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What to Measure for Ecommerce Conversion 2/2

Boost revenue and fine-tune your ecommerce strategy with our guide to ecommerce conversion metrics…

Top seven metrics to measure

Here are the seven most important conversion metrics to track and some guidance for each.

1. Sales conversion rate

Your sales conversion rate measures the percentage of people who visit your ecommerce store and make a purchase. Calculate your ecommerce conversion rate from a specific period (e.g., one month or year) by dividing the number of completed purchases by the total number of ecommerce site and app visitors.


Sales conversion rate = Number of purchases / Number of visitors


Sales conversion rate is the most classic ecommerce metric because it helps you track the core health of your ecommerce business. Even small changes in your sales conversion rate can lead to a significant revenue increase (or decrease) over time.

This metric is also a key performance indicator (KPI) for any number of marketing or product efforts. You can track the sales conversion rate to understand whether your marketing campaigns are effective or if changes to your checkout flow drive more completed purchases.

Conversion rate optimization involves adjusting your ecommerce website or app and marketing efforts to make sure as many people as possible are completing a purchase.

Not all conversions are equal

Looking at your conversion rate in isolation can be misleading. For instance, many businesses see higher conversions during the holiday season. However, if all of those new conversions are one-off, low-value purchases, they won’t have a lasting impact on revenue and aren’t cause for celebration.

McKinsey research has found that focusing on building customer satisfaction and customer lifetime value (CLV) rather than getting individual sales helps companies be more profitable. To do that, analyze your conversions more deeply. Dig into your conversion rate by comparing conversion across:

  • New vs. returning customers
  • Product category
  • Buyer location
  • Platform or device type (e.g., desktop vs. mobile or iOS vs. Android)

Onbac’s cart analysis makes it simple for non-data analysts to gather insights ontop-performing product categories, high-value customers, and popular product combinations. Using that information, they can update their ecommerce store to improve the number of high-value and repeat purchases.

Analyze personalization efforts

Sales conversion rate also helps you track the impact of your personalization efforts. Use it to see whether your personalized recommendations, ads, or content drove conversions. From there, you can iterate on your personalization strategies.

2. Average Order Value (AOV)

Average order value shows the average amount spent when a customer buys something from your digital sales channels. To measure AOV, divide revenue by the number of purchases during a specific time.


Average order value = Revenue / Purchases


Along with conversion rate, AOV is one of the most popular ecommerce product metrics to track because it’s an effective indicator of ecommerce business health. Increasing average order value is a fundamental lever of growth. Even with the same number of customers completing the same amount of purchases, you could directly increase revenue and potentially improve profit margins per order.

Track which products drive high-value conversions

AOV requires understanding what drives high-value conversions. Compare AOV across transactions containing specific products and product categories to see which kinds of products contribute most to high-value baskets.

3. Percentage of returning customers

The percentage of returning customers over a specific time shows you the number of new customers compared to repeat customers. Calculate it by dividing the number of returning customers by the total number of customers during a set amount of time—such as one week or month.


Percentage of returning customers = (Number of returning customers / Total customers) * 100

Most online businesses want to drive repeat purchases. Tracking the percentage of returning customers over time helps you determine whether your buying experience encourages people to return.

If you can acquire customers but struggle to get them to return, there could be friction in the customer experience after they make a purchase. For example, there may be problems with customer service or shipping that need resolving.

Track which products drive repeat business

Beyond looking at how many repeat customers you’re getting, you also want to understand the type of products that drive repeat purchases. Look into the order history of repeat buyers and identify which product or product category they purchase most frequently, or what they initially purchased.

4. Shopping cart abandonment rate

Shopping cart abandonment rate measures the amount of people who added items to their cart but didn’t go through the checkout process. To calculate your cart abandonment rate, divide the number of carts abandoned by the number of carts initiated.


Cart abandonment rate = Carts abandoned / Carts initiated


People who’ve added an item to their shopping cart show high intent to buy. When they don’t complete their transaction, it might reflect friction in the checkout flow, costing you revenue.

Cart abandonment rates are typically high. Baymard Institute benchmarks the average at almost 70%. Lowering your cart abandonment rate means directly improving your ecommerce revenue. Product Data Journeys can help you discover where users are getting stuck before they can successfully check out.

5. Average basket size

Similar to AOV, average basket size measures the number of items people typically buy per order. Measure the average basket size by dividing the total number of items in customer baskets by the number of customers.


Average basket size = Total number of items in customer baskets / Total number of customers


Tracking average basket size helps you to understand your customers’ buying behavior. This information enables you to drive larger baskets and, in turn, revenue.

Average basket size is also helpful in analyzing the effectiveness of marketing promotions and campaigns. Compare average basket size before, during, and after the promotional period to see its impact.

6. Revenue by product and product category

Revenue by product and product category measures the revenue generated by different products. To see what percentage of revenue each product category brings in, divide the revenue for that category by the total revenue for that same period and multiply the result by 100.


Percentage of revenue from product category = (Revenue from that category / Total revenue) * 100


Repeat the calculation across different categories and compare the results. To analyze individual product performance, use revenue from that specific product rather than the category. Additionally, to analyze the performance of products within a category, divide the revenue from each product within that category by the total revenue from that category.

Analyzing revenue by product and product category enables you to identify top and under-performing products. Use the data to adjust your product portfolio and pricing strategy to make them as effective as possible. You might decide to rethink the promotion, product pages, or pricing of underperforming products or cut them altogether.

Track the revenue of different types of products over time to understand which products are typically in demand at different times of the year. Revenue analysis across products helps with inventory management and demand forecasting so you always have the right products in stock.

7. Top-performing product combinations

Identifying top-performing product combinations involves a set of analyses rather than an individual metric. Cart Analysis with Onbac enables you to create a chart for any product and discover which products people usually buy alongside it.

For example, a grocery store might find that the average customer tends to buy strawberry jam with freshly baked bread.

Cart Analysis helps you identify the most popular product combinations.

When you know which products customers tend to buy together, you can suggest them as recommended items to drive cross-selling and increase average order value.

Analyze, then take action

Measuring metrics and running analyses is all about gathering information. But what do you do next?

Experimentation helps you improve your strategies, move metrics in the right direction, and improve your bottom line. Use conversion metrics as a starting point to identify where you can refine your ecommerce strategy. Credits to Amplitude.

From there, try out adjustments to the customer experience. For instance, you might double down on a successful marketing channel (such as email marketing, SEO, or paid ads) or add a pop-up with personalized product recommendations. Run A/B testing to find the best messaging and design for your ecommerce site, social media posts, and ads. Measure the results, then analyze and repeat.