You’re under-leveraging AMC—here’s how to fix it

Introduction

Welcome to You’re Under-Leveraging AMC — Here’s How to Fix It.

In this session, Sreenath Reddy, Founder and CEO of Intentwise, explains how brands and agencies can unlock the full potential of Amazon Marketing Cloud (AMC).

While AMC has become one of the most powerful analytics tools in the Amazon ecosystem, many advertisers still use only a fraction of its capabilities. This webinar breaks down what AMC actually is, the data it contains, and how brands can start generating insights and audiences that drive measurable performance.

Why Many Brands Are Under-Using Amazon Marketing Cloud

Amazon Marketing Cloud has been widely discussed for several years, yet adoption remains limited.

The most common reason is simple:

Many advertisers don’t fully understand what data exists inside AMC or how to use it.

Amazon continues to release new signals and datasets into AMC, expanding its role beyond advertising optimization. Today, AMC can help brands analyze:

• Advertising performance
• Shopper behavior
• Customer acquisition
• Product engagement
• Long-term customer value

In short, AMC is increasingly becoming the central measurement platform for Amazon advertising and shopper analytics.

Understanding the Amazon Shopper Journey

The Amazon purchase journey is rarely linear.

A typical shopper might follow a path like this:

1. See a DSP display ad
2. Click an ad later
3. Return through Amazon search
4. Click a Sponsored Products ad
5. View the product page
6. Add the product to a cart or wishlist
7. Complete the purchase days later

Traditional reporting tools only capture part of this journey.

Most reporting in Amazon Ads still relies heavily on last-click attribution, which ignores earlier interactions in the purchase path.

This creates several measurement challenges:

• No clear connection between upper-funnel awareness and conversions
• Limited understanding of which touchpoints influence purchases
• No visibility into high-intent actions like add-to-cart or wishlist engagement

This is exactly where Amazon Marketing Cloud becomes valuable.

What Amazon Marketing Cloud Actually Is

At its core, Amazon Marketing Cloud is a collection of datasets that track shopper interactions with your brand.

Each interaction is tied to an anonymous user identifier, allowing advertisers to analyze behavior across multiple touchpoints.

Examples of events captured in AMC include:

Advertising Events

• Ad impressions
• Ad clicks
• Campaign exposure
• Sponsored ads engagement
• DSP engagement

Shopping Events

• Product detail page views
• Add-to-cart actions
• Wishlist or registry interactions
• Purchases

Because every event is tied to a user-level identifier, AMC enables analysis across the entire customer journey.

This is what makes AMC fundamentally different from standard reports in:

• Amazon Ads Console
• Vendor Central
• Seller Central

AMC Is a Privacy-Safe Data Clean Room

Amazon Marketing Cloud operates as a clean room environment, meaning it is designed to protect shopper privacy.

There are several important constraints:

User IDs Are Anonymous

Although data is tied to a user identifier, advertisers can never see or query a specific user.

For example, you cannot search for the behavior of a specific shopper.

Aggregation Thresholds

AMC enforces minimum thresholds for reporting results.

If a query returns too few users, the result will appear blank to protect privacy.

For example:

• A report by ZIP code might hide data for locations with fewer than a certain number of users.
• Audience creation requires at least 2,000 users.

These restrictions are standard for clean-room environments.

Types of Data Available in Amazon Marketing Cloud

AMC contains three major categories of datasets.

1. Advertising Data (Default Dataset)

This dataset is available to advertisers using Sponsored Ads or Amazon DSP.

It includes:

• Ad impressions
• Ad clicks
• Campaign exposure
• Conversion events

This dataset is included by default and is free.

2. Amazon Retail Insights Data

The second category adds organic shopping signals, such as product interactions and browsing activity.

This dataset is typically part of a paid subscription and may include free trial access.

It allows brands to analyze both paid and organic customer behavior together.

3. Advertiser-Uploaded Data

Brands can also upload their own first-party datasets into AMC.

Common examples include:

• Direct-to-consumer (DTC) customer lists
• CRM datasets
• Product segmentation metadata
• Customer attributes

Amazon matches these records to anonymous AMC user IDs, enabling brands to analyze overlap between first-party audiences and Amazon shoppers.

Key Use Cases for Amazon Marketing Cloud

There are two primary ways brands use AMC:

1. Generate Insights

AMC enables advertisers to answer questions that were previously impossible using standard Amazon reports.

Examples include:

• How many new-to-brand customers did we acquire last month?
• Which products drive the most customer acquisition?
• What ad sequences lead to the highest conversion rates?
• What are the most common paths to purchase?

