eCommerce Analytics: The Only Authoritative Guide


Whether you’re selling via Shopify, BigCommerce, Magento, Salesforce Commerce Cloud, or another eCommerce platform, it’s essential to have a granular understanding of all data across your brand. 

In short, you must be able to run eCommerce analytics.

But with so much data available from different sources and a huge variety of metrics to track and measure, it can be overwhelming to figure out your CAC, CPC, LTV and LYZ (okay, we made that one up). 

In this guide, you can find the eCommerce metrics that matter most, and how to use them to make informed business decisions.

What is eCommerce Analytics?

eCommerce analytics is the centralization, normalization, and analysis of data from all areas of an eCommerce business, including operations, marketing, customer behavior, and sales. By tracking both high-level trends and granular details, businesses can evaluate the health of the business, and learn how to optimize and drive further growth. 

The goal of eCommerce analytics is to gain insights into the past and present performance of the business, understand customer behavior, and identify areas for improvement. You can then use these insights to ensure important decisions, like marketing spend and campaign strategy, are rooted in evidence.

Setting up Google Analytics 4 (GA4) for eCommerce Analytics

GA4 provides a wealth of insights on shopper behavior across the customer journey. GA4 makes it easier than ever to track users and their interactions, known as events. This can help you make better-informed decisions to optimize your marketing and sales strategies.

Getting set up can take some time, but don’t worry, we have got you covered. Check out the steps below to get started or read our complete guide to GA4 for the full walk-through.

Daasity Pro Tip: If you're a merchant on Shopify, it’s easy to connect your Shopify store(s) to GA4 via the new GA4 integration.

1. Set up Google Tag Manager (GTM)

GTM is a tool from Google that lets you add tracking tags to your site. Basic installation is simple. Create a GTM account if you don’t have one already. Then, set up a “container” for your website, which creates a unique Javascript snippet. Then add the snippet to the pages of your site and check it’s working. 

2. Set up your eCommerce data layer

A dataLayer is a javascript variable that exists in the background on your webpage. Your website sends information to the dataLayer, which Google Tag Manager can extract and use to fire Google Analytics or marketing tags.

Setting up the dataLayer can be tricky, but many eCommerce platforms have plugins, apps, and pre-built code templates to create the dataLayer for you. For Shopify, Elevar can help.

3. Set up your GA4 account & property

If you are new to GA, you’ll need to create an account to set up your first GA4 property. If you already have a Google Analytics account, you just need to create a new GA4 property within that account. 

4. Set up eCommerce tracking

The next step is to start setting up the tags. Tags like view_item, which fires every time a user views a product detail page, or add-to-cart, which is triggered whenever a user adds an item to their cart, enable you to track interactions on your site. Don’t forget to conduct extensive testing to ensure the tags are firing as expected so your data can be tracked correctly.

Types of eCommerce Analytics

eCommerce analytics is a broad topic and encompasses all aspects of the customer journey as well as different areas across the business, such as:

  • Customer Acquisition
  • Customer Retention
  • Subscription
  • Merchandising
  • Operations
  • Paid Media
  • Customer Behavior
  • Onsite

Keep reading to dive into the most important metrics for each category and why you need them. You’ll also find three fundamental guiding questions that every brand should be able to answer under each analytics category. 

If you can’t, it's time to dig deeper into your data or consider investing in an eCommerce analytics solution to ensure you’re getting the full value out of your data. 

Customer Acquisition 

Winning new customers is essential to business success and growth. A good understanding of your customer acquisition data will help you answer fundamental questions, like:

  • How expensive are our customers to acquire by channel?
  • Based on acquisition costs, how much growth can we afford to drive for our brand?
  • How long does it take to recoup our investment in acquiring customers?

The right metrics will help you gain insight into the performance of your customer acquisition efforts so you can figure out which channels and strategies are working best for your brand. 

There are many metrics you can use to measure customer acquisition. Let’s take a look at some of our favorites. 


Cost per acquisition (CPA) is one of the most fundamental eCommerce KPIs as it calculates how much it costs you on average to gain one new customer. This helps you understand and compare the cost-efficiency of different acquisition channels and their development over time, and determine how much growth you can expect with your marketing budget. 


Although CAC is often used interchangeably with Cost per Acquisition (CPA), they are different metrics. CPA refers to the variable marketing cost to acquire a new customer, whereas customer acquisition cost (CAC) refers to the variable marketing cost and includes other costs such as tools, ad vendors, team salary, and agency costs (if applicable).


