ranking when you are ready.
How it works
Use SuggestAPI for product search, autocomplete, recommendations, and agent discovery in front of the catalog you already have.
Stream searches, recommendations, and agent handoffs so they land on the same first-party visitor and customer records as your other sources.
Convertmax attributes those events through the Revenue Graph—acquisition, identity, conversion, and repeat revenue included.
Use Max for demand questions, then take revenue outcomes back into merchandising and ranking in SuggestAPI.
Technical specifics
Agents and implementers cite object-level mappings. This is what Convertmax reads, writes, and attributes—not a marketing overview.
| SuggestAPI | Convertmax | Notes |
|---|---|---|
| Product search query | Discovery intent | First-party search terms join the visitor session and attributed revenue path. |
| Recommendation / compare | Product | Returned and recommended SKUs can be compared with what customers actually buy. |
| Agent discovery | Agentic source / protocol / channel | ChatGPT, Gemini, and shopping-agent evidence rides on the human conversion. |
| Commerce handoff | Session → order → revenue | Merchant checkout stays in Convertmax; SuggestAPI does not replace the storefront. |
Use case
A shopper arrives from an ad, searches “waterproof hiking boots” in SuggestAPI, clicks a product, and checks out. Convertmax keeps campaign, visitor, query, product, and order on one path—so the query is revenue, ROAS, and LTV, not 382 searches and a 17% CTR.
Questions about setup, identity stitching, or rolling this out across your stack? Email help@convertmax.io or book time with the team.