The era in which Amazon marketing was limited purely to running ads and hoping for a good ROAS is over. In 2026, the marketplace is so saturated that brands need a new level of transparency, not just to manage their profitability, but to actively steer it. While the standard version of Amazon Marketing Cloud (AMC) already provides deep insight into your advertising world, the AMC Paid Features (often bundled under the module Flexible Shopping Insights) unlock an entirely new dimension: the seamless connection of advertising with your real, organic retail data. Instead of only knowing which click theoretically led to a purchase, you now learn how your entire brand is moving on Amazon, even when no direct advertising event was involved.
- The technical foundation: what's behind the premium upgrade?
- Incrementality: the "incremental revenue check" for your budget
- Why the 60-month lookback revolutionizes your brand strategy
- The bridge to your data: first-party data matching
- Implementation: how to activate the Paid Features and use the "trial"
- Case study: strategic brand steering using a manufacturer in the garden & tools space
- Conclusion & outlook: your precise compass in a cookieless world
- FAQ – frequently asked questions about AMC Paid Features
- Your experts for AMC & data strategy
The technical foundation: what's behind the premium upgrade?
The AMC Paid Features are not a standalone program but a powerful upgrade within your existing AMC instance. It's the "premium package" that taps into data sources that remain invisible to normal advertisers.
→ The three core building blocks:
Amazon Flexible Shopping Insights
The centerpiece. It delivers data on all shopping events (purchases, detail page views, cart interactions) that occurred organically. That means you finally also see the customers who bought your brand without ever clicking an ad.
Amazon Audience Segment Insights
The "who" behind the purchases. Get aggregated information about lifestyle interests. For example, you'll learn whether your buyers are disproportionately "dog owners" or "outdoor enthusiasts."
Amazon Retail Shopping Insights (incl. Extended Lookback)
While standard AMC usually stores your data for only about 12.5 months, this module unlocks a history of up to 60 months (5 years). It's the indispensable foundation for calculating real long-term trends and Customer Lifetime Value (CLV), i.e. the total value a customer generates for your brand over years rather than just looking at a one-off purchase. At the same time, it corrects the often misunderstood New-to-Brand (NTB) metric: you now see precisely whether a buyer is truly ordering from you for the first time or simply returning after 14 months as a "loyal repeat buyer."
Incrementality: the "incremental revenue check" for your budget
A technical term that, in practice, determines profit or loss. Incrementality answers the question: did the ad really move the customer, or would they have bought anyway?
Without the Paid Features (i.e. without organic data), you could previously only see that a customer made a purchase after seeing an ad. But you couldn't know whether that customer was a loyal fan who finds you organically every week anyway. With Flexible Shopping Insights we measure the efficiency of your budget. We identify the net result: revenue that simply would not have existed without the ad. This also helps you honestly evaluate your New-to-Brand (NTB) rate: are you really winning new customers through advertising, or are you just paying for sales to your existing customers?
Why the 60-month lookback revolutionizes your brand strategy
The time dimension is often underestimated in data analysis. Most brands optimize for 7, 14, or at most 30 days. But real customer relationships last years.
→ Why 5 years of history makes the difference for you
Real repurchase cycles
For products with a long lifespan (such as tools, home appliances, or travel luggage), you don't buy new every year. Only with a 5-year view do you understand when customers truly come back for an upgrade or accessories. Without this insight, these loyal buyers are incorrectly flagged as New-to-Brand (NTB) again and again, simply because their last purchase was more than 12 months ago.
Seasonal loyalty
Do your customers only buy every two years around Prime Day? Without the Extended Lookback, this rhythm stays hidden. With 60 months of data we identify recurring behavior patterns across multiple years and can calculate marketing budgets for major events more precisely.
Loyalty tracking & reactivation
You identify your "super users" who have been loyal to your brand for years. Above all, the 5-year retrospective enables highly precise reactivation. We can specifically target customers whose last purchase was exactly 36 months ago, the ideal moment for a model upgrade or replacement parts.
Real repurchase cycles
Seasonal loyalty
Loyalty tracking
The bridge to your data: first-party data matching
One aspect that is often overlooked in the discussion around Paid Features is the integration of your own data. As a modern brand, you likely have your own online shop or customer database (CRM). With the corresponding paid modules, you can upload your own encrypted customer data into AMC. The system then matches it anonymously against Amazon's data.
- The result: you learn how many of your shop customers later buy on Amazon, or how your Amazon advertising influences sales in your own shop.