LTV:CAC (or CLV:CAC) is the ratio of your brand's customer lifetime value (average gross margin per customer over their lifetime with your brand) and your customer acquisition cost (how much your business spends, on average, to acquire a new customer).

The ratio of customer lifetime value to how much you spend to acquire a customer is one of the most important acquisition metrics. It indicates whether your business is earning enough money to offset your acquisition costs over time, which says a lot about the profitability, growth potential, and overall health of your business. 

Customer Retention

Customer loyalty and retention are essential for any business. It is usually significantly more cost-effective to keep an existing customer happy than to acquire a new one. Additionally, high-value customers tend to spend more money, advocate for your brand, and provide valuable feedback.

Understanding customer retention will help you answer fundamental questions, like:

  • What tactics can we deploy to drive repeat purchases and foster long-term customer relationships?
  • What products do customers buy that lead to repeat purchases?
  • What are the most effective levers we can pull to increase our customer lifetime value?

Tracking key metrics enables businesses to adjust their customer retention strategies and identify opportunities to improve the customer experience and increase revenue. Here are some of the most important ones.

Repurchase Rate

Repurchase rate is the percentage of customers who have purchased more than once in a given time period.

Also known as repeat purchase rate, it is a vital metric that every consumer brand needs to track in order to measure the success of its marketing and retention. It helps brands understand if they have a good product-market fit, and how much customers like and value their products.


Customer lifetime value is one of the most important metrics for consumer brands. Abbreviated as CLV, LTV, or CLTV, customer lifetime value is gross margin per customer, or for a particular cohort, over their lifetime with your brand. 

Customer lifetime value tells you how good your brand is at retaining customers who purchase more than once. Although it does not indicate true profitability (like net profit), it is a critical metric for businesses to measure, as it enables an understanding of the revenue potential of their customer base and helps guide strategic decisions.


Analytics is crucial for subscription-based businesses because it enables them to make data-driven decisions that drive growth, reduce churn, and increase revenue. 

Subscription relies heavily on customer retention, and analytics can help identify patterns that signal potential churn, such as declining engagement or usage. By identifying and addressing these warning signs, businesses can improve their retention rates and reduce customer churn.

These questions will help you understand how your subscription business is doing and identify points for improvement:

  • Are we just attracting discount shoppers that want one discounted order?
  • How can we extend the length of subscriptions? 
  • How can we reduce our churn rate?

Subscription Growth

In the above graph from the Daasity platform, you can see an example of a healthy subscription business. The kind of growth you want to see is consistent and sustainable. Consistent, sustainable growth means that a business can grow its customer base over time in a way that is predictable and doesn’t sacrifice its profitability or long-term viability. 

And, an important element of that is churn.

Subscription Churn Rate

Churn rate measures the rate at which customers cancel or do not renew their subscriptions within a given period. By understanding churn rate, businesses can identify opportunities to improve their product, pricing, and customer service to retain more customers and drive sustainable growth.

Churn Rate is calculated as 1 minus the number of active subscription days in a month divided by the total number of potential subscription days in a month. For instance, if a business has 100 active subscribers at the start of the month, and 5 of them cancel their subscriptions during the month, the churn rate would be 5%. 

A high churn rate can indicate that a business is not providing enough value or that its pricing is not aligned with customer expectations. A low churn rate is an indicator of a healthy business, as it suggests that customers are satisfied with the product or service and are more likely to remain loyal and refer others to the business. 


Data is crucial for merchandising because it enables businesses to understand customer behavior, preferences, and buying patterns. These insights then help them to forecast demand, optimize their product offerings, and nail their pricing strategy.

To gain a better understanding of your merchandising strategy and performance, ask yourself the following fundamental questions: 

  • How can I improve my product assortment?
  • What can I do to increase my Average Order Value (AOV)?
  • How can I optimize my purchase orders and improve forecasting?


Average order value is the average dollar amount that customers spend with your business, per order. It is one of the most fundamental metrics you should be tracking and optimizing because it provides insights into how much revenue is generated per customer transaction. A high AOV means that customers are spending more money per transaction, which has a positive impact on revenue and profitability.

Optimizing Product Mix

Gross margin is an important metric that helps you understand which products are most—and least—profitable, which can help you decide which products to promote, which to optimize, and which to take out of your assortment completely. 

