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How to use Amazon Brand Analytics in 2020

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Amazon Brand Analytics (ABA) is a treasure-trove of customer, competitor and keyword insight for an Amazon Seller. As of April this year, it’s now also where ‘Brand Registered’ Vendors need to go in order to access the same information — replacing Amazon Retail Analytics (ARA) Premium.

The move for Vendors used to ARA Premium isn’t huge, although it does come at a cost savings of over $30k per year. The reports are basically the same, just a few naming conventions have changed. For Brand Registered Vendors who previously only had access to ARA Basic, the shift is far more substantial — the same goes for any Seller or Vendor just getting to grips with the Amazon ecosystem.  

Ultimately, ABA is pretty straightforward to access, but far more complicated to put to good use. The information provided is siloed across different reports, and pulling the context required to actually transform the data into actions with positive outcomes is more complicated than simply logging in.

Here, we are going to provide a crash course on ABA basics in 2020 — helping you gain a foothold on how to access the platform and what to do with the information it provides.

Once you read this guide, I suggest downloading our free eBook on Master Amazon Brand Analytics to go beyond the basics and get the most out of the platform this year.

Where can you find Amazon Brand Analytics?

Let’s get the basics out of the way. 

You can find Amazon Brand Analytics under the Reports tab in Seller Central or Vendor Central. 

In order to access the Amazon Brand Analytics tool, you have to meet two eligibility criteria: 

  1. Be accepted to the Amazon Brand Registry program. This is free, although requires meeting several criteria that may cost money. Primarily, it means holding a registered trademark in the territory in which you sell. You can find a full list of eligibility criteria here
  2. You have to have a registered Vendor or Seller account on Amazon — this one is pretty straightforward.  

What is Amazon Brand Analytics?

ABA is a reporting tool that gives you insights into Amazon customer behavior, your competitors, and overarching search trends. This information is presented as averages, rather than specific transactions.  

Data is generally available in Brand Analytics within 72 hours of the close of a given period. Data is stored for one year. If you want to look at seasonal trends or long-term trends, you will need to export and archive the information. You can also use third-party analytics tools — something we will get back to. 

ABA data is delivered in four separate reports: 

1. Amazon Search Terms: 


This report tells you search frequency rank (SFR) — the comparative ranking of search terms by volume. You can also see the top three ranking ASNIs for each term, and the click share and conversion share that each has.

  • Click share is the percentage of total clicks that a given ASIN receives for a search term. 
  • Conversion share is the total percentage of sales a product makes compared to total sales for that term. 

Why this is useful: This report is the core of ABA. SFR helps you identify consumer trends — indicating which items are the most popular on Amazon, and which terms are most commonly used to search per category. It also helps you identify your main competition for different terms, and conversion share and click share help you determine how competitive the market is. You can search this report by search terms or by ASIN. Doing both will help you find competitor patterns. 

 

2. Market Basket Analysis: 


This report shows you what other items are being purchased alongside your products. It does this by showing you the other items that customers have in their check-out basket alongside yours.

Why this is useful: This report gives you a snapshot of comparative consumer behavior — helping you identify the other types of products that your customers also buy. This might give you ideas for Sponsored Brand or Sponsored Product ads. It can also help you create bundles. However, to be honest, this is a pretty ‘noisy’ report. People keep items in their basket for many reasons, sometimes with no intention of making a purchase. 

3. Item Comparison and Alternate Purchase Behavior: 


This is a single report, but it’s split into two categories. Item Comparison shows you the top five items customer’s view after viewing your product. Alternative Purchase shows you the top five items a customer purchases after viewing your item. 

Why this is useful: This report is similar to the Market Basket Analysis Report, but arguably more targeted — removing the ambiguity about how long that item may have been in that basket. The most common use of this information is to determine other products to target with ads. It might also reveal items within your catalog that are often purchased together — giving you ideas for bundles. 

Note: The Alternate Purchase percentages are of the total number of shoppers who went on to make a purchase. For example, if 100 people view your item and only one goes on to make a purchase, that will register at 100% (rather than 1%) for that item in the report.  

4. Demographics: 


This report gives you key demographic information about your customers. This includes gender, average number of orders, household income, education, and more. This is average information, and is also segmented by accounts, not actual individuals — so, multiple people using one account can skew the data. However, brands with D2C channels can cross-reference this information, allowing them to improve the demographic accuracy of both data sources.  

Why this is useful: By better understanding your customers, you can tailor your strategy on a broad-level to match. Demographics information can help you identify new product opportunities that might resonate with your audience, or better personalize Sponsored Brand Ads, including videos, images, and headlines. For example, if you know all of your customers are seniors, using older people in your lifestyle photography can help you better connect with your average buyer.  

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Putting ABA information to good use 

Data is great, but you need to be able to take informed actions using that information if you want to transform data into a competitive advantage. This is where ABA struggles the most. The reports provide a detailed picture of search trends and customer behavior, as well as your competitors. However, it doesn’t provide much in the way of context about why different brands and ASINs are doing well. 

What you really need to know is information about the products that surface in the Search Terms Reports and Alternative Purchase Reports. Unfortunately, the only way to get this information is to look it up yourself. A critical manual step to transforming ABA data into actions is downloading the reports as CSV. files and augmenting it with data points about ASIN star rankings, delivery times, listing types, and comment histories. This type of context can tell you where you need to improve in order to compete. 

The challenge here is time. Building these spreadsheets takes time, and they begin to go out of date as soon as they are finished. A better option is to turn to analytics tools that can pull this information automatically, providing you the ready-made context you need to take action. These same tools can also pull transactional data from Amazon MWS, helping you build specific CLV calculations and buying trajectories. However, if you want to get into this detail, I suggest checking out our eBook.

The future of Amazon Brand Analytics

As Amazon comes under more regulatory pressure, Amazon will be more likely to provide greater access to its customer data. Some of these capabilities, such as Repeat Purchase Behavior, which had already been available only to Vendors, are now appearing on Seller Central — more are likely to follow.

These rollouts have usually been made available with little-to-no fanfare, and on a region-by-region basis. As Amazon rationalizes its platform for Sellers and Vendors, it’s likely that this piecemeal release process will continue. But, as we’ve seen, it’s only when the data provided in such reports is  “joined-up” that you start seeing its true value. 

Having the right data is vital for customer analytics, but it’s not enough on its own. To execute at scale, you will also need to look for the right skills, governance, and the right way of working.  Analytics tools are needed to combine data across channels, touchpoints, and systems along the customer journey. That is the way to gain the holistic insights needed to stay ahead of the competition and have time to actually act on that information.  

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