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How to Improve Your Amazon Customer Analytics in 2022

Are you looking for strategies to master your Amazon Seller data analytics? Follow these 5 steps and you'll improve your customer analytics this year.

Daniel Durling

Last updated:
February 25, 2022

Amazon Sellers have long been looking for new strategies to deal with the changing landscape that is selling on Amazon. Last year, most advertisers began prioritizing top-of-funnel campaigns to reach new-to-brand shoppers, leading to an increase in brand purchases of 36%. 

The lesson here is this: understanding your business performance — what it is and where you can gain growth — is crucial to developing winning strategies and staying ahead. That's where customer analytics come in. To help you improve your customer analytics, we will take you through the critical steps needed to master the art, including how to get them, what to look for, and how to channel the derived insights into your future strategies.

Suggested reading: Add to your knowledge of Amazon analytics with our eBook Mastering Amazon Brand Analytics.

Step 1. Get updated with Selling Partner API

You need to look no further than Selling Partner API for evidence of Amazon's constant updates and innovation. SP-API is a suite of API-based automation for Amazon Sellers (and even Vendors) and evolves Amazon Marketplace Web Service (Amazon MWS) APIs. These have offered Sellers programmatic access to Amazon features for more than 10 years but are now getting a little long in the tooth.

SP-API offers all Selling Partners and third-party developers several improvements over Amazon MWS, such as JSON-based REST API design standards, OAuth2.0 selling partner authorization, and a test endpoint — the most requested feature in MWS. In the future, all new API functionality will be built in SP-API, with updates to MWS only to support business-critical changes.

SP-API is deployed to automate data flow further and sell more efficiently. It automates manual processes. It can also give access to insights and predictions regarding consumers' purchase intentions to optimize advertising expenses and stay ahead of the competition — but only if you understand the data and have the tools to exploit it — more on that later.

Step 2. Find out what data you need

Even with Amazon becoming more open with its data, there are still gaps in data visibility that you have to deal with from selling on Amazon. Amazon has not provided much useful customer data to its Sellers, leading to many having to use tactics outside of Amazon to gather customer information. However, that is improving thanks to tools such as Demographics within Brand Analytics.

But there is still a lot to be desired when Amazon presents customer data to Sellers from within their in-house tools. Prioritizing the customer aspect of each set of data is crucial to decide what works and what doesn’t in your existing strategies, and how you can amend them to drive greater growth.

Step 3. Develop your analytics approach

Sellers on Amazon can quickly become overwhelmed with the volume of data involved, the number of sources and reports on Amazon, and the need to balance quantitative and qualitative insights.

It's not enough to gather data — you need to analyze that data to form insights into business performance and potential competitive advantages. Unfortunately, Amazon Seller Central provides just the data, not the insights.

However, there are some clever ways to build up a clear picture of your buyers on Amazon. Our own tool Nozzle is a prime example of advanced customer analytics software combined with a range of Amazon reports to give you a detailed view of customer behaviors and buying intentions. You can also use tricky techniques such as exploiting external platforms such as Facebook to originate some of your Amazon traffic and harvest data from the resulting sales.

Either way, third-party analytics solutions such as Nozzle can really help you maximize the value of Amazon data.

Such analytics tools stitch together data horizontally across silos to provide a holistic customer view. Advanced data analysis, typically using AI and machine learning, can quickly find insights across many customer journey paths and help prioritize the most promising sales journey. You can now test a variety of approaches in near real-time to determine which combinations yield the best sales results.

Step 4. Make informed business decisions

Analytics enable you to reassess your existing approach and develop innovative and lucrative future strategies. By linking improvements, new sales, new-to-brand customers, repeat purchases, and customer lifetime value (CLV), you are suddenly making business decisions that actively help you grow.

Looking at which marketing campaigns are most effective at turning in-store customers into repeat, online customers will help you develop promotional top-of-funnel campaigns to increase engagement, improve loyalty, and contribute to building long term customer relationships.

Your analytics solutions will now be shaping advertising, keyword and content strategy based on a combination of customer behavior, journeys, and historical data. You need to move beyond personalizing the early stages of the customer life cycle to orchestrating actions across the entire customer life cycle (acquisition, engagement, and retention of your customers.) 

For example, a particular customer persona may be a repeat purchaser, and you might use targeted offers and coupons to keep them coming back. However, if their purchase frequency slowly decreases (a soft churn), it will likely lead to an eventual stop. By recognizing this subtle trend, your marketing can kick in to get those customers back on board and prevent a loss of revenue.

Step 5. Use the best analytics tool you can find

Having the right data and insights is vital to customer analytics. But they’re not enough on their own. You can make fundamental business decisions by understanding critical metrics like lifetime value, retention rates, and customer acquisition costs.

Look for tools that improve:

  • Customer Acquisition: To understand the actual value of your customers and optimize your marketing.
  • Customer Lifetime Value: To discover how your customer data can keep you ahead of your competition.
  • Growth Opportunities: To unlock new areas of business or even new sectors.

To execute at scale, you will also need a tool that supports the right skills, governance, and the right way of working to help you become really customer focused.

The most practical and efficient way to improve customer analytics is to invest in an analytics tool like Nozzle. We analyze vast amounts of data, draw helpful insights, and generally make your selling experience on Amazon more efficient, more effective, and better informed.

Pro tip: There’s a huge variety of analytics tools out there so get up to speed with what they are and which are worth investing in. Our blog 4 Types of Amazon Analytics Tools and Are They Worth It? goes more in depth on that.

Data is key to improvement

Data-driven decisions are the long-term solution to improving customer analytics. They enable you to develop a fundamental understanding of customers in the long run.

Nozzle offers unique data analysis software to assist you and your business. We deliver in-depth insights, a richer understanding of your customers, better advertisement delivery and optimization, and even tailor-made business solutions.

You will find that we are focusing on areas no one else touches and provide data other sellers didn't know existed. We use technology in a very deliberate and thoughtful way, always with the aim of improving your business and your experience while also understanding your need for transparency and insights to help you (and your customers) win on Amazon. To see exactly how we do it — why not take a 14-day free trial?

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