For instance, products with high sales and high margins are your top performers because they are a key profitability driver, so you should prioritize these in your product strategy. Products that generate few sales but have a high gross margin per unit could be an opportunity. You could consider running a campaign to promote them and boost sales. 

On the other hand, products with a low gross margin per unit may be driving little to no value, especially if sales are low, too. You may need to adapt your pricing strategy, save costs on raw materials, or cut them off.

By understanding the gross margin of each product, you can make informed decisions about which products to focus on and how to optimize your product strategy for maximum profitability.


eCommerce operations metrics may not be as well-known as marketing metrics like CPA, but they shed light on a number of critical topics impacting customer experience, profitability, efficiency, and the ability to scale. 

Metrics like out-of-stock-rate and weeks of supply play an essential role in helping companies evaluate the efficiency of their supply chains. This is more important than ever: since the pandemic, even large, enterprise brands have been facing inventory and logistics challenges.

Here are some fundamental questions you should be able to answer about the operations side of your business:

  • How can we optimize our warehousing?
  • Should we be working with a 3PL (third-party logistics)?
  • Do we have any pain points in our supply chain?

Carrying Cost

Carrying cost (also called carrying cost of inventory and holding costs) is the sum of all expenses incurred by storing products in your warehouse until they are sold, including insurance, taxes, labor, energy, product depreciation, and inventory storage costs. 

Ideally, you would want to track the carrying cost as a percentage of the total inventory value, which is around 20-30% in a healthy business.

Measuring carrying cost helps ensure your operations are running efficiently. A high carrying cost can indicate issues in key areas like order planning, forecasting, inventory management, and profitability.

Weeks of Supply

Weeks of supply (WoS) estimates how long your inventory will last based on your current or estimated sales rate. It helps you monitor inventory levels and ensure you have enough inventory until the next purchase order arrives.  A healthy WoS is typically around 6 weeks, but this varies depending on your products and industry. 

For more metrics, including inventory turnover and backorder rate, check out our article 9 Operations Metrics to Keep Your eCommerce Business Booming.

Paid Media 

eCommerce metrics and data are vital for paid media because they provide valuable insights that help marketers to improve campaign performance and, ultimately, drive more ROI. 

For example, you can use metrics like conversion rate and ROAS to optimize ad spend and improve messaging at the ad group level, which should result in more conversions and revenue. 

eCommerce metrics and data play a key role in enabling advertisers and brands to make data-driven decisions and ensure they are getting an optimal return on their paid media investment.

Data can help marketers answer fundamental questions on their paid media strategy, such as:

  • In which channels should we allocate our marketing spend?
  • Is our marketing and advertising effective?
  • What are our most profitable channels?

If you’re not sure, read on to find out the most useful eCommerce metrics for paid media and how you can use them to optimize your campaign strategy.


Return on Ad Spend (ROAS) shows how much money you generate for every marketing dollar that you spend. It is one of the most-used eCommerce KPIs, and is a key indicator of the efficiency of paid media campaigns.

To calculate ROAS, divide your brand's revenue by your total marketing spend over a given time frame. For instance, if your brand has a monthly Google Ads budget of $10,000, and you drive $50,000 in sales that month, your ROAS is 500%. 

A high ROAS indicates a high return in relation to your advertising costs, which is a sign your campaign strategy is working.


Marketing Efficiency Ratio (MER), also known as blended ROAS, enables you to track and understand the efficiency of your marketing spend.

It measures the high-level performance of your marketing campaigns. While ROAS helps guide advertising decisions at the ad or campaign level, MER helps you understand how efficient you need your marketing to be in order to achieve your target profitability. 

To calculate MER, divide your total sales revenue by your marketing spend across all channels (if you would rather express it as a percentage, multiply the result by 100).

Marketing Attribution

Marketing attribution refers to the process of assigning an action or transaction to a specific channel, vendor, subchannel, or media type. This plays a key role in helping marketers to identify which marketing channels and customer touchpoints actually lead to conversions and sales, and which just soak up ad spend without a tangible return. 

There are many different attribution models, including first-click, last-click, and multi-touch. Whatever the attribution model, the goal is the same: identifying high-performing channels and tactics that lead to the most sales and, ideally, the highest LTV. 

