What is AMC (Amazon Marketing Cloud)?
3 min

What is AMC (Amazon Marketing Cloud)?

Gloria Steiner, August 31, 2022

What is AMC?

When was the last time you increased budget on a campaign without basing it off of a metric or a piece of data to support that decision? Or create a day-parting strategy without analyzing data to view what time of day is best to decrease / increase bids? The answer should be: never.

Data is critical to make decisions, especially when you have a budget to work off of that should be spent in the most efficient and smartest way possible. This gets difficult when a brand is trying to analyze the value of spend put into an upper funnel (brand awareness) campaign that reaches millions of views on various platforms and unsure whether it brought back any consumers to purchase through another campaign that is closer to the purchase. With the Amazon Marketing Cloud, a brand is now able to see this in full transparency.

To start, the Amazon Marketing Cloud is a data clean room. What is a clean room?

Think of a room with people inside and the only way you can get information from who they are or what they have done is to anonymously submit a question through the door and poll the entire room. If enough people answer the poll, you will be able to get the results, but only at an aggregated level. This means, you won't be able to get specific information on a user level, only on the group level if enough people have done similar things (example: watched a video ad on Prime at 3PM) or have similar attributes (example: postal code of where they live).

What kind of people are in the Amazon Marketing Cloud clean room?

People who have been exposed to an Amazon Advertisement run through the Amazon DSP, Sponsored Products and/or Sponsored Display (Sponsored Brands coming next). But, there is an opportunity to add more people to the room - people who are very close to your brand already. A brand is able to add people who have been to their website and see if those people have also been exposed to Amazon Advertising or purchased on Amazon.com.

Why is a clean room important? Measurement and Privacy are the key factors.


Using the Amazon Marketing Cloud is the only way you can get an idea of who is in that room and what actions those people take without them revealing any personally identifying information (PII). An Amazon Advertiser can now safely acquire information about how ads are performing and use that data to evaluate campaigns, optimize ad spend and, very soon, enhance custom audience creation with customized dataset creation.

Clean rooms also meet the many data security compliance laws and regulations required by industry, state, and federal data regulations (think of CPRA and GDPR) because in this secure environment the data is available but not tied to the identifying information that’s protected by these regulations.


An Advertiser can leverage a data clean room for user-level analysis across a range of metrics such as Customer Acquisition Cost (CAC) or Customer Lifetime Value (CLV). This allows for a brand to know how costly it is to acquire a new customer on Amazon (spend divided by number of new-to-brand customers), the lower that value, the cheaper it was for them to get a new customer to the brand and the more effective the brand is being with their audience targeting. Combining a brand’s CAC with knowing how much revenue a customer brings the brand over their lifetime (average order value multiplied by average purchases over the time analyzed) the brand can know at what cost they are able to acquire a new customer and what revenue that customer will bring in the future. Dividing a brand’s LTV by their CAC can signal profitability. For example, if a brand’s LTV is $80 and CAC is $30, the LTV / CAC ratio is 2.7, meaning it is profitable. Anything below 1 means the brand is losing revenue on every customer.

A brand is also able to measure the effectiveness of advertisements, especially at the brand awareness or brand building stage where it has not always been clear if these are effective. Without multi-touch attribution, it is typically been the last-touch campaign that receives the full credit for the conversion, however, with a data clean room, a brand is now able to see the full customer journey and assign a decided weighted credit to any touchpoint in that journey.

it gives transparency into the actual impact of these tactics and if a brand should keep running specific campaigns or not as you can evaluate the true cross advertising unit impact of all your ad spend running, Sponsored and Amazon DSP.

How can brands know who is in their clean room?

As mentioned previously, a brand needs to poll the room and need enough people in the room to answer the poll in order to get any type of information back. When creating the poll, you need to ask questions, or queries, in SQL (Structured Querying Language). Once the query is structured properly and accepted by the Amazon Marketing Cloud, the brand can download the data and create a visualization to tell a story with aggregated user traffic data which spans across the brand’s advertising campaigns and website.

Perpetua has been working with the Amazon Marketing Cloud since early 2020 and have been building many different questions to add to the poll. Without the right questions, and properly structured with SQL, a brand will not be able to extract insight (or reliable insight) from the people within the clean room. The Perpetua Business Intelligence Team is dedicated to working on impactful questions that will give transparency into the advertising efforts of Perpetua’s customers.

A dashboard is created with valuable visualizations to give insight into what the people in the brand’s clean room have done, what value they bring to the brand and how the brand can strategize to have more efficient campaigns/grow their tactics in a strategic manner.

Interested in knowing who is in your Amazon Marketing Cloud clean room? Email us at hello@perpetua.io to find out.

To get started or learn more about how Perpetua can help you scale your Amazon Advertising business