Answers the console can't give
See how campaign types work together, not just how each one performs alone.
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Amazon Marketing Cloud
Amazon Marketing Cloud, set up and put to work.
We set up your AMC instance, write and schedule the queries, and land the results in your own warehouse next to your Amazon Ads and Selling Partner data. Path to conversion, new-to-brand and audience overlap then show up in the dashboards your team already uses.
What you get
Clean room access that turns into answers.
Uploads that actually match
Customer lists prepared to Amazon's spec, so match rates aren't lost to formatting.
Know before you build
We size your audiences against AMC's aggregation thresholds before any query work starts.
Analysis your team can continue
Documented queries your analysts can adapt without starting over.
The problem
Access granted, value unrealized
Plenty of teams have clean room access and almost nothing to show for it. The reasons are consistent: first-party data was never prepared for matching, so hash formats and email normalization silently destroy match rates. Aggregation thresholds return empty results and the query looks broken rather than blocked. And the SQL dialect is unfamiliar enough that analysis stops after the first template. The access is not the hard part.
Before and after
What changes.
Access only
- Access granted, little to show for it
- Hash formats quietly destroy match rates
- Aggregation thresholds return empty results
- Analysis stops after the first template
Put to work
- Match rates measured against a known baseline
- Queries that return results, not blanks
- Insights refresh on schedule
- Audience findings turned into DSP campaigns
What we implement
What’s included.
- AMC instance setup for each advertiser and region
- Customer list uploads hashed to Amazon's spec (email, phone and address), with a match-rate baseline
- A query library for path to conversion, new-to-brand and audience overlap
- Scheduled query workflows, so recurring analysis runs without an analyst rerunning SQL
- Results landed in your warehouse next to your Amazon Ads API and SP-API data
- Audience activation from AMC back to Amazon DSP
- Threshold-aware reporting that explains a blocked result instead of showing an empty one
How we work
How we run it.
Step 1
Audit first-party data quality and estimate realistic match rates before promising outcomes
Step 2
Normalize and hash identifiers, then validate match rates against a known holdout
Step 3
Build the two or three questions with the clearest commercial value first
Step 4
Automate the recurring queries and pipe results into the warehouse
Typical stack
What it runs on.
- Amazon Marketing Cloud
- Amazon Ads API
- Amazon DSP
- Snowflake / BigQuery
- dbt
- SQL
FAQ
Common questions.
What can a clean room tell us that platform reporting cannot?
Cross-touchpoint questions the platform UI will not answer: true new-to-brand rates, overlap and incremental reach between campaign types, path-to-purchase sequences, and how ad exposure relates to repeat purchase in your own customer data. It is the only privacy-safe way to join your customer records to platform-side exposure data.
Do we need a minimum data volume for this to work?
Yes, and it is worth checking before you invest. Clean rooms enforce aggregation thresholds, so small audiences return nothing at all. As a rough guide, meaningful analysis needs tens of thousands of matched records. We size this in the audit and will tell you if you are below the useful floor.
Is our customer data exposed to the platform?
No. You upload hashed identifiers, the join happens inside the clean room, and only aggregated results come out. Neither party can read the other's raw rows. That is the entire design premise, and it is why aggregation thresholds exist.
How is this different from a CDP?
A CDP unifies identity inside your own estate for activation and personalization. A clean room is a controlled environment for joining your data to someone else's for measurement. They are complementary, and a well-modeled CDP or warehouse makes clean room match rates substantially better.
Check your clean room readiness
Tell us what first-party data you hold and which clean rooms you have access to, and we will assess match potential before any build.