For most consumer brands, Amazon is simultaneously their biggest growth opportunity and their biggest blind spot.
You know your monthly sales numbers. You track your TACOS. You monitor your bestseller rank. But ask a deeper question—"What's the actual LTV of our Amazon customers?" or "How long does it take for a Subscribe & Save customer to pay back?"—and the answer is usually silence, followed by weeks of manual spreadsheet archaeology.
Here's the uncomfortable truth: most Amazon analytics tools treat your customers like transactions, not people. They give you attribution and ad performance, but they ignore the metrics that actually matter for profitable growth—retention, lifetime value, and true contribution margin by customer cohort.
That's the problem Drivepoint set out to solve with our new Amazon Reporting Package. Because when you're spending six or seven figures on Amazon advertising, you deserve better than averages and assumptions.
The Amazon Data Problem Nobody Talks About
Amazon is one of the most expensive customer acquisition channels in retail. Between sponsored ads, DSP campaigns, and the platform's take rate, the cost of growth adds up fast. Yet most brands are flying blind on the metrics that determine whether that growth is actually profitable.
Traditional Amazon reporting stops at the transaction level. You see sales by SKU, orders by day, and maybe some basic repeat purchase rates if you're lucky. But you don't see cohorts. You don't see new vs. returning customer economics. You definitely don't see how Subscribe & Save fundamentally changes customer behavior and lifetime value.
The result? Finance teams planning Amazon with incomplete data. Growth teams making media mix decisions without understanding true payback periods. Leadership asking questions about Amazon profitability that take days to answer, if they can be answered at all.
This isn't just an analytics gap. It's a strategic disadvantage. While you're guessing at customer economics, your competitors who've figured out cohort-level reporting are making faster, smarter decisions about where to invest and how to scale.
What Makes Amazon Different (And Why Your DTC Reporting Won't Work)
If you're already tracking cohort-level metrics for your DTC channel, you might be thinking: "Can't I just apply the same framework to Amazon?"
The short answer is no. Amazon operates fundamentally differently than DTC in ways that break traditional cohort analysis:
The Subscription vs. Non-Subscription Split
Subscribe & Save isn't just a convenience feature—it completely changes customer economics. Subscription customers have different retention curves, different order frequencies, and different contribution margins than one-time buyers. Lumping them together in your analysis means you're optimizing for an average that doesn't actually exist.
New vs. Returning Customer Dynamics
On Amazon, the distinction between new and returning customers matters more than almost any other channel. New customer acquisition costs are dramatically higher. Returning customer behavior reveals your true product-market fit. Yet most analytics tools treat all orders the same, leaving you unable to measure the efficiency of your new customer acquisition or the strength of your retention.
Cross-Channel Attribution Complexity
Many brands drive customers to Amazon through off-platform advertising: Meta, Google, podcasts, influencer partnerships. These customers show up as "Amazon customers" in your reporting, but their acquisition cost lives somewhere else entirely. Without the ability to segment and track these cohorts separately, you're mixing high-CAC and organic customers in your LTV calculations, destroying the signal in your data.
Platform-Specific Margin Structures
Amazon's fee structure—referral fees, FBA fees, advertising costs—creates contribution margin profiles that differ significantly from DTC. A cohort might look profitable at the gross margin level but underwater when you account for the full cost structure. Understanding customer-level economics requires modeling these costs at the cohort level, not just at the product level.
The bottom line: Amazon requires purpose-built cohort analysis. Anything less leaves you making million-dollar decisions with incomplete information.
Introducing Drivepoint's Amazon Reporting Package
Drivepoint's Amazon Reporting Package gives CPG teams the same level of customer intelligence for Amazon that best-in-class brands have been using for DTC—cohort-level visibility into retention, lifetime value, and true contribution profit.
Instead of treating Amazon as a black box that spits out monthly sales numbers, Drivepoint turns it into a fully modeled customer channel where you can answer the questions that actually matter for profitable growth.
What You Get Out of the Box
Full Cohort Views
Track customer behavior over time by acquisition month. See retention curves, order frequency, and cumulative revenue by cohort. Understand not just how many customers you acquired, but how they behaved in months 1, 3, 6, and 12.
New vs. Returning Customer Segmentation
Separate new customer acquisition from repeat purchase behavior. Measure the efficiency of your new customer acquisition spend. Track retention rates and reorder patterns for customers who've bought before. Finally answer the question: "Are we actually retaining the customers we're spending to acquire?"
Subscription vs. Non-Subscription Breakouts
Analyze Subscribe & Save customers separately from one-time buyers. Compare retention curves, order values, and lifetime value between subscription and non-subscription cohorts. Understand whether subscriptions are driving meaningful LTV uplift or just shifting revenue timing.
Net Sales and Contribution Profit LTV
Move beyond vanity metrics like gross sales. See true Net Sales (after Amazon's returns, chargebacks, and other deductions) and Contribution Profit (after all variable costs including advertising, FBA fees, and COGS) at the cohort level. Know exactly what each customer cohort actually contributes to your bottom line.
