If you run DSP campaigns, manage Brand Stores, or want to get into podcast advertising, you should pay attention to the three big Amazon advertising updates that came out in January 2026.
Amazon added a shopping-signal-enhanced last-touch attribution model to Store ads, added the Podcast Audience Network to Amazon DSP, and gave Brand Stores section-level performance insights.
These aren’t big news stories like the unBoxed event in November. But they do help advertisers with real problems they have every day.
View Attribution Updates: Shopping-Signal Enhanced Model for Smarter Conversion Tracking
Launch Date: January 1, 2026
Amazon came up with a new attribution model after doing a lot of research on how people shop in the Amazon store.
The shopping-signal enhanced last-touch attribution model is what it’s called. It changes the way view-through conversions are credited in a big way.
The Challenge with Traditional Attribution Models
Attribution has always been hard in digital ads. In the past, last-touch models gave all the credit to the last ad interaction before the purchase.
But that leaves out the discovery phase, which is when people first see your brand while looking through categories or products.
Amazon’s research found that traditional models had some big issues:
- Some ad views help people find new brands when they are looking for something in a general category or just browsing.
- These moments are important for conversions, but earlier models of attribution didn’t give them enough credit.
- People often give credit to the last ad they saw, even though they really decided because of earlier discovery moments.
The new model focuses on these discovery moments and gives credit where it really counts for buying something.
It has a shorter attribution window that shows how real people shop on Amazon.
Now that this method is out, it’s the standard way to report on conversion metrics like Purchases, Sales, and return on ad spend (ROAS).
But you can still see the old view. Unified Reporting APIs and interfaces still have “all views” metrics, such as Purchases (all views), which show all ad views for eligible campaigns over 14 days.
Which Campaign Types Are Affected?
This attribution update affects specific campaign types:
- Sponsored Brands campaigns
The new attribution methodology applies to view-through conversions. If someone sees your Sponsored Brand ad during a category browse, then purchases later, the attribution credit now depends on whether that view happened during a discovery moment.
- Sponsored Display campaigns
Campaigns billed on a viewable impression basis, including branded keyword campaigns, now use the new model. These campaigns often serve ads during exploratory browsing, exactly where the shopping-signal enhancement focuses.
- Amazon DSP campaigns
DSP campaigns that serve ads in the Store now credit conversions based on the enhanced model. DSP inventory in the Store reaches shoppers at various journey stages, and the new attribution recognizes which views truly drive discovery.
Conversion reporting for all other campaign types and inventory types remains unchanged. Click-based attribution also stays the same. Clicks still get full credit regardless of attribution model—this only affects view-through conversions.
Impact on Campaign Optimization Strategy
Attribution models affect how you improve your campaigns. Your optimisation strategy needs to change if the conversion metrics you use to make optimisation decisions change how they are calculated.
The shopping-signal enhanced model puts discovery moments at the top of the list:
- Under the new model, campaigns that reach shoppers while they are browsing or searching for a specific category may get more attribution credit.
- Campaigns that mostly retarget shoppers who are close to making a purchase may get less view-through attribution credit.
- The people who saw your ads and made purchases were still the same; only the way you measured them changed.
It’s important to know this difference when reporting to stakeholders and setting performance goals.
A drop in reported conversions doesn’t always mean worse performance.
It could just mean that fewer conversions met the new attribution standards.
The “all views” metrics keep things going.
You can see how attribution methodology affects reported performance by tracking both standard metrics (new model) and “all views” metrics (14-day view window).
This way, you don’t lose historical comparisons.
Global Availability by Region
- North America: United States, Canada, Mexico
- South America: Brazil
- Europe: United Kingdom, Germany, Spain, Italy, France, Belgium, Poland, Turkey, Netherlands, Sweden, Ireland
- Middle East: United Arab Emirates, Saudi Arabia, Egypt
- Asia Pacific: Australia, India, Japan, Singapore
- Africa: South Africa
Who Has Access to This Feature?
Advertisers who use reports, reporting APIs, or console views. This includes self-service advertisers, managed service clients, and agencies managing campaigns on behalf of brands.
Technical API Implementation Details
The attribution approach utilized through the Amazon-based ads api is included by default in standard conversion metrics for usage within amazon ads platform for amazon marketplace.
The naming convention when referring to “all views” metrics is in the following format: purchases_all_views, sales_all_views, etc.
The detailed descriptions of each of these fields can be found within the technical documentation of the amazon ads api documentation portal.
The “all views” metrics will be present within the Amazon-retail-conversions metric group with an explicit name indication of “(all views)”.
