Amazon DSP (Demand-Side Platform) reports are the “black box” of Amazon advertising. Unlike Sponsored Products, DSP measures behavior rather than just keywords. To win here, you must move from “how many people clicked?” to “how many new people did I reach?”. So learning how Amazon DSP Reports work is pretty much vital.
But it is not simple to do this. Understanding DSP Reports requires a big shift in your understanding of ad orders.
However, it is possible to take full advantage of DSP Reports even if you’re not an Amazon expert. All you need is the right information.
That’s why this article will explain all you need to know about this subject so you can prepare yourself to run smoother, more effective Amazon DSP Orders.
Before You Start: What You Need to Have in Place for Accurate Amazon DSP Reporting
This article assumes you’ve already run a DSP order with a clear objective in mind.
To generate the right leads and serve your customers effectively, sellers must plan and organize their marketing strategies.
It’s not like customers will see your advertising and instantly make a purchase. Customers typically weigh several factors before making a purchase decision.
Thus, the seller needs to understand the three stages of the sales funnel to create content tailored to each stage.
Amazon DSP Reports Overview: The 5 Report Types That Drive Better Decisions
Reports can be created through the Amazon DSP Console under Measurement & Reporting:
Then, click on New custom report. Before we continue with Report creation, here are five useful types of DSP Reports that will usually cover your needs as you continue to use the platform:
Audience Reach Report: Measure Unique Reach and New Audience Growth
Audience Reach reports focus on how many unique people your ads reached. Their main objective is to help you understand whether your orders are actually expanding exposure or whether they are simply circulating among the same users.
These reports show the total number of unique humans reached, deduplicated across devices. This matters because the same person might see your ad on a Fire TV, a mobile app, and a desktop browser, but should still be counted as one individual.
Reach tells you if DSP is doing its job of introducing your brand or product to new potential customers. Very useful for Amazon DSP Retargeting.
If reach remains flat while spend increases, it usually means the order is saturated and additional budget is going toward repetition instead of expansion. In contrast, healthy reach growth indicates that DSP continues to acquire new users within the selected audiences.
Frequency Report: Control Ad Repetition and Reduce Wasted Spend
Frequency is closely tied to reach and is often analyzed alongside it. While reach tells you how many people saw your ads, frequency tells you how many times, on average, each person saw them.
These reports work like a waste detector. If frequency is too high, you risk annoying users and spending budget on diminishing returns. If frequency is too low, users may not remember your brand or product at all.
There is no universal definition of what is too high or too low. It mainly depends on your timeframe and the overall performance of the DSP orders you’ve run before. In general, many sellers aim for 3 to 7 exposures per day window. This should not be treated as a strict rule, though. It depends on the performance of the order.
Again, all of this depends on your niche, too. Experience will tell what works for your business.
Recency Report: Find the Time Lag Between Ad Exposure and Purchase
Recency reports add another layer of context by showing how much time passed between a user’s last ad exposure and their purchase. In simple terms, they help answer how long it takes someone to buy after seeing a DSP ad.
This is especially important for products with longer consideration cycles. Some users may convert quickly after exposure, while others may take days or even weeks to make a decision. Recency helps you understand whether your retargeting windows are aligned with real buying behavior, or whether ads continue to serve long after their influence has faded.
- If purchases tend to happen shortly after exposure, long retargeting windows may be unnecessary.
- If purchases happen much later, aggressive short-term retargeting may create waste without improving results.
Path to Conversion Report: Understand Assist Touchpoints and View Through Impact
This type of Report shows the ad touchpoints a customer had on their 30-day path to conversion. In plain terms, it shows the sequences that lead to purchases.
For example, your ad may show up while streaming a documentary on Freevee via their Fire TV. But they don’t buy immediately.
Three days later, while browsing a lifestyle blog, they see a DSP Display Banner featuring the same product. Still no click, but there is consideration.
Then, two days after that, they visit Amazon to buy groceries. They see your Sponsored Ad in the “Inspired by your browsing” slot, click it, and finally purchase.
Reports focused on the conversion path will show you this journey in detail.
Audience Segmentation and Overlap: Expand Targeting with High Intent Lookalike Audiences
These reports are the ultimate expansion tool.
They will show you the performance by audience segment. Audience overlap specifically helps you discover other audiences that share members with your selected audience, so you can find new, similar audiences to test.
It identifies other interests your customers have, helping you better understand when and where to display your ads.
Amazon DSP Metrics That Matter: DPVR, eCCDV, NTB Percent, Reach, and View Through Conversions
Amazon DSP and PPC are different. DSP campaigns are not measured like Sponsored Ads. This chart highlights the metrics that best reflect DSP’s role in building awareness, driving consideration, and influencing purchases over time.
| What to Ignore | What to Prioritize | What Each Metric Proves |
| CTR (Click-Through Rate) | DPVR (Detail Page View Rate) | Users rarely click display ads. DPVR proves the ad actually drove them to your product page later. It should be read alongside reach and frequency. |
| Impressions | NTB (New-to-Brand) % | Impressions only track delivery. They are not useless. They are secondary.
