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10 Most Important Ecommerce KPIs to Measure in 2024

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ecommerce kpis
Ecommerce continues to rapidly gain market share year after year. To stay competitive in this fast-paced environment, online retailers need to closely track and analyze key performance indicators (KPIs) that measure the health and success of their business. Understanding your ecommerce KPIs allows you to identify issues, optimize processes, uncover new opportunities, and benchmark your progress against industry standards. Monitoring the right metrics leads to data-driven strategies that drive sustainable growth and profitability. In this comprehensive blog post, we will overview the 10 most critical ecommerce KPIs that online retailers should monitor in 2023 to run a high-performing business. For each metric, we define what it measures, explain how to calculate it, provide up-to-date industry benchmarks, and discuss why it is vital to track.

GMROI – Gross Margin Return on Inventory Investment

Definition

GMROI measures how efficient and profitable you are at turning your inventory into gross profit. It indicates how many dollars of gross margin you generate for every dollar invested in inventory. The higher your GMROI, the better you are at wringing profit from your product mix and inventory levels. It shows your inventory is aligned with demand and selling at full price.

How to Calculate

GMROI = (Annual Gross Margin ÷ Average Inventory) x 100 To break this down:
  • Gross Margin = Total Revenue – Cost of Goods Sold
  • Average Inventory = (Beginning Inventory + Ending Inventory) / 2

Benchmarks

GMROI can vary widely depending on the retail sector:
Bar graph of GMROI in dollars across retail categories.
Overall, a GMROI of 2.0+ is considered healthy across retail categories. Anything under 1.0 signals potential issues with inventory management and product mix.

Why It Matters

Tracking GMROI allows retailers to identify negative trends and optimize inventory to maximize gross margins. It provides insight into which products generate the highest return on investment. With rising costs across the supply chain, effectively managing GMROI through careful inventory planning and merchandising strategies is more critical than ever.

Ecommerce Conversion Rate

Definition

The ecommerce conversion rate is the percentage of website visitors that complete a desired action, like making a purchase or signing up for a newsletter. It measures your ability to convert traffic into customers.

How to Calculate

Ecommerce Conversion Rate = (Total Number of Conversions ÷ Number of Website Visitors) x 100 Where conversions are any desired action like sales, email sign-ups, downloads, etc.

Benchmarks

Average ecommerce conversion rates vary significantly by industry and target action:
Bar graph of commerce conversion rate by industry.
Top-performing ecommerce sites typically have conversion rates between 2-4%, while rates below 2% indicate opportunities for optimization.

Why It Matters

Conversion rate is one of the most important ecommerce KPIs because it directly measures how effectively you are turning website traffic into business results. The higher your conversion rate, the more customers you acquire from the same amount of traffic. Lifting conversion rate just a few percentage points has a big revenue impact. Tracking this metric allows you to identify weak points in the customer journey and funnel. You can then optimize pages and touchpoints to reduce friction and get more visitors completing purchases.

Average Order Value (AOV)

Definition

Average order value (AOV) is the average dollar amount spent per order on your online store. It is total revenue divided by total number of orders.

How to Calculate

AOV = Total Revenue ÷ Total Orders

Benchmarks

AOV varies based on the products sold:
Bar graph of average order value of products sold in dollars.
The overall average is $109 across industries. You want your AOV to be competitive within your product vertical.

Why It Matters

Tracking AOV allows you to identify changes in purchase behavior over time. For example, a decreasing AOV could indicate customers are buying fewer items per order or purchasing lower priced products. Combined with conversion rate, AOV helps determine the revenue impact of each visitor to your site. Higher AOVs drive more revenue without requiring more traffic. You can lift AOV by optimizing cross-sells, upsells, discounts, and promotions around your most popular or high margin items. Understanding your AOV benchmarks is key for forecasting and making data-driven decisions.