Podcast Audience Network Integration: Seamless Audio Advertising Through Amazon DSP
Launch Date: January 1, 2026
Amazon Ads added the Podcast Audience Network to Amazon DSP, which lets advertisers plan, run, and measure podcast advertising campaigns along with other digital media campaigns they are already running.
This integration uses Art19’s audience intelligence and Amazon’s first-party data to target premium podcasts more accurately, all from one buying platform.
The Challenge with Fragmented Podcast Advertising
Podcast advertising has been growing quickly, but you have to use different platforms and processes to buy it than you do for other digital campaigns.
Advertisers wanted podcasts to have the same level of targeting accuracy and measurement tools as display, video, and streaming TV.
But systems for buying podcasts didn’t work with programmatic platforms.
This made things more complicated for operations:
- Different ways to log in
- Different dashboards for reporting
- Targeting an audience that isn’t connected
- No one view of how well the campaign is doing across all channels
The integration with the Podcast Audience Network fixes this by putting podcast campaigns right in Amazon DSP.
You can use the same targeting options, creative management tools, and see how well your podcast is doing, along with other campaign metrics.
Key Benefits of Amazon’s Podcast Integration
1. One Solution for Everything.
Control your entire advertising (podcast, display, video & streaming TV) ad inventory through a single interface with one login, a common budget, and unified reporting.
2. Enhanced Targeting.
Combine Amazon’s shopping information with Art19’s podcast data for superior targeting through matching the appropriate podcast audiences with your products.
3. Improved Analytics.
Receive detailed metrics (completion rates, audience demographics, etc.), along with direct links from podcasts to Amazon purchases, much like your other digital advertising channels.
4. Simplified Work Flow.
Your staff can complete their entire workload within one system without having to switch back and forth between different logins, setups, and reports from various systems.
5. Great Shows.
Use well-known, trusted podcasts’ large and engaged audiences to get your message out quickly and effectively.
Where It’s Available
North America: United States
The initial launch focuses on the US market, where podcast advertising spending reached significant scale, and Art19’s publisher network has strong coverage.
Technical Implementation
Podcast campaigns use the standard Amazon DSP API endpoints with audio creative specifications for API users.
\The inventory source parameter tells campaigns to go to podcast inventory by setting it to “podcast_audience_network.”
The API structure for making campaigns is the same as for other audio campaigns.
All of the targeting parameters, bidding strategies, and reporting metrics use API field definitions that are already in use.
There is no need for a separate API integration.
If you already use the Amazon DSP API for other types of campaigns, all you need to do to add podcast campaigns is change the inventory source parameter.
Section-Level Brand Store Insights: Granular Performance Data
Launch Date: January 16, 2026
Metrics Available: As of January 10, 2026
Amazon’s Brand Stores now have section-level performance analytics, which provide you with specific interaction stats for each part of your store.
You may now view how different types of content affect shoppers, broken down by where the traffic comes from.
The Problem It Solves
Previously, brand store optimization depended on page-level performance indicators alone.
This means you could see how well each page performed, but didn’t know which particular area on the page caused the amount of user activity generated from the page.
This is how the optimization process got tricky:
- If a page had low levels of activity, there was no way to know if it was due to the hero image, the product grid, the text content, or the call-to-action location.
- The changes made were based on assumptions rather than actual data.
- You would wait to see if the overall page metric improved, without knowing what specifically worked.
- The process of using trial and error wasted valuable time and ultimately took away some things that may have performed well on the page.
With section-level performance metrics, you will now know exactly how well each hero image creates clicks, how well product grids create activity, and how well text boxes create conversions from visitors.
What Changed Specifically
There is now a new “Sectional performance” tab on the Brand Store insights dashboard. This tab shows the metrics for each section on each page of your Brand Store.
Some of the available metrics are:
Renders: Show how many times Amazon showed a section to customers. Some parts of the page show up right away and are above the fold, while others show up only when shoppers scroll down.
Count the number of times shoppers actually saw the section. Amazon’s rules say that the section must be visible in the browser window for a certain amount of time.
Clicks: Keep track of how people interact with shoppable items in sections. Images of products, text tiles with links, and buttons that tell people to do something all make people click.
Click-through rate: This shows how many impressions that were seen led to clicks. This number shows which parts of the site turn visitors into users.
These metrics seem to be broken down by traffic source, so you can see how paid traffic interacts with sections differently from organic traffic.
Why This Changes Things
Insights at the section level make data-driven optimisation possible.
You don’t have to guess which parts drive engagement; you can see the actual performance data for each section.