Cross-Channel Reporting Integration
Measure the impact of off-Amazon advertising on Amazon customer acquisition. Track cohorts driven by Meta, Google, or influencer campaigns separately from organic Amazon customers. Allocate CAC correctly and understand true blended economics across channels.
The Questions You Can Finally Answer
With cohort-level Amazon reporting, your finance and growth teams can answer the strategic questions that have been nearly impossible to address:
- Are your Amazon customers actually profitable over time? Not just in month one, but across their entire lifetime as customers.
- Do new Amazon customers behave differently than returning ones? And what does that mean for your acquisition strategy and payback assumptions?
- Does Subscribe & Save meaningfully change LTV—or just shift when revenue shows up? The difference matters enormously for cash flow planning and channel investment decisions.
- How long does it really take for Amazon customers to pay back? When you account for all acquisition costs, platform fees, and contribution margin, what's your true payback period by cohort?
- Which acquisition sources drive the most valuable Amazon customers? Are customers who find you organically more valuable than those driven by off-platform ads? What about those acquired through Amazon DSP versus Sponsored Products?
- Is your retention getting better or worse over time? Are newer cohorts performing better than older ones, suggesting improving product-market fit? Or are they performing worse, indicating saturation or quality issues?
These aren't academic exercises. These are the questions that determine whether your Amazon growth is building enterprise value or burning cash.
Why This Level of Reporting Has Been Nearly Impossible—Until Now
Very few platforms offer cohort-level Amazon reporting at this level. There's a reason why.
Amazon's data structure is built for marketplace operations, not cohort analysis. Order-level data lacks persistent customer identifiers in the way that DTC platforms provide them. Subscription data lives in a separate system from one-time purchase data. Returns, refunds, and chargebacks require careful reconciliation to calculate true Net Sales.
Building cohort views requires stitching together data from Amazon Seller Central, Amazon Advertising, your 3PL for COGS, and often external attribution platforms—then applying sophisticated logic to segment customers, calculate contribution margins, and track behavior over time.
Most Amazon analytics tools punt on this complexity. They focus on what's easy to measure: sales trends, ad performance, keyword rankings. They ignore LTV and retention entirely because building that capability is genuinely hard.
Drivepoint doesn't punt. We built our entire platform around the belief that consumer brands deserve enterprise-grade financial intelligence, and that includes making Amazon as transparent and modelable as any other channel.
We've solved the data engineering complexity so you don't have to. The cohort views, segmentation, and LTV calculations work out of the box. Your team gets Amazon reporting that matches the sophistication of your DTC analytics—no manual spreadsheet work required.
What This Means for How You Run Your Business
Better reporting isn't just about having prettier dashboards. It's about making fundamentally different strategic decisions.
For Finance Teams
Stop forecasting Amazon with top-line assumptions. Start modeling it channel with customer-level economics—retention curves, cohort-based LTV, and realistic payback periods. Build budgets and scenarios that reflect how Amazon customers actually behave, not how you hope they behave.
For Growth Teams
Shift from optimizing for lowest ACOS to optimizing for highest LTV. Understand which acquisition sources drive customers worth acquiring. Make defensible cases for customer acquisition spend based on payback data, not attribution hand-waving.
For Leadership
Get the visibility you need to evaluate Amazon as a strategic investment, not just a sales channel. Understand the trade-offs between new customer acquisition and retention investment. Make confident decisions about how much to scale Amazon spend based on real cohort economics.
When 75% of Drivepoint customers improve their EBITDA margin by an average of 6.7 percentage points in their first year, it's not because our software has magic beans. It's because cohort-level visibility—across all channels, including Amazon—enables teams to stop guessing and start optimizing based on what actually drives profitability.
Ready to Turn Amazon Into Your Most Transparent Channel?
If you're tired of treating Amazon like a black box—if you're ready to understand the true economics of your Amazon customers and make strategic decisions based on cohort-level data instead of averages and assumptions—it's time to see Drivepoint in action.
The modern way to do FP&A isn't humans and spreadsheets. It's using purpose-built technology that handles the complexity so your team can focus on strategy and optimization.
Book a Demo and see how Drivepoint's Amazon Reporting Package gives your team the customer intelligence you've been missing—cohort views, retention analysis, true LTV calculations, and contribution profit segmentation, all out of the box.
Because when you're spending six or seven figures on Amazon, you deserve to know whether those customers are actually profitable. And more importantly, you deserve to know what to do about it.
About Drivepoint
Drivepoint is the AI-powered FP&A platform built exclusively for consumer brands. As finance teams face mounting pressure to deliver real-time insights across fragmented retail channels, Drivepoint automates data consolidation and scenario planning across DTC, Amazon, wholesale, and retail operations. By eliminating the manual spreadsheet work that creates strategic bottlenecks, Drivepoint helps consumer brands make confident decisions at the speed of opportunity while improving profitability—customers improve EBITDA margins by 6.7 percentage points on average within their first year.
