The ultimate guide to analysing Amazon data holistically

Atom11 presents the ultimate guide to holistically analysing Amazon data, enabling businesses to unlock actionable insights, optimize strategies, and achieve sustained growth on the platform.

Mar 11, 2024

analysing Amazon data
analysing Amazon data

For businesses, understanding Amazon data is imperative for staying competitive and optimising performance. However, it is not easy to navigate 150 reports from seller central, vendor central and advertising data. In this post, we will provide a comprehensive guide to analysing Amazon data holistically, covering various aspects from sales metrics to customer reviews and competitive intelligence.

Understanding Amazon Data:

Amazon provides abundant data through its Seller Central and Vendor Central platforms, as well as through third-party tools and APIs. These data points can be broadly categorised into sales metrics, operational metrics, customer feedback, and competitive intelligence.

First, let’s go through all the data that Amazon provides. In section 2 of this post, we will talk about 3 ways in which amazon ad automation softwares brings this data together.

Part 1: Amazon metrics:

Sales Metrics:

Sales metrics are required to assess overall performance and growth of an account. Key metrics include:

1. Sales Revenue: Total revenue generated from product sales.

2. Units Sold: Number of units sold over a given period.

3. Average Order Value (AOV): Average price at which products are sold.

4. Sales by Product Category: Distribution of sales across different product categories.

Operational Metrics:

Operational metrics provide insights into the efficiency of various processes and can help identify areas for improvement. Examples of operational metrics on Amazon include:

1. Inventory Levels: Quantity of stock available for each product.

2. Inventory Turnover: Rate at which inventory is sold and replaced.

3. Fulfilment Metrics: Measures of order fulfilment performance, such as order defect rate and late shipment rate.

4. Advertising Metrics: Performance metrics for Amazon advertising campaigns, including ad spend, click-through rate (CTR), conversion rate, and Advertising Cost of Sale (ACOS)

Customer Feedback:

Customer feedback is crucial for understanding customer satisfaction and identifying opportunities for product improvement. Key sources of customer feedback on Amazon include:

1. Product Reviews: Written reviews and ratings left by customers.

2. Seller Feedback: Feedback left by customers regarding their experience with a seller.

3. Customer Questions & Answers: Questions asked by customers and answers provided by sellers or other customers.

4. Customer Service Metrics: Metrics related to customer service interactions, such as response time and resolution rate.

Competitive Intelligence:

Analysing competitors' performance and strategies is essential for staying ahead in the competitive Amazon marketplace. Key aspects of competitive intelligence include:

1. Competitor Pricing: Analysis of competitors' pricing strategies and price positioning.

2. Competitor Sales Metrics: Assessment of competitors' sales performance, including revenue, units sold, and market share.

Analytical Tools and Techniques:

To effectively analyse Amazon data, atom11 provides 3 important levers that brands can use:

1.   Analytics dashboard: The analytics dashboard is a unique combination of sales and operational metrics.

Let’s take a sneak peek:

Amazon advertising campaigns

The following dashboard helps you analyse time series trends on 23 parameters including total sales, total orders, inventory day on hand, inventory units on hand, AOV, best seller rank and all ad metrics.

In the following image, you can see that 1$ increase in price led to a 50% drop in sales for this product. This information saved precious time from the brand and agency, to fix the right issue (i.e. pricing) rather than solving and optimising advertising performance.

amazon advertising optimization

Similarly, brands have used this dashboard to find the right root cause of sales fluctuation rather than obsessing over advertising optimization.

 An extension of this dashboard is the compare tool, where customers can select 2 time periods and compare data from 28 different parameters.

 2.   Alerts: Looking at data is a deep dive activity that teams do once a week. But what if you were to get alerts daily notifying you of sales fluctuations. Using these alerts, teams can directly spring into action and take corrective action. Rather than spending time figuring out what to do.

Alerts help you prioritise which ASINs to take action on.

The best part – you can set up alerts the way you want and they get delivered right to your email every morning!

amazon ad automation softwares

3.   Refreshable google sheets: Fortunately, or unfortunately most reporting in the Amazon world happens on google sheets. Agencies want to create custom reports for their advertisers, and brands/ sellers themselves use google sheets or Looker studios to create custom reports.

Atom11 provides custom refreshable reports for data in any format.

Luum, a brand aggregator and agency mentioned, “Having these refreshable sheets have been critical to our agency strategy. It has reduced our time to reporting by 2-4 hours a week. We are now able to focus on building advertising strategies rather than building reports. Game changer”

Best Practices for Holistic Analysis:

To derive actionable insights from Amazon data, businesses should follow these best practices:

1. Set Clear Objectives: Define specific goals and objectives for the analysis to ensure focus and relevance.

2. Use Multiple Data Sources: Combine data from multiple sources, including Amazon's own data and third-party sources, for a more comprehensive analysis.

3. Contextualize Data: Consider external factors such as market trends, seasonality, and competitive landscape when interpreting data.

4. Iterate and Refine: Continuously iterate on analysis methodologies and refine strategies based on insights gained.

5. Collaborate Across Teams: Foster collaboration between different teams within the organisation, such as marketing, sales, and product development, to leverage diverse perspectives and expertise.


Analysing Amazon data holistically is essential for businesses looking to thrive in the competitive e-commerce landscape. By leveraging sales metrics, operational metrics, customer feedback, and competitive intelligence, and employing analytical tools and best practices, businesses can gain valuable insights to optimise performance, drive growth, and enhance customer satisfaction on Amazon. As the e-commerce landscape continues to evolve, mastering the art of holistic data analysis will be critical for maintaining a competitive edge in the marketplace.