What are AMC query templates?

AMC query templates are ready-made Amazon Marketing Cloud reports maintained by DataDoe. They answer common advertising questions, such as which ASINs win new-to-brand customers or which search terms start a purchase journey, without writing SQL. They are adapted from Amazon's Instructional Query Library and reviewed by DataDoe.

• Run a template as it is: your AI agent calls amc_query_start with a templateId (REST: POST /amc/query-executions).
• Schedule it: create a workflow with a templateId and a weekly or daily schedule (amc_workflows_create, REST: POST /amc/workflows).
• Adapt it: read the template SQL (amc_query_template_get, REST: GET /amc/query-templates/:templateId), edit it (for example to filter campaigns or ASINs), and run the edited SQL as your own query.

Templates have no parameters. The time window of an on-demand run, or the schedule of a workflow, decides which dates the report covers. Templates aggregate the whole account, for example by ASIN, keyword, or campaign.

Templates are free. Retrieving their results costs the same as any other AMC result; see Amazon Marketing Cloud.

Which templates need Amazon paid features?

Most templates use the free datasets every AMC instance has. Three templates need Amazon Insights, an Amazon paid feature that adds all purchases of your brand on Amazon, not only ad-attributed ones.

To use them, subscribe to Amazon Insights for the instance in the AMC UI under Paid features. DataDoe does not subscribe on your behalf. Amazon has made its 1P paid features free to query through 31 Dec 2026, but the subscription is still required, and Amazon sets the pricing after that date.

When your agent checks a template with your Seller or Vendor (sellerOrVendorId), the template shows availability: AVAILABLE, or MISSING_DATA_SOURCES with the missing data sources and paid features. Running an unavailable template fails with AMC_TEMPLATE_DATA_SOURCES_UNAVAILABLE before anything runs in Amazon, so nothing is charged.

Which templates are available?

Ad-attributed results use Amazon's 14-day attribution window: run reports at least 14 days after the end of the period to capture all conversions. AMC removes rows with too few customers to protect privacy, so small accounts or short periods can return fewer rows or an empty result.

New-to-brand customers and purchases by ASIN (ntb-by-asin)

Question: Which ASINs win new-to-brand customers, and what share of ad-attributed purchases and sales comes from customers new to the brand?

How to read it: One row per purchased ASIN (promoted and brand halo). A high ntb_purchases_pct means the ASIN mostly sells to customers new to your brand, a good candidate for acquisition campaigns. A low share means repeat buyers dominate: use it for retention. Customers count as new-to-brand if they had not bought from your brand in the previous 12 months.

Recommended window: previous month. Paid feature: none.

New-to-brand gateway ASINs (ntb-gateway-asins)

Question: Which promoted ASINs bring in the most new-to-brand customers, and which are most likely to be a customer's first purchase from the brand?

How to read it: gateway_asin_rank 1 is the ASIN that acquired the most new customers. ASINs with an ntb_users_pct well above your average are strong entry products; consider featuring them in acquisition campaigns. ASINs well below it mostly serve repeat customers.

Recommended window: previous month. Paid feature: none.

Promoted vs brand halo sales by keyword and search term (keyword-search-term-halo)

Question: Which keywords and customer search terms drive sales of the promoted ASINs, and which mostly drive sales of other ASINs of your brand (brand halo)?

How to read it: A high brand_halo_sales_pct means shoppers who searched that term often bought a different ASIN of your brand than the advertised one; consider advertising that ASIN directly. Search terms with strong promoted sales are candidates for exact-match keywords. Covers keyword targeting only (broad, phrase, and exact).

Recommended window: previous month. Paid feature: none.

Sponsored Products, Brands and Display overlap (ad-product-overlap)

Question: Do customers reached by more than one sponsored ads product purchase at a higher rate than customers reached by only one?

How to read it: Each row is an exposure group, the set of ad products that reached a customer. Compare purchase_rate_pct of combined groups with single-product groups. A clearly higher rate supports running the ad products together; this shows correlation, not proven incrementality.

Recommended window: previous month. Paid feature: none.

Time to conversion (time-to-conversion)

Question: How long after the attributed ad click or impression do customers purchase, per ad product?

How to read it: Purchases are grouped in time buckets from under a minute to over seven days after the last ad touch. A large share in the first buckets means short consideration, so bid and budget changes show quickly. A long tail means a longer consideration cycle: judge campaigns on at least 14 days and consider retargeting.

Recommended window: previous month. Paid feature: none.

Path to conversion by campaign (path-to-conversion)

Question: Which sequences of sponsored ads campaigns do customers see before they purchase, and which paths convert best?

How to read it: Each row is a path of campaigns in the order they first reached the customer. For customers who purchased, only campaigns, impressions, and spend up to their last ad-attributed purchase count. Paths with several campaigns and a higher user_purchase_rate_pct than single-campaign paths show campaigns that work together. Rare paths are removed by AMC privacy thresholds, so the report favors the most common journeys.

Recommended window: previous month. Paid feature: none.

First vs attributed search term (first-vs-last-search-term)

Question: Which upper-funnel search terms start the journey of customers who later purchase through a different search term?

How to read it: Each row pairs the first search term that showed the customer an ad of a campaign (looking back up to 30 days) with the search term the purchase was attributed to. Rows where same_search_term is false show assisting terms: generic first terms that lead to specific or branded terms deserve budget even if their own last-touch results look weak.

Recommended window: previous month. Paid feature: none.

Cross-sell: next ASIN purchased (cross-sell-next-purchase)

Question: After customers buy one ASIN through ads, which ASIN of your brand do they buy next, and how many days later?

How to read it: Top-ranked pairs are your strongest product affinities: bundle them, cross-promote the follow-up ASIN, or retarget buyers of the lead ASIN around avg_days_between_purchases after their first purchase. Only ad-attributed purchases count, so the numbers are a lower bound.

Recommended window: previous month. Paid feature: none.

Organic vs ad-touched new-to-brand customers by ASIN (organic-vs-ad-touched-ntb-by-asin)

Question: For each ASIN, how many new-to-brand customers and sales came from customers exposed to ads versus customers who bought without an ad exposure?

How to read it: Each ASIN has an ad-exposed row (an ad reached the customer in the 28 days before the purchase) and a non-ad-exposed row. A higher new-to-brand share among ad-exposed customers suggests ads help acquire new customers for that ASIN; a large non-ad-exposed share shows how much the ASIN sells organically.

Recommended window: previous month. Paid feature: Amazon Insights.

Repeat purchase and customer value cohorts (repeat-purchase-ltv-cohorts)

Question: How much are new-to-brand and existing customers worth over time, how many come back, and do ad-exposed customers spend more?

How to read it: Customers are split by type (new-to-brand or existing), purchase frequency (one-off or repeat), and ad exposure. sales_per_customer of new-to-brand repeat customers is the value a retained new customer brings in the period; compare it with your cost to acquire a customer. The share of repeat customers among new-to-brand customers is your repeat rate.

Recommended window: a custom period of 6 to 12 months, run on demand. Paid feature: Amazon Insights.

Time to second purchase (time-to-second-purchase)

Question: How long do customers wait between their first and second purchase from your brand, and does it differ for new-to-brand customers?

How to read it: The bucket with the most customers is your typical repurchase cycle: time replenishment reminders, Subscribe & Save offers, and retargeting just before it. Many customers in the first day usually means split orders rather than true repurchases.

Recommended window: a custom period of 6 to 12 months, run on demand. Paid feature: Amazon Insights.