Customer Lifetime Value (CLV)

Definition

Customer lifetime value (CLV) is the total revenue you can expect from an average customer over their entire lifetime with your business. It is a prediction of the net profit you will gain from your relationship with a customer.

How to Calculate

There are a few methods to calculate CLV, but a simple formula is: CLV = Average Order Value x Purchase Frequency x Average Customer Lifespan Where:
  • Average Order Value = revenue per order (discussed above)
  • Purchase Frequency = how often the customer places an order
  • Average Customer Lifespan = how long in months or years the customer remains active
You can further factor in additional costs like promotions, shipping, returns, support, and the cost of capital.

Benchmarks

There are no broad benchmarks for CLV due to differences in business models and industries. However, a good rule of thumb is CLV should be 3:1 of customer acquisition cost (CAC). Having CLV exceeding CAC means your customer relationships are profitable in the long run.

Why It Matters

Understanding customer lifetime value allows you to determine which segments are most valuable to focus on. You can shape product selection, promotions, and messaging around your most profitable customers. CLV also informs how much budget you can justify investing to acquire new customers. Shoot for positive return on CAC by having CLV exceed the costs. High lifetime value customers have a lower churn rate and make repeat purchases over many years. CLV represents the ultimate value of your marketing and retention strategies.

Customer Acquisition Cost (CAC)

Definition

Customer acquisition cost (CAC) is the total cost involved in acquiring a new customer. This includes advertising, promotions, discounts, paid search marketing, and all other marketing expenditures made to acquire new customers.

How to Calculate

CAC = Total Customer Acquisition Costs ÷ Number of New Customers CAC should include all marketing, sales, and promotional expenses dedicated to acquiring new customers for a given period. Divide this total acquisition spend by the number of new customers gained.

Benchmarks

Like CLV, acceptable CAC varies significantly across industries depending on average order values and profit margins. On average:
Bar graph of customer acquisition cost averages by industry in dollars.
You want to keep CAC as low as possible while still meeting volume and growth targets. This requires balancing acquisition spend against the expected lifetime value per new customer.

Why It Matters

Monitoring CAC ensures your marketing expenditures are efficient and driving a positive return on investment. If CAC creeps up, you may be wasting budget on underperforming channels, campaigns, or ad placements. Keeping close track of CAC movements helps you optimize the acquisition funnel to control costs and get maximum results from marketing spend. This leads to profitable growth over the long term.

Customer Retention Rate

Definition

The customer retention rate is the percentage of customers you retain over a given time period. It shows your ability to generate repeat purchases and loyalty. High retention means customers repeatedly purchase from you vs. competitors.

How to Calculate

Customer Retention Rate = ((CE – CN) / CS) x 100 Where:
  • CE = number of customers at end of time period
  • CN = number of new customers acquired during period
  • CS = number of customers at start of time period
This shows the percentage of initial customers who remained active at the end of the measured period.

Benchmarks

  • The average retention rate for all retail industries is around 63%.
  • SaaS and subscription businesses target over 80%+.
  • Ecommerce retention of 50-70% is generally solid.

Why It Matters

It is 5-25x more expensive to acquire new customers than retain existing ones. Maximizing retention is critical for keeping customer acquisition costs low and lifetime values high. Tracking retention over time shows if your efforts to build loyalty and create repeat purchases are working. When paired with CLV data, you can determine which customer segments deserve the most focus for engagement and retention campaigns.

Cart Abandonment Rate

Definition

The cart abandonment rate is the percentage of online shoppers who add items to their shopping cart but leave your site before completing the purchase. It measures leakage in the purchase funnel.

How to Calculate

Cart Abandonment Rate = (Number of Abandoned Carts ÷ Number of Website Visitors) x 100

Benchmarks

Abandonment rates average:
Bar graph of cart abandonment rate (CAR) averages in percent.
Rates above 75% are common across industries. The key is tracking your rate over time and working to gradually reduce it.