NTB, on the other hand, demonstrates that the DSP order is actually growing your business by acquiring new customers. |
| CPC (Cost Per Click) | eCCDV (Cost Per Detail Page View) | DSP is more about consideration and intent. You want to know what it costs to get a shopper into your funnel. That’s why CPC loses value in DSP. CPC assumes intent while DSP operates in an intent-driven environment.
The Cost Per Detail Viex (eCCDV) metric, though, measures exactly what you want to know. It tells you how much you are paying to get someone to visit your product detail page after being exposed to a DSP ad, whether they clicked the ad or not. |
| ROAS (Standard) | View-Through Conversions | Standard ROAS heavily favors last-click behavior and undervalues DSP’s role. Many users are exposed to DSP ads on TV, mobile apps, or websites, then convert days later through Search or organic traffic.
View-through conversions capture this delayed influence and the broader halo effect of DSP, helping you understand how upper-funnel exposure contributes to sales without requiring an immediate click. |
How to Build Amazon DSP Reports: Dimensions, Time Unit, and Metrics Columns
What many sellers struggle with at the beginning is how granular Amazon’s Demand-Side Platform actually is.
Amazon DSP does not give you fixed “Audience Report,” “Path to Conversion Report,” etc as single buttons. Instead, almost all DSP reports are built by combining:
- Dimension
- Time unit
- Columns
DSP Report Dimension: Choose the Level That Matches Your Optimization Goal
Dimension is simply what you’re grouping the data by. In the screenshot, the main dimension is set to Campaign, the standard one. However, there are many more you can play with:
Below this, there’s a list of “Breakdown” checkboxes selected:
DSP Report Dimension: Choose the Level That Matches Your Optimization Goal
Each checkbox adds another layer of detail to each row of data:
- Advertiser: The brand or advertiser account. Mostly useful if you manage multiple advertisers.
- Order: The insertion order. This is usually tied to a specific strategy or budget grouping.
- Line item: This is the most important level for DSP optimization. Line items are where targeting, format, bidding, and budgets live.
- Creative: This breaks performance down by individual ad creative.
- Campaign flight: This groups results by flight dates. Useful only if flights are actively used.
This means the report type is not chosen upfront. You create it by choosing the right dimension.
DSP Time Unit: Summary vs Daily vs Weekly for Analysis and Trend Reporting
How should I group time in my order? That’s the answer Time Unit solves.
When you choose Summary, all selected dates are combined into a single total. This one is best for strategy decisions.
- In Daily, each day gets its own row.
- Day of week groups performance by Monday, Tuesday, etc.
- Weekly or Monthly is usually used for trend analysis and executive reporting.
DSP Report Columns: Select Metrics for Traffic, Conversions, NTB, and View Through
Columns are the metrics. This is where you choose what Amazon will actually measure. The left menu groups metrics into categories:
- Traffic: Impressions, clicks, viewable impressions
- Rates: CTR, DPVR, viewability rate
- Costs: Spend, CPM, CPC
- eCommerce conversions: Detail Page Views, purchases, sales, NTB metrics
- Combined conversions: Includes view-through and click-through combined
- Off-Amazon conversions: Used mainly for AMC or pixel-based measurement
It is by combining the three elements that you get each DSP Report type we covered earlier.
Here’s how.
Build a Reach Report: Campaign vs Line Item Views for Audience Expansion
Dimension: Campaign or Line item. Campaign is useful for a high-level view, while Line item is better if you want to understand reach by targeting strategy or format.
- In the Breakdown section, you typically keep Advertiser, Order, and Line item selected. Creative is optional here, as this report focuses on exposure and not message performance.
Time Unit: select Summary. Reach is almost always analyzed as a cumulative number over a period, not day by day.
Columns: At a minimum, include Impressions, Reach, and Frequency. They should all be metrics related to traffic and reach. Viewable impressions can be included if you want an additional quality signal, but they are not required for a basic reach analysis.
Build a Frequency Report: Identify Saturation, Overlap, and Delivery Waste
You again start with Dimension set to Campaign or Line item. Line item is usually preferred, because frequency issues almost always come from targeting overlap or narrow audience definitions at the line item level.
- Keep the same Breakdown selections as the Reach report.
Time Unit should remain Summary.
In Columns, include Impressions, Reach, Average frequency, and, if available, Frequency buckets. Frequency buckets are handy because they show how many users saw the ad once, twice, five times, and so on.
This configuration allows you to see whether the budget is being used to reinforce memory or wasted through excessive repetition.
Build a Recency Report: Set Retargeting Windows Based on Real Purchase Timing
Dimension: use Line item. Recency analysis only makes sense when tied to specific targeting and tactics.
- Keep Advertiser, Order, and Line item in the Breakdown.
Time Unit: Summary. Recency is analyzed across the whole window to understand timing patterns, not daily behavior.
