To optimise your e-commerce site and boost turnover, it’s essential to measure and track several KPIs. If you’re an e-retailer, these KPIs will help you track your e-commerce performance on a daily basis. Generally speaking, your KPIs should be mapped to the successive steps a visitor takes in your purchase funnel. If you haven’t already modelled your KPIs in this way, here’s a (non-exhaustive) list of the e-commerce KPIs you should be sure to include in your web analytics dashboard.
The volume of visits represents the traffic that has come to your site. Remember, a single visitor can make several visits to your site using different devices or browsers. After 30 inactive minutes, we’ll consider that the visit has ended. If you notice variations in this KPI, be sure to examine the current context of your e-commerce activity:
- Are you currently running acquisition campaigns?
- Have you recently sent a reminder email to your prospects?
- Is your organic ranking having an impact?
- Have you launched or closed a certain platform (mobile app or site, for example)?
Conversion rate (visit)
This KPI tells you the likelihood of a visit converting into a purchase, and it can be calculated quite simply: it’s the ratio between visits that have converted and the total number of visits. If you see major fluctuations in this KPI, be sure to verify:
- The quality of incremental new visits generated by current campaigns
- Any potential technical problems on key pages (the steps of your funnel)
- If certain pages need a new layout or design
Average cart value
This KPI represents the average amount spent per order on your online store platform(s). To calculate the average cart value KPI, simply divide your turnover by the number of orders placed during a given period. As always, don’t forget to refer to the context when analysing this KPI:
- Are you currently running any promotions (promo codes, discounts, gift vouchers, etc.)?
- Has the overall number of orders increased?
- Have you changed your shipping prices?
The turnover (revenue) you generate is nothing more than the product of the 3 aforementioned metrics (visits, conversion rate and average cart value). You can interpret this KPI as follows if you notice any variations:
- A drop in turnover despite an increase in visits: Verify that the conversion rate is stable. If it isn’t, it means that your incremental visits are not as good-quality as your normal point-of-reference visits. It’s a good idea to verify which traffic sources, referrer sites and campaigns are bringing this low-quality traffic.
- A drop in both turnover and conversion rate despite consistent traffic levels: Have you changed anything technical or design-wise on your site? Check the performance of your key pages (product pages, cart, conversion funnel, payment pages, etc.) on different devices and browsers.
- A drop in both turnover and average cart value despite a stable level of visits and conversion rate: Investigate things related to your promotional offers. There may have been a problem with distribution, leading to few or no additional orders, with a lower average cart value.
Visitors & customers
To measure your website’s popularity, this is an essential KPI: it qualifies an internet user over a given period. We also use the term unique visitor, generally identified by a cookie and counted only once during the analysed period. If the site requires a login and you collect additional information on the visitor (such as socio-demographic information, for example), it can be even more beneficial to take a customer-centric approach in your behavioural analysis in order to refine your sales strategy according to buyer profile.
Page views per visit
As its name indicates, this KPI indicates the number of pages viewed per visit, on average. This KPI attests to the efficiency of your e-commerce site (product catalogue, categories, product pages, search options, etc.) and its ability to engage visitors.
The bounce rate KPI represents visitors who only viewed one page during their visit to your site. In other words, they arrived and then left. A high bounce rate on a single page generally indicates low user interest. But there are many potential ways of interpreting this quality-based KPI: UX problems, navigational issues, content issues, etc. Many different explanations exist for high bounce rates. Consider that if you’re seeing bounce rates higher than 85%, you should take action.
Average visit length
The average visit length KPI is obtained by dividing the time spent during all visits by the total number of visits. You can then compare the average visit length of your new visitors versus your returning visitors. Doing so will give you a good idea of how engaging your content and online sales approach are.
Your web analytics tool will count a user as a new visitor when he or she does not have a web analytics cookie present when arriving on your site. If a visitor comes to your site, then deletes the web analytics cookie, he or she will be considered as a new visitor when returning to your site. The new visitor metric indicates the volume of prospective customers and therefore your sales potential.
