Measure Off-Amazon Conversions in AMC

Yes, Amazon Marketing Cloud (AMC) can measure DTC web, app, store, and offline conversions once Events Manager receives them through Amazon Ad Tag (AAT), Conversions API (CAPI), or a Mobile Measurement Partner (MMP), the event is defined in the Amazon demand-side platform (DSP), and it is associated with a DSP order. The practical difference from Amazon conversions is the setup and taxonomy: off-Amazon subtypes arrive as numeric codes, purchase sales and non-purchase value mean different things, and the complete history starts on October 20, 2023. I handed the question to our agent through the Amazon Ads MCP, grounded by Amazon Agent Atlas, and asked it to prove each gate before running AMC SQL.

That answers the Slack question: "We're running DSP ads to our DTC site. Can we measure those conversions inside AMC the same way we measure Amazon conversions?" A plain ChatGPT or Claude chat hits three walls. It has no access to your data, so it cannot inspect the advertiser's Events Manager or AMC instance. It has no way to take action, so a human must copy, validate, and run its SQL. It has generic knowledge, not Amazon's, so it can miss the DSP-order gate, numeric subtype map, or coverage date. That becomes disconnected, generic, manual work that ships silent mistakes. The MCP supplies account access, Atlas supplies Amazon's current rules, and Skills make the checks repeatable.

Events Manager data reaches AMC only after the event is linked to a DSP order

Sending an event to Amazon DSP is necessary but not sufficient. The Introduction to Events Manager instructional query names three prerequisites: set up AAT, CAPI, or MMP; define the event in Amazon DSP; and associate that event with an Amazon DSP order. If the order association is missing, the data does not flow into AMC. The empty result can look like zero customer activity even though the failure is configuration.

The agent therefore runs a preflight before SQL. It checks the ingestion source, event definition, order association, AMC instance, and requested start date, then returns a pass or a named setup failure. That sequence also keeps the claim precise: Events Manager covers off-Amazon web, offline, and app events used for attribution, reporting, optimization, and targeting, but the event must pass the DSP setup gate first.

All Events Manager signals are available in AMC whether ad-exposed or not, and the playbook says the paid conversions_all subscription is not required to query non-ad-exposed Events Manager signals. That makes non-ad-exposed analysis possible without making it causal proof. It is a comparison and audience-discovery input, not evidence that advertising created an outcome in a user who was never exposed.

Purchase sales and non-purchase conversion value are different measurements

off_amazon_product_sales is monetary sales from off-Amazon purchases. off_amazon_conversion_value is an advertiser-defined, unitless value for non-purchase events such as a page view, app install, lead, or form submission. Do not add the second field to revenue or use it in return on ad spend (ROAS) unless the advertiser has explicitly documented a monetary scoring convention outside the schema.

Events Manager also represents off-Amazon conversion_event_subtype values as numeric codes. The retrieved mapping is:

The event formerly labeled Product purchased is now Off-Amazon purchase. The Skill keeps the mapping versioned and leaves an unknown code visible instead of coercing it to a familiar label. That is safer than silently converting an unrecognized future subtype into revenue.

The canonical Total Impact query joins campaign delivery to conversion outcomes

Amazon's canonical Total Impact Analysis query from Introduction to Events Manager joins campaign cost, impressions, and unique reach from dsp_impressions to Amazon and off-Amazon outcomes from amazon_attributed_events_by_traffic_time. It keeps purchase sales, non-purchase value, combined sales, and conversion counts separate, then calculates Amazon and off-Amazon ROAS from the corresponding monetary sales fields. Set the workflow's date range in the AMC query editor to October 20, 2023 or later before running it.