Why It Matters

A staggering $4+ trillion in merchandise is abandoned annually. Recovering even a fraction of these lost sales significantly boosts revenue and conversion rates. Analyzing cart abandonment helps you identify pain points in the purchase process. You can then remove friction through better product information, upgraded payment methods, coupons at checkout, streamlined flows, and savvy email remarketing.

Bounce Rate

Definition

Bounce rate is the percentage of website visitors that land on a page and immediately leave (“bounce”) without any other actions or pageviews. High bounce rates indicate content is not resonating.

How to Calculate

Bounce Rate = (Single Page Sessions ÷ Total Sessions) x 100

Benchmarks

Average bounce rates by industry:
Bar graph of average bounce rates by industry in percent.
Well-designed sites should aim for sub 40% bounce rates on key landing pages. Higher means opportunity to improve content.

Why It Matters

High bounce rates signal pages are not interesting or useful to your visitors. This wastes potential conversions and impacts your rankings. Analyzing bounce rates helps improve landing page quality, focus your content strategy, and provide the engaging experience users want. Key landing and entry pages to your site like product descriptions, category/home pages, and the blog should have lower bounce rates if the experience is dialed in. Monitor rates to catch issues.

Average Session Duration

Definition

Average session duration is the total length of time visitors spend actively engaged on your website per session on average. Longer durations signal you are holding user attention.

How to Calculate

You can measure this through Google Analytics for your site overall and for key pages. It will show the average session length over a given time frame.

Benchmarks

The average across all websites is 2-3 minutes, so the goal should be over 2 minutes for ecommerce sites. The 75th percentile is over 4 minutes. Top performers in their vertical can average 8-10+ minutes as visitors get stuck browsing products and content.

Why It Matters

Session duration shows whether your website experience is interesting and compelling enough to keep visitors engaged. Higher session times mean visitors are consuming more content and products before leaving. This leads to more pageviews, conversions, and sales. Short durations may indicate visitors are not finding what they want quickly, or that you need to add more sticky content like reviews, videos, and guides to capture attention.

Pages Per Session

Definition

Pages per session is the average number of pages viewed per session across your site. It measures how many pages visitors are loading and engaging with on average.

How to Calculate

Pages per session is an out-of-the-box metric in Google Analytics. The report will show you the average over time.

Benchmarks

The overall average is 2.6 pages per session across all websites and industries. Top performers aim for 5+ pages. Ecommerce sites should target 3-8 pages per session on average depending on their product selection. More pages demonstrate engaged visitors.

Why It Matters

More pages per session indicate visitors are intrigued by your content and product selection. They are clicking and browsing through your site. Higher page counts tend to correlate with more conversions and sales. It shows visitors are engaged rather than quickly bouncing away. Low page counts may signal disconnects in your navigation or opportunities to add related content and internal links to prompt further browsing.

Return Rate

Definition

The return rate is the percentage of orders that are returned. It measures product quality, fit, and alignment with customer expectations.

How to Calculate

Return Rate = (Total Returns / Total Transactions) x 100

Benchmarks

Return rates vary based on products:
Bar graph of return rate by product type in percent.
Rates above 10% in certain categories can indicate issues with product consistency, sizing, or depictions.

Why It Matters

A high return rate eats into your margins through processing fees and other costs. It also creates unhappy customers if their expectations are not met. Analyzing the reasons for returns allows retailers to adjust product descriptions, sizing guidance, and other details to set accurate expectations that meet demand. Certain categories like apparel and shoes have inherently higher return rates. Setting the right expectations helps offset costs through lower shipping rates and restocking fees. Monitoring all of these ecommerce KPIs against industry benchmarks allows you to set targets, identify lags or issues, and optimize every aspect of your online operations. Retalon provides advanced retail predictive analytics to help ecommerce brands accelerate growth and gain a competitive edge. Get in touch today to see how our AI-powered solutions can help you increase sales, margins, and customer loyalty through data-driven strategies.

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