This is important because different types of sections have different uses:
- A section with shoppable images should get people to click on products.
- A text tile section could make people stay longer by telling the story of your brand.
- A section for a product grid should make people want to add items to their carts.
You can now make each section work better for its own purpose.
You know the creative needs to be better if a shoppable image has a lot of renders but not many clicks.
You can tell that a text tile is too low on the page if it doesn’t render well.
The breakdown of traffic sources shows how different groups of people act.
Paid traffic from Sponsored Brand ads may act differently from organic traffic from search results.
By knowing these differences, you can make pages that work well for both types of traffic.
Where It’s Available
- North America: United States, Canada, Mexico
- South America: Brazil
- Europe: United Kingdom, Germany, Spain, Italy, France, Belgium, Poland, Turkey, Netherlands, Sweden, Ireland
- Middle East: United Arab Emirates, Saudi Arabia, Egypt
- Asia Pacific: Australia, India, Japan, Singapore
- Africa: South Africa
Who Can Use It
Advertisers with Brand Stores automatically have access to section-level insights. No additional setup or fees required.
The feature works for all Brand Store types, including basic stores, enhanced stores, and stores with custom layouts. Every section type reports performance metrics.
API Implementation
The Stores Analytics API now includes endpoints for retrieving section-level performance metrics. These endpoints follow RESTful conventions and return JSON-formatted data.
The API accepts parameters for date ranges, page filters, section filters, and traffic source filters. This enables programmatic access to section data for custom dashboards or automated reporting.
Rate limits apply to section-level API calls following standard Amazon Ads API throttling policies. Technical documentation provides complete endpoint specifications, request/response formats, and authentication requirements.
Final Thoughts
The new ads for Amazon’s January 2026 are now live. You can use them right now.
Better attribution modeling that takes into account times of discovery. Amazon DSP made it possible to run all of your podcast ads in one place.
Granular Brand Store optimization based on data from each section. It’s all there.
Set up your reporting so that it keeps track of both standard and “all views” metrics. This month, start your first podcast campaign.
Begin optimizing Brand Store sections based on real performance data.
These changes improve how you measure performance, give you more options for buying media, and let you fine-tune Brand Store optimization.
Try them out this quarter. Go into Q2 with plans that have already worked.
January helped you improve your measurements, grow your inventory, and make your optimizations more accurate. Use them.
FAQs
What does the new attribution model mean for the numbers that show how well my campaign is doing?
For Sponsored Brands, viewable Sponsored Display, and Amazon DSP campaigns that run in the Store, you might see changes in the reported Purchases, Sales, and ROAS. These changes are not because of changes in performance, but because of how measurements are made. To keep things consistent with past data, use “all views” metrics.
Can I choose not to use the new attribution model?
No. The last-touch attribution model with the shopping signal automatically works for all campaigns that meet the requirements. You can still compare and report on “all views” metrics, though.
How much cash do you need to start a podcast campaign?
Amazon doesn’t say what the official minimum is, but the minimums that make sense depend on what the campaign is trying to achieve. It could cost $5,000 to $10,000 a month to run awareness campaigns. Don’t just use podcast ads; think of them as part of a bigger audio plan.
How do podcast CPMs compare to CPMs for other types of audio?
The CPMs for podcasts depend on how well the inventory is and how well the targeting is. Premium podcast inventory usually costs more than programmatic audio inventory but less than deals with publishers directly. Expect CPMs to be about the same as those of other high-end audio ads.
How far back does section-level data go?
Starting on January 10, 2026, you can get metrics at the section level. Before this date, there was only historical data at the page level, not the section level.
Can you export data for each section?
Yes. The Brand Store insights dashboard lets you download section-level metrics as CSV files. You can also get section data programmatically with the Stores Analytics API.
Do section-level insights work for all Brand Store layouts?
Yes, section-level metrics show how well all kinds of sections are doing in all Brand Store layouts, even ones that are made just for you.
How often should I look at how each section is doing?
During the first stages of optimization, check the metrics for each section once a week. When performance levels out, switch to reviews every two weeks or once a month. Every three months, do in-depth analyses to find bigger patterns.
Sayali is Director of Revenue Growth at Sequence Marketing Agency, where she specializes in developing data-driven revenue optimization strategies for brands selling across major eCommerce platforms including Amazon, Walmart, and Shopify. Her expertise includes strategic campaign planning, comprehensive market analysis, and cross-functional coordination with creative teams to drive measurable growth and ensure cohesive brand messaging across advertising efforts.