How do I harvest converting search terms into exact match campaigns on Amazon?

The playbook

Every step calls a Nova tool that reads your live Amazon data, so paste this into Claude, ChatGPT or any assistant connected to Nova's MCP server. Run it every two to four weeks, marketplace by marketplace.

Use Nova to find the search terms I should harvest into exact match campaigns, with a starting bid for each.

Period: the last 30 complete days. If I name other dates, use those.

Scope: Sponsored Products, one marketplace at a time. If I sell in several, start with the one with the most ad spend.

1. Set the bar. Call Nova's query_advertising with groupBy "childAsin" and the metrics spend, sales, orders, acos and breakEvenAcos. Above its break-even ACOS, a product loses money on each ad sale. Say which products have no break-even because their costs are missing.

2. Find the converting queries. Call Nova's query_search_terms with groupBy "searchTerm", adProducts ["sponsored_products"], targetingDetails ["phrase", "broad", "close-match", "loose-match", "complements", "substitutes"], the metrics spend, clicks, orders, sales, acos and cvr, metricFilters orders above 0, sorted by sales, limit 200. Set aside the rows with the search term "*", which are product page placements. A row that looks like an ASIN is a product to add as a product target, not a keyword.

3. List what is already exact. Call Nova's query_advertising with groupBy "keyword", targetingDetails ["exact"], the metric spend, limit 1000, for the same marketplace. Remove from step 2 every query that already has an exact keyword with the same text.

4. Check what is blocked. For the 10 biggest candidates, call Nova's list_negative_targets with q set to the query. A rule counts only if its keywordText matches the query exactly. Flag any candidate that is negated somewhere, because someone chose to block it.

5. Find where each query sold. For the 10 biggest candidates, call Nova's query_search_terms with searchTerms set to that one query and groupBy "adGroup", with spend, orders and sales. It returns the campaigns and ad groups that caught it.

6. Read the margin behind each ad group. For those ad groups, call Nova's query_advertising with adGroupIds set to them, groupBy "childAsin", and the metrics spend, sales and breakEvenAcos. Use the lowest break-even ACOS of the products in the ad group.

7. Set a starting bid. For each candidate, divide its sales by its clicks to get the revenue per click, then multiply by the break-even ACOS from step 6. That is the most a click can cost before an ad sale loses money. Suggest a starting bid below it, and never above it.

8. Sort the candidates. Harvest: at least 2 orders and 10 clicks, ACOS below break-even. Watch: 1 order, or fewer than 10 clicks. Do not harvest: ACOS above break-even, or the query is negated somewhere.

9. Report, in four lists.
   - Harvest: query, orders, clicks, ACOS, conversion rate, the ad group that caught it, and the starting bid
   - Product targets: ASIN rows with orders, and where they sold
   - Watch: candidates to read again next run
   - Do not harvest: with the reason
   Then give the Harvest list ready to paste, and for each query the source ad group where a negative exact will stop it competing with the new exact keyword.

Rules: you cannot change anything on my account, so I create the campaigns, bids and negatives in Amazon Ads. A query carries no product margin of its own, so say the bid uses the break-even of the products in the ad group. Never add sales across ad types. Say which figures are missing and why, and relay every notice Nova returns (P&L rules, COGS gaps, currency, ad history).

Raw markdown