-- Instructional Query: How to query Events Manager Signals - Total Impact Analysis --
-- AD PRODUCTS: Amazon DSP
/*
 ------- Customization Instructions -------
 1) Set the "Date range" in the Query Editor to define the time range.
 1a) It is recommended to query events after 10/20/2023, as events before this date may be missing dimensions and metrics.
 */
-- Gather campaign cost and impression data
WITH traffic AS (
  SELECT
    campaign_id_string,
    campaign,
    SUM(impressions) AS impressions,
    SUM(total_cost / 100000) AS total_cost,
    COUNT(DISTINCT user_id) AS unique_reach
  FROM
    dsp_impressions
  WHERE
    user_id IS NOT NULL
  GROUP BY
    1,
    2
),
-- Gather Amazon and off-Amazon (Events Manager events) conversion data
conversions AS (
  SELECT
    campaign_id_string,
    conversion_event_source_name,
    conversion_event_name,
    conversion_event_category,
    CASE
      conversion_event_subtype
      WHEN 53 THEN 'Add to shopping cart'
      WHEN 7 THEN 'Application'
      WHEN 140 THEN 'Checkout'
      WHEN 136 THEN 'Contact'
      WHEN 141 THEN 'Lead'
      WHEN 54 THEN 'Off-Amazon purchase'
      WHEN 133 THEN 'Other'
      WHEN 134 THEN 'Page View'
      WHEN 135 THEN 'Search'
      WHEN 21 THEN 'Sign-up'
      WHEN 5 THEN 'Subscribe'
      ELSE conversion_event_subtype
    END amazon_conversion_event,
    SUM(off_amazon_conversion_value) AS off_amazon_conversion_value,
    SUM(off_amazon_product_sales) AS off_amazon_product_sales,
    SUM(conversions) AS conversions,
    SUM(total_product_sales) AS total_product_sales,
    SUM(total_purchases) AS total_purchases,
    SUM(combined_sales) AS combined_sales
  FROM
    amazon_attributed_events_by_traffic_time
  GROUP BY
    1,
    2,
    3,
    4,
    5
) -- Join cost and impressions with conversions
SELECT
  t.campaign,
  c.conversion_event_category,
  c.conversion_event_source_name,
  c.conversion_event_name,
  c.amazon_conversion_event,
  SUM(t.impressions) AS impressions,
  SUM(t.total_cost) AS total_cost,
  SUM(t.unique_reach) AS unique_reach,
  SUM(COALESCE(c.off_amazon_conversion_value, 0)) AS off_amazon_conversion_value,
  SUM(COALESCE(c.off_amazon_product_sales, 0)) AS off_amazon_product_sales,
  SUM(COALESCE(c.conversions, 0)) AS conversions,
  SUM(COALESCE(c.total_product_sales, 0)) AS total_product_sales,
  SUM(COALESCE(c.total_purchases, 0)) AS total_purchases,
  SUM(COALESCE(c.combined_sales, 0)) AS combined_sales,
  CASE
    WHEN SUM(t.total_cost) > 0 THEN SUM(COALESCE(c.total_product_sales, 0)) / SUM(t.total_cost)
    ELSE 0
  END AS amazon_roas,
  CASE
    WHEN SUM(t.total_cost) > 0 THEN SUM(COALESCE(c.off_amazon_product_sales, 0)) / SUM(t.total_cost)
    ELSE 0
  END AS off_amazon_roas
FROM
  traffic t
  LEFT JOIN conversions c ON t.campaign_id_string = c.campaign_id_string
GROUP BY
  1,
  2,
  3,
  4,
  5

The query stays faithful to the retrieved instructional query, including Amazon's total_cost / 100000 normalization and campaign-ID join. Inspect the returned source names and event definitions before operationalizing it; unknown subtype codes stay visible through the ELSE branch instead of being silently relabeled.

combined_sales is Amazon total_product_sales plus off_amazon_product_sales; it does not include the unitless value assigned to non-purchase conversions. The query reports Amazon and off-Amazon ROAS separately, so leads and page views never enter either monetary numerator. A combined-sales return can be derived downstream only after the output grain and cost allocation have been reviewed.

Events Manager history is complete only from October 20, 2023 onward

Treat October 20, 2023 as the completeness boundary for the named Events Manager dimensions and metrics in amazon_attributed_events_by_* and conversions* tables. Earlier periods can be missing those fields. A range before the boundary can also omit 30-day ad-unexposed events from conversions and conversions_with_relevance, so a lower historical count is not safely interpreted as lower customer activity.

The Off-Amazon Conversions Playbook carries the result beyond reporting into campaign measurement, segmentation, and separately reviewed audience creation. Examples include users who added to cart off Amazon but did not purchase, converters who were not ad-exposed, and non-ad-exposed purchasers of product A who may be candidates for product B. Those are useful hypotheses. They do not prove incrementality, and measurement SQL does not activate an audience by itself.

AMC only returns aggregated, pseudonymized outputs that meet its aggregation thresholds. The agent keeps the output at campaign and event grain, avoids SELECT *, rejects unsafe start dates, and reports suppressed or unknown results instead of turning them into zeros.

What happens next

After the preflight and subtype checks pass, schedule the total-impact analysis as a recurring Skill. Keep Amazon product sales, DTC purchase sales, and non-purchase conversion value in separate output columns; use combined_sales for the Amazon-plus-DTC product-sales view; and review any unknown subtype before the run reaches a dashboard or optimization rule.

The complete workflow runs through the Amazon Agent Data layer: the Amazon Ads MCP supplies live AMC access, the Selling Partner MCP adds catalog or retail context when the decision needs it, Skills make the checks recurring, and Amazon Agent Atlas grounds the taxonomy, date rule, and setup gates. If a segment is worth activating, hand it to a separate reviewed audience workflow rather than making activation an invisible side effect of measurement.

Events Manager turns DTC outcomes into dependable AMC measurement only when ingestion, DSP association, event taxonomy, and revenue semantics are all correct.

Next, place those captured outcomes inside the full AMC path across DSP and sponsored ads.