Columns: Purchases, Detail Page Views, and Recency metrics if available in your account. Select conversion-related metrics that support recency analysis. Some DSP interfaces expose recency as time-to-conversion groupings rather than a single metric.
This configuration lets you see whether conversions occur shortly after exposure or later, which directly affects the ideal retargeting window.
Build a Path to Conversion View: Compare Click Through vs View Through Contribution
The Path to Conversion report is partially built outside the standard configuration page, but the configuration page supplies the underlying data that supports it.
Dimension: Campaign or Line item. Campaign works well for understanding how formats work together, while Line item gives more tactical insight.
- In the Breakdown, keep Advertiser, Order, and Line item selected.
Time Unit: Summary.
In Columns Purchases, Detail Page Views, View-through conversions, and Click-through conversions. We’re aiming towards conversion metrics that allow you to compare assist behavior.
This configuration will not show you the whole customer journey, but it’ll help you understand how DSP contributes to it.
Build an Audience Overlap Report: Find New Segments to Scale Without Fatigue
The Audience Overlap report requires a small but important change in how you use the Dimension setting.
Dimension: Set it to Audience. This allows the report to group results by audience segment rather than by campaign structure.
- In the Breakdown, include Line item so you can see which targeting strategies are tied to each audience. Advertiser and Order are usually left on by default.
Time Unit: Summary.
Columns: Reach, Impressions, Detail Page Views, Purchases, and New-to-Brand metrics if available. These help you evaluate audience size and also quality.
This configuration reveals which audiences share users, which ones are saturated, and which adjacent audiences may be good candidates for expansion.
Key Takeaways: How to Use DSP Reporting to Improve Targeting, Retargeting, and Incremental Growth
Amazon DSP is designed to influence shoppers across devices and over time, so the reporting approach must shift from click-based to audience- and behavior-based measurement.
The reports covered here are Reach, Frequency, Recency, Path to Conversion, and Audience Segmentation/Overlap, are the core tools that let you answer the questions that matter in DSP:
- Are we expanding exposure or just repeating impressions to the same users? (Reach + Frequency)
- Is our retargeting window aligned with real buying timelines? (Recency)
- How does DSP assist conversions alongside other touchpoints? (Path to Conversion + view-through impact)
- Where can we scale efficiently without audience fatigue? (Segmentation + Overlap)
If you prioritize DPVR, eCCDV, NTB%, reach, frequency, and view-through conversions, you get a clearer view of DSP’s true contribution: building awareness, creating consideration, and driving incremental customers… not just harvesting last-click sales.
Amazon DSP Reporting FAQs: Reach, Frequency, Recency, NTB, and Attribution
Is Amazon DSP reporting different from Sponsored Ads?
Yes. Sponsored Ads reporting is mostly click and keyword-focused. Amazon DSP reporting is built around audience exposure, behavior, and influence over time.
Why does Amazon DSP focus so much on reach and frequency?
Because DSP is designed to introduce products and brands to shoppers who may not yet be actively searching.
What is the difference between reach and impressions?
Impressions count how many times an ad was shown. Reach counts how many unique people saw the ad. One person can generate multiple impressions. In DSP, reach is more meaningful than impressions because it shows audience expansion.
How should I use recency data in practice?
Recency helps you understand how long it typically takes shoppers to convert after seeing a DSP ad. This insight is especially useful for setting retargeting windows.
How do I know if Amazon DSP is incremental or cannibalizing my Sponsored Ads and organic sales?
This helps sellers interpret view through conversions, NTB percent, and overlap to confirm DSP is expanding demand instead of recycling existing buyers.
What is a good DPVR benchmark for Amazon DSP, and how do I troubleshoot low DPVR?
This targets a common pain point and lets you explain creative fatigue, audience quality, frequency, and landing page relevance in a practical way.
When should I optimize DSP at the line item level vs the campaign or order level?
This clarifies reporting structure and gives you a clean bridge into dimension selection and how to isolate what is actually driving performance.
How do I choose the right lookback window and retargeting window in DSP reporting?
Sellers search this constantly because the wrong windows create wasted spend. This also pairs well with your recency section.
Why does Amazon DSP sometimes show conversions with low clicks, and how should I report that internally?
This addresses the “DSP feels fake” objection and gives them language to explain view through impact and halo effect without relying on CTR or last click ROAS.
Ready to Make Amazon DSP Reporting Actionable?
Amazon DSP reporting is only valuable when it turns into clear decisions. Reach, frequency, recency, DPVR, eCCDV, and New to Brand metrics are signals that point to what is working, what is saturated, and where spend is getting wasted.
By filling out the form below, you step into a focused conversation that connects your DSP reports to real actions. The goal is to help you understand what the data is actually saying about audience growth, retargeting windows, and incremental sales so you can scale with confidence.
Share a bit about your brand and what you are trying to accomplish with DSP, and one of our Amazon advertising specialists will reach out with specific insights tied to your account. No pressure. No generic pitch. Clear guidance on how to measure DSP properly and use reporting to improve performance.
Fill out the form below, and let’s turn DSP reporting into a practical advantage for your business.