E-Commerce Metrics & Reporting Guide

This guide intends to provide entrepreneurs with an understanding of the data necessary to scale any new e-commerce venture. To download the PDF version of this guide, click here.


- Step 1: Choose a few dimensions to segment your data

- Step 2: Track key metrics (segmented by dimension)

- Step 3: Use impactful reporting tools to uncover valuable insights

1. Segment the Data by Dimension

Traffic Source/Campaign

How users came will influence their behavior. Also, metrics will differ by why users came in (offer- based vs sale, etc.). Tracking by source will also help to minimize Cost of Acquiring Customer (CAC).


To track seasonality and trend initiatives. Weeks (or groups of weeks) work best. Day of week tends to have too much volatility. Months vary in length and have arbitrary start/end dates.


The device type (e.g. desktop vs mobile vs tablet) and screen size can have a major impact on many key metrics.

Product Category

Segmenting by product or product type can help you better understand metrics like Customer Satisfaction, Churn & Repeat Purchase Rate.


Segmenting users by join date (e.g. when users made their first purchase, subscribed or created an account) helps you identify trends over time, and measure the impact of changes in your business. You would typically group customers in cohorts by month or year, and compare cohorts by metric & number of periods elapsed.


Segmenting customers & sales by geographic location or demographics can offer some high-level context.

2. Track Key Metrics (segmented by dimension)

Average Order Value (AOV)

This is the average dollar amount for each order on your store. Many e-commerce businesses focus on growing revenue by increasing purchase volume, but focusing on average order value is equally important. If most of your orders are really small, that means you have to get a lot more people to buy in order to achieve your target.

Average Order Value =   $ Sales
# of Orders

A similar, but equally important metric is Average Order Profit (AOP). Tracking AOP will show you if your customers are placing orders with low or high profit-margins.

Average Order Profit =   $ Sales - Cost of Goods Sold
# of Orders

*AOP does not consider marketing or customer acquisition costs -- that information is represented in the Lifetime Value and Marketing ROI metrics.

Conversion Rate

Shows how efficient your website is at "closing the deal" -- adding to cart, registration, checkout, payment or subscription.

Conversion Rate =   # Sales
Visitors to Site

Cost of Acquiring Customer (CAC)

Shows how efficient your website is at "closing the deal" -- adding to cart, registration, checkout, payment or subscription.

CAC =   Acquisition Spending
# Customers Acquired from Mkt Campaign

Customer Lifetime Value (CLV)

CLV is a measure of profit, so it can help you determine how much you are willing to pay to acquire a customer, knowing that you can make up the money within a given time period.

Customer Lifetime Value (CLV) = Average Profit per Customer - Cost of Acquiring Customer (CAC)

Average Profit Per Customer =   Average Order Profit (AOP) x Total # of Orders
Total # of Customers

CLV is significant because it's more cost effective to keep an existing customer than to acquire a new one. Once a customer is acquired, you want to influence them to keep buying.

Marketing ROI

Marketing ROI =   Customer Lifetime Value (CLV)
Cost of Acquiring Customer (CAC)

Many companies calculate their return on investment on a single sale (AOP / Average COGS). Instead, the ROI should be focused on the lifetime value of the customer. It's the most accurate measurement of a customer's economic worth for the company.

Churn Rate

Percentage of customers who don't make a repeat purchase.

This is also measured by its opposite value, Repeat Purchase Rate.

Customer Satisfaction Rate or Net Promoter Score

Feedback requests and surveys are good ways to hear firsthand from the customer. To determine your Net Promoter Score, ask "How likely is it that you would recommend your company to a friend or colleague?" Customers respond on a 0-to-10 point rating scale and are categorized as Promoters, Passive or Detractors.

Net Promoter Score   =   % Promoters   -   % Detractors
  =   9s and 10s   -   0 through 6s

CLV is significant because it's more cost effective to keep an existing customer than to acquire a new one. Once a customer is acquired, you want to influence them to keep buying.

3. Uncover Critical Insights

Measure the (Customer Acquisition) Funnel

For e-commerce sites looking to scale, it's important to understand the costs of acquiring new customers. However, new customers may reach your site from many different sources, so measuring these costs at different points in the acquisition funnel can help drive down costs. In addition to Cost of Acquiring Customer (CAC) and Conversation Rate, other key metrics to consider are Click Through Rate and Shopping Cart Abandonment Rate.

Each campaign is different. A Google Adwords campaign might look like this:

Impressions >> Clicks/Visitors >> Shopping Cart >> Sale >> Repeat Purchase

Similarly, a paid email campaign might begin differently:

Emails Sent >> Opens >> Clicks/Visitors >> ...

For each campaign, keep track of the data points along the funnel and use them to calculate other cost metrics along the way. For example, Cost Per Impression (CPI), Cost Per Click (CPC), and Cost Per Visitor.

This sort of analysis will help you identify your most important channels for driving revenue and acquiring new customers to scale more effectively.

RJ Metrics

RJ Metrics is a great metric tracking tool for e- commerce sites.
The RJ Metrics platform lets you import your data from a wide variety sources & gives you the tools to understand key metrics & segmenting dimensions.
RJ Metrics is a powerful tool that supports many large e-commerce sites, but they also negotiate plans for new e-commerce startups that may still have little to no revenues.

Cohort Analysis

Cohort analysis is an incredibly useful tool to understand how your business strategy has changed over time. Below is an example from RJ Metrics of repeat purchase data segmented in cohorts by month joined.

Sources used in this guide


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