Brands advertising on Amazon frequently struggle to obtain a complete picture of their campaign performance across varied ad tactics. This blind spot primarily stems from Amazon’s traditional last-touch attribution model, which severely limits visibility into the actual impact of upper-funnel tactics like display ads executed via Amazon DSP. To solve this attribution problem, Amazon officially launched AMC in 2021, operating as a secure data clean room of advertising events. This infrastructure allows advertisers to generate deep insights past the last click.
By utilizing AMC, brands have gained invaluable insights into the incrementality of upper-funnel advertising, new-to-brand performance, and lifetime value. However, until late 2025, a major time grain issue persisted: the historical Amazon Marketing Cloud dataset was strictly limited to a 13-month rolling lookback.
This 13-month restriction meant key metrics like new-to-brand (NTB) or lifetime value (LTV) only took into account whether a shopper had purchased within the prior year, causing earlier purchases and historical revenue to be entirely missed. To address this massive gap, Amazon released a new dataset called Amazon Retail Purchases, giving advertisers up to five years of comprehensive purchase data. In June 2026, this expanded dataset was made free for queries through the end of 2026. Just as marketers must leverage modern AI integrations (read our comprehensive guide on ChatGPT ads GEO visibility secrets to master conversational funnels), sellers must adapt to this new data standard. Here are 6 amazing use cases unlocked by the 5-year Amazon Marketing Cloud dataset.
1. Discover True Lifetime Value with the Amazon Marketing Cloud Dataset
If you sell as a Vendor on Amazon, you previously had virtually no way to deeply understand the true LTV of your individual customers. With the five-year Amazon Marketing Cloud dataset unlocked, you can now finally understand this critical metric all the way down to the specific product level.
When you truly understand LTV, you can make better, more aggressive decisions about where your Customer Acquisition Cost (CAC) needs to fall on a per-product basis. For example, several CPG brands may discover they have an incredibly high LTV after a shopper initially purchases a lower-priced SKU, as those buyers eventually convert into higher-priced multi-packs. This realization could lead to a strategic decision to intentionally take a loss on the initial purchase, massively increasing available advertising allocation because you know the shoppers will bring profitable revenue over the longer term.
2. Measure New-To-Brand (NTB) Rates Using the Amazon Marketing Cloud Dataset
Because AMC was previously limited to a 13-month rolling lookback period, calculating the true new-to-brand rates for both a brand’s overall advertising campaigns and individual products was heavily skewed.
- For brands with much longer repurchase cycles, like high-end consumer electronics, it was incredibly difficult to understand which tactics successfully acquired net-new customers.
- With the five-year shopping data now available, brands can access 60 full months of rolling shopping events.
- This grants advertisers a much more accurate and true new-to-brand rate.
- Because several brands find that a rigid five-year window is too long, the retail purchase dataset is highly flexible.
- Advertisers can dynamically customize their NTB window based strictly on their exact specifications up to the full 60 months.
3. Optimize Repeat Purchase Windows in the Amazon Marketing Cloud Dataset
Before the retail purchase dataset was made widely available, understanding exact repeat purchase cycles was nearly impossible for several retail categories with extended customer lifecycles, such as luxury goods. With only 13 months of historical data available, brands actively missed key insights. Furthermore, they lost the ability to retarget past purchasers simply because their standard repeat purchase window exceeded the 13-month threshold.
With the five-year lookback availability inside AMC, these brands can now fully understand their ideal repeat purchase windows. They can instantly create and activate highly targeted audiences that reach shoppers specifically within their ideal post-purchase time window. This powerful audience activation actively extends across the Amazon display network, Prime Video, sponsored ads, and third-party inventory.
4. Identify Gateway Products via the Amazon Marketing Cloud Dataset
Once you accurately understand metrics such as lifetime value or new-to-brand rates by product, the natural next question is discovering exactly which products are driving the entry of customers who eventually purchase your higher-priced SKUs.
For standard CPG brands, this gateway event could mean the initial purchase of bulk products. For consumer electronics, it may be a customer testing a base model before eventually buying an upgraded model. No matter the specific retail scenario, the 5-year Amazon Marketing Cloud dataset enables brands to look across an extended timeline to map the customer lifecycle across all SKUs. This data drives key executive decisions regarding which products should be pushed to net-new shoppers in advertising campaigns, placed on promotion, or used to focus retargeting efforts against past purchasers. You can review additional developer documentation on Amazon Ads to master these technical capabilities.
5. Reacquiring Lapsed Customers with the Amazon Marketing Cloud Dataset
Amazon advertising offers several built-in methods for targeting past purchasers of your specific products. Using Amazon DSP, advertisers can reliably create custom audiences with flexible lookback windows up to 365 days. However, none of these legacy methods provided a way to target purchasers who lapsed past 13 months. If a brand lost a customer for over a year, they had absolutely no means to attempt to reacquire them, regardless of their previous high lifetime value.
Since the new retail purchase dataset is available not only for queries but also for activating audiences, brands can now activate long-term winback strategies. By leveraging AMC’s advanced segmentation abilities, brands can completely customize the lookback window of historical purchases, set a strict minimum LTV threshold, and focus heavily on specific product purchasers.
6. Combine First-Party Data in the Amazon Marketing Cloud Dataset
One of the absolute most underleveraged features of AMC is the unique ability to upload first-party shopper data to be joined seamlessly with Amazon’s own shopper data. If a retail brand has direct access to shopper-level purchase history via a direct-to-consumer (DTC) website or a robust email list, this data can be securely hashed and uploaded directly into AMC.
This external data can then be securely joined with the Amazon Marketing Cloud dataset using privacy-safe shopper IDs. Brands can thoroughly understand the complete lifecycle of their shoppers across external platforms, mapping exactly how Amazon interactions affect direct-to-consumer purchasing and vice versa.
Frequently Asked Questions
What is the new Amazon Marketing Cloud dataset?
The new Amazon Retail Purchases dataset extends the historical lookback window for Amazon purchase data from 13 months to a full five years (60 months).
How much does the 5-year dataset cost?
Historically requiring a $500 monthly subscription for query execution, Amazon made the 5-year dataset free to query starting in June 2026 through the end of the year.
Why is a 5-year lookback important?
It allows advertisers selling durable or seasonal goods with long replacement cycles to accurately track long-term customer lifetime value (LTV), new-to-brand metrics, and repeat purchase behavior that would otherwise be lost in a 13-month window.