Conversion rate (visitor)
Be curious about your visitors! (rather than your visits). Depending on the products you sell, the purchase cycle can be long, irregular, and fragmented. By taking a “visitor” approach when measuring your online store’s attractiveness, you can measure your true ability to convert your visitors. Calculating the conversion rate per visitor is simple: it’s the number of visitors who placed an order divided by the total number of visitors to your site. Remember to take the temporal granularity of your sales cycle into account when analysing your conversion rate per visitor. For example, a grocery delivery site might expect to receive orders on a weekly basis; in this case, visitor conversion KPIs could be calculated on a week-long period.
Number of transactions
Counting the number of transactions enables you to calculate the average cart value (the average value of your orders). By tallying the transactions made on your e-commerce site, you can then evaluate the performance of all related actions or elements:
- Payment methods
- Shipping provider
- Promo codes
- Customer ID
Average order value
To get the average order value metric, divide the total amount of sales-generated turnover by the number of transactions. If your catalogue offers a wide variety of products, you can calculate the average value of orders for each product category. The average order value KPI will help you detect trends and better understand the behaviour of your buyers. You can even refine your analysis by measuring the turnover generated by each source (campaigns, search engines, social networks, email, direct traffic, referrer sites, etc.).
Cart abandon rate
This KPI represents the number of completed transactions with regards to the number of carts created. More than half of users abandon their shopping carts along the path to conversion – they generally leave a site without having finalised the payment step. As cart abandons are of the biggest issues plaguing e-retailers, you should definitely understand why and how to take action to reduce your cart abandon rate (a few ideas: cart reminder messages, offers for reduced shipping, one-page checkout…).
Cost of customer acquisition
In other words, this KPI tells you how much you’ve got to spend, on average, to recruit a new customer. The cost of customer acquisition metric lets you evaluate the performance of your marketing campaigns and the ROI on the acquisition investments you’ve made. To identify your top-performing channels (where you should be investing your budget), calculate the customer acquisition cost per channel.
Customer lifetime value
This KPI is an estimation of the total amount that each customer will spend on your e-commerce site over the course of his or her “lifetime” as your customer. You can calculate customer lifetime value by combining average order value, purchase frequency, and customer lifetime (duration) metrics. With this KPI, you can determine a maximum cost of acquisition. Evidently, to reach profitability, your customer lifetime value must be higher than your cost of acquisition.
Repeat purchase rate
The repeat purchase rate reveals the proportion of customers who make repeat purchases amongst your entire customer base. To calculate the repeat purchase rate KPI, just divide the total number of clients who have purchased on more than one occasion by your total number of customers. Segment your visitors to determine groups who have only purchased once or twice, and those who have purchased several times. Then leverage this information to adapt your targeting and tailor your marketing messages to these different groups. For example, you might consider taking an ultra-personalised approach with your most loyal customers (by taking their purchase history into account to craft highly relevant messages).
While the repeat purchase rate KPI is calculated using the entire customer lifetime, the purchase frequency KPI represents the proportion of customers who have made more than one purchase over a given period of time. This KPI is useful when analysing the purchase cycles of different products sold on your e-commerce site.
Average duration between orders
This KPI shows the average length of time that passes between 2 purchases. Armed with this information, you can, for example, schedule the sending of your marketing automation emails. The average duration between orders KPI can be calculated by dividing 365 by the value obtained for purchase frequency. Keep in mind that that this average duration between purchases can vary between product categories.
The churn rate is the percentage of customers who never come back to your site. The lower this rate, the higher your customer lifetime value will be. By keeping an eye on your churn rate, you can ensure that your offerings are sufficiently matched to your target audience. To improve your churn rate, use a web analytics solution which offers purchase scenario models based on different buyer profiles, such as the RFM model.
Product return rate
If your customers often order and then return a certain product, there are several possible explanations:
- The product page is very engaging and efficient
- The product does not match the description, or is of poor quality
Depending on your industry and your products, the product return rate can strongly vary. Logically, we see higher product return rates in the apparel industry, where sizing issues can cause product return rates of around 20% to 30%, or even higher than 50% in some cases.
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