How to improve your Amazon customer insights analytics in 2021

Understanding customers and customer purchase journeys is critical. The ongoing health crisis, with Amazon prioritizing on fulfilment of high-demand products, and the consequential economic stagnation only highlight the importance of data-driven decision-making. If you are a Seller on Amazon, improving customer analytics should be a top priority in 2021. 

Amazon is known for not providing large volumes of customer data to its Sellers, forcing brands to use tactics outside of Amazon to gather information on their customers. That’s changing, with tools such as Demographics within Brand Analytics. But there is still a lot to be desired when it comes to how Amazon presents customer data to Sellers within their in-house tools. 

You have to be very careful when dealing with Amazon to abide by its rules of customer engagement — or face the consequences of suspension or even termination of trading. Amazon’s Data Protection Policy makes it clear that it only allows developers to use customer information for tax and shipping purposes, not for advertising.

But there are ways to build up a picture of your buyers on Amazon. One is to use customer analytics software to combine a range of Amazon reports to give you a surprisingly detailed view of customer behaviors and buying intentions. The other is to use external platforms such as Facebook to originate some of your Amazon traffic and harvest your data from resulting sales. Here, we are going to explore both options. 

Reaping the benefits of Amazon MWS 

Connecting to the Amazon Marketing Web Services (MWS) is crucial to automating your Amazon Seller Central Account and making the most of the data provided to you. It’s the only source of transactional data from Amazon, apart from downloading multiple spreadsheets and reports.  

MWS is an integrated web service API. It’s what enables Amazon Sellers software to automatically exchange data on listings, orders, payments, reports, and more. This is also where most third-party tools get their transactional data to be able to provide their analytics services.

MWS helps Amazon Sellers answer two key questions about customers:

• How do I improve my Amazon customer analysis beyond what Amazon allows me to have?
• If more than half of shoppers start their journey on Amazon, how can we reach the other half on channels such as Google, Facebook, and Instagram?

Let’s start with the analytical question first.

Making the most of analytics solutions 

Third-party analytics solutions can really help you maximize the value of MWS. Sellers on Amazon can quickly become overwhelmed due to the volumes of data involved, the number of sources and reports on Amazon, and the need to balance quantitative and qualitative insights. 

Analytics tools stitch together data horizontally, across silos, to provide an integrated view of the customer. Advanced data analysis, typically using AI and machine learning, will find insights quickly across many variations of the customer journey and help to prioritize the most promising sales journey theories. It enables Sellers to test a variety of approaches in near real-time to determine which combinations will yield the desired sales results.

Sales impact 

With customizable dashboards, you can monitor the impact of improvements on a variety of sales and advertising key performance indicators (KPIs). By making a link between improvements, new sales, and new-to-brand customers, repeat purchases and customer lifetime value, you will be able to prove the value of your advertising spend. 

For example, by looking at which marketing campaigns are most effective at turning in-store customers into repeat, online customers, you can look at what promotional campaigns most increase engagement, improve loyalty and contribute to building long term customer relationships. 

Analytics solutions can now shape advertising, keyword and content strategy based on a combination of customer behavior, journeys, and historical data. While some platforms use orchestration to personalize the early stages of the customer life cycle, those that stand out are able to orchestrate actions across the entire customer life cycle (acquisition, engagement, and retention of your customers).and establish workflows to support this.  

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 is slowly decreasing (what banks call 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.

Geographies

Analytics solutions will help find high performing cities/regions and replicate successful marketing tactics. They will also identify constant under-performers to adjust your strategy.

Personas

Most brand decisions should stem from a deep understanding of customers — how their preferences change over time and how their behavior evolves with their preferences.

By creating customer personas across product categories, you can take action to better engage with customers, potentially using more specific language or phrasing to drive more targeted ads and communication.

Customer journeys 

The purchase funnel is a journey and you can leverage analytics solutions to better understand your customer shopping behavior. Market Basket Analysis will identify which products customers are comparing your products to and what they ultimately buy. This should make it easier to identify bundling opportunities.  

If you can quantify your customer lifetime value (CLV), you can identify which products lead to higher value product sales in the future and potentially adjust marketing spend to focus on higher CLV products.

Reaching beyond Amazon

There are several reasons to look beyond Amazon for customer analytics data. One practical reason is that it appears that Amazon’s algorithms look favorably on you generating traffic from outside Amazon. It does seem logical for Amazon to want traffic from trusted large platform sites to go to Amazon listings, and Amazon’s algorithm seems to reward that. 

Another compelling reason is the “eggs in one basket” problem. It might be surprising, but there are online shoppers that don’t use Amazon, and depending wholly on a single platform comes with dangers. 

The third reason is the issue of ownership over customer data. If you are originating sales on Facebook or Google, and then moving completion to Amazon — you have customer data from the beginning to the end of the process and can analyze the complete journey. The recent offerings from Amazon attribution will aid this process. For example, if you have, or can create an existing customer list from your own ‘.com’ site, you can join that data set to MWS data, fill in the gaps and improve your data.

The final reason is to capitalize on some of the advances on platforms such as Facebook. For example, messaging bots could be a gamechanger for your customer targeting and analytics.

Facebook platform

In 2015, mobile messaging apps overtook social media use. If you “speak” to your prospects on Messenger and send them to Amazon to make the purchase, once they’ve made the purchase, they trust you as a brand and you have valuable customer data.

The emergence of chatbots

The ecommerce landscape is changing at a fast rate, and messenger bots on Facebook are an interesting development. Messenger bots can send a daily automated message which could, for example, be an offer with a link to your Amazon landing page. 

The possibility of 27% of US adults buying basic products through a chatbot is enticing, especially with 13% buying an expensive product. It would also mean that Amazon Sellers who want to reduce their dependence on Amazon exclusively can turn to Facebook chatbots to achieve this — allowing them to own the customer journey and the resulting data.

There are still restrictions that apply on how you use ads on Messenger, and Facebook has now put more checks in place — you need to apply for permissions from Facebook to implement these messages. But if that reduces spam and the misuse of the channel, then it is potentially a good thing in the long run for retailers. 

Collect data, but tread carefully

Customers’ privacy is a big issue, and that’s a trend that’s only likely to grow. In data protection terms, Amazon acts as a data controller of any customer personal data collected via its services. According to Amazon’s terms, Sellers may not use any such customer personal data (including contact information) for any purpose other than fulfilling orders or providing customer service in connection with a Service. Make sure you understand what data you are harvesting, and why.

Amazon as a platform risk

You may get to the stage where it is essential to control the destiny of your own business. For that, you need to own your customers and your customer data. If you learn how to effectively drive traffic, then you start to have the option to send your customers wherever you want. 

Amazon is slowly restricting the ways that you can communicate, the language that you use, and how frequently you communicate through the buyer-seller messaging platform. It’s natural that Amazon wants to protect the credibility of its brand — especially when it is under regulatory pressure. At the same time, it doesn’t make it easy for Sellers to communicate and build relationships with customers.

Moving forward

Having the right data and insights is vital for customer analytics. But it’s not enough on its own. Analytics tools are needed to combine data across channels, touchpoints, and systems along the customer journey. With the right toolset, you will be able to build customer profiles and understand how to best provide for your customer demographics. But to execute at scale, you will also need to look for the right skills, governance, and the right way of working to become really customer-focused. 

Now, more than ever, brands need to connect with customers and deliver value as a brand. Understanding customer data is key.