2. Create Advanced Audiences

AMC can also generate custom audiences for targeting.

These audiences can be activated through:

• Amazon DSP
• Sponsored Display
• Sponsored Products (via audience bid adjustments)
• Sponsored Brands

Because these audiences are built from shopper behavior, they often perform significantly better than standard targeting segments.

Example AMC Insight: New-to-Brand Customer Acquisition

One powerful AMC use case is analyzing new-to-brand customers across campaigns and channels.

Instead of viewing new-to-brand metrics only at the campaign level, AMC allows brands to analyze:

• New customers acquired across all campaigns
• Acquisition by product
• Acquisition by campaign type
• Acquisition by touchpoint sequence

In one example shared in the webinar, a brand discovered that 11 products within a portfolio of nearly 2,000 SKUs drove most new-to-brand acquisitions.

As a result, they shifted advertising budget toward those products—even though their ACOS appeared less efficient.

Path-to-Purchase Analysis

AMC also enables multi-touch attribution analysis.

Brands can examine questions like:

• Do customers convert after seeing DSP first and Sponsored Ads later?
• What campaigns generate the first touch vs the last touch?
• Which sequences drive the highest purchase rates?

These insights can significantly influence advertising strategy.

Product Engagement and Drop-Off Analysis

AMC allows brands to analyze customer behavior between product interactions.

For example:

• Detail page views
• Add-to-cart events
• Wishlist or registry engagement
• Purchases

Brands can identify products where shoppers frequently abandon the journey between steps.

This can highlight issues such as:

• Weak product content
• Poor pricing
• Ineffective imagery
• Competitive pressures

These signals can also power retargeting audiences.

Five-Year Customer Purchase Data

Amazon recently introduced a dataset that provides five years of purchase history tied to anonymized user IDs.

This dataset unlocks advanced analytics including:

• Customer lifetime value (CLV)
• Repeat purchase behavior
• Churn analysis
• Long-term customer cohorts

For many brands, this is the first time they can analyze true customer lifecycle behavior on Amazon.

Customer Lifetime Value Analysis

Using the five-year dataset, brands can analyze:

• How much revenue customers generate over time
• How customer value varies by acquisition cohort
• How repeat purchase behavior evolves

For example, brands can compare customers acquired in different quarters and measure their value after:

• 3 months
• 6 months
• 12 months
• Multiple years

These insights help brands invest more confidently in long-term customer acquisition.

Example AMC Audience Strategies

Brands are increasingly using AMC to build advanced audiences.

Some examples include:

Lookalike Audiences from Subscription Customers

A brand identified shoppers using Subscribe & Save, then created lookalike audiences based on those users.

These audiences were used across Sponsored Ads campaigns.

High-Value Customer Retargeting

Brands can identify shoppers who repeatedly purchase high-value products and target similar customers using DSP.

First-Party Data Integration

Brands can upload CRM data and use it to:

• Exclude existing customers from prospecting campaigns
• Cross-sell related products
• Target known customer segments

High-Intent Shopper Targeting

Many shoppers search for products but never click an ad.

These users can form a high-intent audience pool for additional targeting campaigns.

Building an AMC Strategy

To maximize AMC value, brands should establish a consistent experimentation process.

This typically involves:

1. Learning how AMC data works
2. Identifying key questions about shopper behavior
3. Generating insights through queries or dashboards
4. Creating audiences based on those insights
5. Testing audiences within advertising campaigns

Over time, this creates a continuous insight-to-activation flywheel.

About Intentwise

Intentwise helps brands and agencies turn Amazon data into actionable insights.

The company offers two main solutions:

Intentwise Analytics Cloud

A data and analytics platform that unifies:

• Retail data
• Advertising signals
• Shopper insights

This platform powers:

• Automated reporting
• Advanced analytics
• AMC analysis and activation

Intentwise Ad Optimizer

A performance optimization platform for:

• Sponsored Ads
• Amazon DSP

Together, these tools help brands transform complex datasets into clear performance insights and faster decision-making.

Final Takeaway

If there is one key takeaway from this session, it is this:

Amazon Marketing Cloud contains shopper-level signals that connect advertising events with shopping behavior.

Understanding how to use these signals allows brands to:

• Improve measurement
• Build stronger audiences
• Optimize advertising strategy
• Unlock deeper customer insights

AMC is quickly becoming the central intelligence layer for Amazon advertising.

Brands that learn to use it effectively will gain a significant competitive advantage.

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