Customer Behavior

Behavioral analytics helps brands identify and understand customer interactions, preferences, and buying patterns. Marketing teams can use this information to target high-value customers and optimize the shopping experience, which can lead to higher and more frequent sales. 

Fundamental questions include:

  • Who are my best customers?
  • How can I segment my customer base to better reach them?  
  • What is the typical duration between customer purchases?


RFM analysis is the best way to segment and rank your customers by value over a given time period. It considers three dimensions: 

  • Recency (how recently someone purchased)
  • Frequency (how frequently someone purchased), and 
  • Monetary (how much they spent)

RFM analysis helps you identify your high-value customers​​ (as well as low-value customers, and everyone in between).

High-Value Customers

High-value customers are the customers who are worth the most to your brand. While you might think a high-value customer is someone who spends a lot of money with your brand—and you’re not wrong—a more accurate definition is someone who is highly engaged, buys more often, and spends more than others. They are often (but not necessarily) long-term customers.

65% of a company's revenue comes from repeat customers and the top 10% are spending three times more than your average customer. Targeting your high-value customers can have a huge impact on your bottom line, which is why running an RFM analysis to identify them is a good idea.

Time Between Orders

Time between orders is a marketing personalization metric that shows the duration between a customer's orders, and how long it will likely take that customer to place their next order.

Time between orders is often underrated, but this useful metric can be used to create highly-effective, personalized marketing automations. One consumer brand uses Daasity's time between orders calculation to automate marketing offers to customers.


Your website is the backbone of your eCommerce business, so optimizing the user experience, especially key product pages and the checkout process, is essential. To do that, you need data. There are many, many metrics you can track, two of the most important ones being traffic and conversion rate. 

On-site analytics provide valuable insights into how visitors are interacting with your site, which pages and features are most popular, and where users may be experiencing difficulties or confusion. You can then use this data to make informed decisions about how to improve the user experience, ultimately driving more sales.

For best results, you will want to combine channel-level conversion information with marketing metrics such as LTV to understand how effective each channel is at acquiring the right types of customers.

Fundamental questions to be able to answer:

  • Is the conversion rate significantly different between new customers and returning customers, or between mobile / desktop / tablet visitors?
  • Is our bounce rate increasing or decreasing over time?
  • Are visitors coming from specific channels showing higher or lower conversion rates?

Conversion Rate

Conversion rate is a key performance metric that you can use to evaluate your website and campaigns. It measures the number of desired actions taken by users, typically purchases or other high-intent actions such as event signups, and divides it by the total number of visitors.

For example, if your brand’s site gets 1000 visits in a month and 100 conversions, your conversion rate would be 10%.

Tracking conversion rates is essential because it allows businesses to measure the success of their site or app and identify areas for improvement. Improving the conversion rate also allows businesses to get more sales with the same amount of traffic. If you double your conversion rate you essentially double the value of your ad spend, which can lead to increased revenue and higher cost efficiency.

Site Traffic

Site traffic refers to the number of visitors that a website receives within a specific time period. Depending on the analytics tool you use and how it is set up, the exact metric may be slightly different. Common metrics include visits, sessions, visitors, and page views.

Measuring site traffic is important because it enables brands to evaluate the effectiveness of their online presence and marketing efforts. By tracking the number of visitors and analyzing their behavior, you can identify patterns and trends, such as which pages are the most popular or which sources are driving the most traffic. This information can then be used to optimize your site, improve the user experience, and ultimately drive better business results.

eCommerce Analytics with Daasity

Life would be much easier if a single metric could tell you everything you wanted to know. But we all know it’s not that simple. To get a complete picture of your eCommerce performance, you need to track a range of KPIs across the business, from acquisition and paid media to operations and merchandising.

That’s where Daasity can help. Daasity is the only platform that enables brands to centralize and standardize their data across eCommerce, Amazon, retail, and wholesale channels, giving them a single source of truth. 

Daasity ingests and standardizes all your data —and we mean all your data —wherever it is coming from. Daasity enables you to see the full picture, rather than siloed channel or biased ad vendor reports, with holistic dashboards and reports showing all the metrics you need from every data source. 

Over 1600 brands use Daasity to track acquisition metrics that matter, find the leaks in their funnel, and uncover behavior patterns that lead to improved user experience and higher sales.

Visit us to learn how all these metrics can be automated, giving you actionable insights and powerful eCommerce analytics at your fingertips.

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