A Practical Guide to Measuring the Lifetime value of Amazon Customers
Many Amazon sellers grapple with the challenge of trying to figure out what the true value of their customers is who purchase their products from the Amazon marketplace. This is an interesting question and a very important one for sellers on the Amazon marketplace to understand. The challenge is that finding an answer to this question is not straightforward. Let us look at some of the reasons why it is challenging.
Amazon provides good reporting capability for sellers who sell their merchandise on the Amazon marketplace. These reports are typically scheduled from the seller dashboard, and the output can be downloaded to a desktop. Generally, a channel manager oversees handling these reports manually, curates the reports to suit internal reporting requirements, and share the curated version of these reports to their leadership teams. If sellers are only selling on a single Amazon marketplace, then it becomes relatively less time consuming to understand and to report regularly to management. However, it is usually not that simple. Let’s look at why.
Amazon also provides various marketing tools for sellers to make the products visible to the millions of users who purchase on Amazon, daily. Amazon has close to seven advertising products all under the umbrella of Amazon advertising. It is not uncommon that sellers use more than two of these advertising products to make their products visible to buyers on the Amazon marketplace. If you look at the Amazon channel holistically for a seller who is only selling on one of the Amazon market places, for example, the US, then they have at least three different data sources from which reports have to be downloaded every day, consolidated and presented to management.
Questions for you:
- Who does this activity for you today?
- Is it the best use of their time?
- If these reports are automated, then what would you have these resources do more often?
- If these reports are automated, would you be empowered to make better decisions?
- If these reports are automated, do you feel that a more efficient channel can be run?
There are many reasons why this consolidation is required.
There are many KPIs that Amazon sellers are interested in. There is a need to understand the
- total sales,
- total sales by products,
- total sales by categories,
- total sales by product variant
- inventory movement at different times of the week/month
- which warehouses should hold what quantities of each product?
- many other sales-related metrics.
In addition to this marketing teams who spend money running advertising campaigns targeting certain keywords and display ads, want to understand:
- the effectiveness of their advertising campaigns
- which keywords perform better?
- what is the right time of the day to advertise for their products?
- what products to advertise based on available inventory?
- what is the ROI of a particular campaign and how does that vary over time and across multiple countries?
- and many others.
Getting answers to some of the questions above or the KPIs listed this is where the reporting provided by Amazon through the seller dashboard or the advertising dashboards may quickly become insufficient even for short-term reporting needs. To understand more deeply about the channel, it is important to get a historical perspective as well as timely data of performance across sales, marketing, product, and customers.
The problem becomes more challenging as sellers expand globally and sell their products in multiple Amazon marketplaces.
|Amazon Marketplace||Seller Central||Sponsored Brands||Sponsored Products||Display Ads/Amazon Media Group|
In the table above we try to highlight the typical Amazon seller who is selling in multiple Amazon marketplaces. The challenge becomes quite evident. There are four seller central dashboards or reports that have to be reviewed every day in addition to the marketing team having to deal with the advertising ROI on each of these channels.
Pictures below highlight a vendor selling products on Amazon Canada and Amazon US and running ads on these marketplaces as well.
The typical workflow involves a channel administrator or a marketer downloading reports after logging in to each of the admin panels multiple times daily, consolidate that data, and share with the management so that the management teams have good visibility into how different channels are performing or supporting their own analysis/work.
Seller central reports from Amazon provides a masked email ID of the customer and their shipping address. In order to calculate customer retention, crucial metrics like retention, repurchase rate, lifetime value, and margins, these reports have to be consolidated not only on a weekly basis but also on data historically as well. Managing weekly or monthly spreadsheets across multiple channels and consolidating them using Excel is a manual exercise which is prone to errors, limited by resource time, not scalable, and lacks the capability that the administrators and decision-makers need to slice this information in different ways to get the data they need about their customers and channel performance.
To tackle the problem of manual reporting, mature Amazon sellers resort to using Amazon MWS APIs to automate the extraction of data of sales and marketing performance, consolidate the data to a central data warehouse like Snowflake or Google BigQuery. Amazon APIs are notorious for their throttling and are very challenging to build, maintain, and support. Programming skills are required to build and maintain these APIs which may not be readily available with many Amazon Sellers and even if they were, certainly not the best use of time and money. Even when these APIs are built out, to the surprise of many sellers, they find that Amazon doesn’t provide personally identifiable (PII) information. PII data is critical to understand customers better and key customer metrics like lifetime value, retention rate, repurchase rate, product affinity and others.
This is a two-part problem.
- A significant amount of time is spent just reporting on channel performance which takes away time from an expensive resource every day who would rather do analysis on the Amazon data rather than spend time getting access to the data.
- Lack of consolidated Amazon performance data limits sellers from performing an in-depth analysis of each channel/market and its performance.
The solution to both the problems listed above is automated consolidation of Amazon sales and marketing data into a centralized data warehouse and automated reporting. Automating the extraction of data from Amazon seller central and various Amazon ad channels enables automation of reporting to be built and delivered to the stakeholders and operations executives. There is an immediate benefit to automating these reports because these reports are refreshed every hour with the latest data from Amazon so that decisions can be made in a timely manner based on data that is up to date. However, for in-depth customer analysis, the challenge remains because of the lack of PII data in the Amazon MWS APIs. There a workaround for this which involves automation at its core and quarterly manual intervention to get to the bottom of questions regarding the customer base.
Our product, Daton, helps you extract data from all your Amazon seller central dashboards and advertising channels and replicates the data to a centralized data warehouses without any manual intervention. It is easy to set up, starts at $20, and enables you to own your Amazon marketplace data.
The channel metrics like the ones discussed above, can be fully automated once and for all so that these metrics are available in the dashboard that you can review and understand in greater detail. Talk to us on how customers are solving the lifetime value challenge and see how you may be able to set processes in place to get to know your customers better. We will help you with the automation and the quarterly manual intervention that is required for this exercise. The skills that are required to be able to do this on your own are SQL, Python, and knowledge of using a BI tool like PowerBI or Grow.com. We can guide your teams on how this can be done or if you don’t have the resources, we will build it out for you. Reach out to us at firstname.lastname@example.org to get a step-by-step guide on how you can do it yourself.