- Your safety: since AMC is a "data clean room," everything stays privacy-compliant. Neither you nor Amazon can identify individual people, but you gain statistical certainty about your customers' behavior across platform boundaries.
Implementation: how to activate the Paid Features and use the "trial"
Opting into the Paid Features requires not just budget but, above all, the right skillset. In your AMC console you'll find the corresponding options under the "Paid Features (beta)" tab.
→ The path to your insights
Individual pricing
Amazon calculates the fee based on your account's data volume. Via the "See options" button you get your individual price proposal.-> Xingu tip: pricing is not a fixed rule. It's often worth proactively reaching out to your Amazon Account Executive (AE) to discuss individual terms or package options for the Paid Features.
The 60-day trial
Amazon often gives you the option to test the feature free for 60 days. This is the ideal phase to run your first incrementality analysis.
The technical SQL hurdle
this is the point where many brands hesitate. The data doesn't arrive as a ready-made dashboard. It sits in raw tables that must be queried via SQL (a database language).
This is where we come in as Xingu. We see ourselves as your interface: you give us the business questions, we write the right SQL queries in AMC to hand you back the answers in the form of clear, strategic recommendations. Unlocking the features is the tool; the art lies in drawing the right conclusions for your budget allocation. Feel free to reach out to us, no obligation!
Case study: strategic brand steering using a manufacturer in the garden & tools space
To translate theory into practice, let's look at a real scenario from a leading manufacturer in the garden and home improvement sector.
→ The problem: NTB rate vs. reality
A manufacturer in the garden and tools space had the problem that the standard 12-month New-to-Brand (NTB) rate was not representative of real Customer Lifetime Value (CLV).
For products with longer life cycles (e.g. high-quality cordless drills), customers buy less frequently. Between the first purchase and the purchase of an additional device or replacement part, 18 or 24 months often pass. Since Amazon defines NTB value only over a 12-month window by default, a loyal existing customer who bought from the brand again after 1.5 years was incorrectly counted in the system as a "new customer." The brand was therefore investing budget in supposed new-customer acquisition, when in reality it was "merely" (though valuably) nurturing existing customers.
→ The solution: the Extended Lookback
By using the AMC Paid Features, the analysis window was extended to 60 months. Only this 5-year view revealed the true face of the customer base: a significant portion of "new customers" were in reality loyal brand fans who simply had a longer repurchase cycle.
→ The result: strategic realignment
Only this transparency made it possible to precisely calculate the real Customer Lifetime Value (CLV). The brand could now accurately assess what acquiring a genuinely new customer is allowed to cost, since the long-term value of customers over the years was now measurable. This led to a significantly more efficient budget allocation, moving away from short-term ROAS toward profitable long-term steering. By cleaning up the data and specifically targeting actual new customers, the real NTB rate was increased by up to 15%, since the budget was no longer being spent ineffectively on loyal existing customers.
Conclusion & outlook: your precise compass in a cookieless world
The AMC Paid Features turn your Amazon marketing from pure click optimization into well-founded business steering. You learn your true incremental revenue, understand the value of your customers over the years, and can invest your budget where it delivers the greatest real added value for your growth. But the strategic value goes beyond pure performance: at a time when conventional tracking methods are increasingly going "blind" due to stricter browser policies and the end of third-party cookies, AMC remains your stable anchor. Because it's built on Amazon's own first-party signals and operates within a protected data clean room, it is the only solution that will still deliver precise data in 2026 and beyond, without compromising your customers' privacy.
FAQ – frequently asked questions about AMC Paid Features
In the free version you only see customers who have seen or clicked your ads. In the Paid Features you see your entire customer base (organic + paid) and can compare these groups directly against each other.
There's no blanket answer here. Amazon often doesn't work with fixed price lists. Our experience shows: the Paid Features are often negotiable as part of annual discussions or Joint Business Plans (JBP) with Amazon. It's definitely worth actively raising the topic with your vendor manager or as part of DSP media planning, rather than waiting for "standard prices."
Yes, that's strongly recommended. Since the data is in raw form, complex questions like incrementality or CLV can only be answered through custom programming. Partners like Xingu take this technical burden off your hands.
Absolutely. AMC is a "data clean room." That means data can be analyzed but never exported at the individual level. Your privacy and that of your customers remains protected at all times.
Yes, that's one of the biggest advantages. You can create audiences such as "bought 3 years ago but has been inactive for 12 months" and target them specifically via Amazon DSP.