27% of users abandon their purchases due to a payment process that’s too long or complex. Once visitors have browsed through your catalogue and started adding products to their baskets, they’re about to enter your checkout funnel. It’s critical to capture their full attention and propel them toward a single objective: finalising their order. This means limiting cart abandons while simplifying the purchase process as much as possible. It’s therefore essential to understand the main steps of the conversion funnel when optimising your overall conversion rate. But how should you go about doing this? What should you analyse, exactly, in the visitor journey? It’s indeed somewhat of an art. 


The funnel’s overall performance 

On an e-commerce site, the primary sales KPIs to track are of course turnover/revenue, average cart value and number of transactions. You may also analyse revenue per sales channel (e-mail, social networks, direct traffic, search engines), per marketing campaign (paid or organic), per product category or even per promotional action. 

But a deeper analysis of the purchase funnel will allow you to understand in greater detail at which steps of the conversion process your visitors are leaving your site. The main steps are the cart, choice of delivery, payment and confirmation. 

In AT Internet’s web analytics solution’s settings, you can define which type of interaction (page load, form submission, click on a button, etc.) will trigger measurement between steps. 


The main KPIs to track, as seen in this report: 

  • Conversion rate in the funnel: the ratio of carts which converted into finalised transactions, compared to all active carts from the analysis period (in green above the funnel). 
  • Number of active carts in each step (figures in blue under the name of each step). 
  • Rate of passage for each step (percentage in green between each step) which is the ratio between carts that continued on to a subsequent step and the total active carts at the analysed step. 


Cart abandons 

Let’s take a closer look at the critical step that is a person’s arrival on the cart page. The cart’s performance will have a strong impact afterward on the conversion process. As with buyers who visit a house for sale, first impressions are paramount. The only CTA (call-to-action) to highlight at this time is the one that will carry the user through to the following step. It’s therefore essential to have a good understanding of what we call non-converted carts and abandoners.   


This means analysing carts that were active during a certain period but which did not lead to a conversion. By measuring the number of interactions that occurred after cart creation, and by analysing the cart’s potential value, you can detect which customers are hesitant and which customers have high potential. 


Cross-site navigation  

The linear, single-site and single-device purchase journey no longer exists. You must be able to measure the entire customer journey. And your digital analytics tools can tell you a lot about user interactions with your brand. Don’t limit yourself to simply analysing visits in silos… In concrete terms, if you analyse several platforms that share the same cart IDs, you can reconcile cross-site visits within your web analytics tool. Thanks to this, a visitor who creates a cart on one device and then finalises the purchase on another device will no longer be considered as a cart abandon (on the first device). We’ll instead consider that both devices contributed to the transaction.  

Other reports exist for tracking cross-device behaviour: retention analyses, overlap, navigational sequences, visitor deduplication. Use them to your heart’s content! 

Learn more about multichannel and omnichannel analysis in this article. 


Efficiency of payment methods 

No matter the payment system, its smooth functioning is critical to finalising the transaction. One technical error from your payment service provider could mean your customer immediately loses trust in your brand. And same thing on the analytics side: shoddy tagging and imprecise data can skew your analysis and direct you toward poor decisions… 

Your payment-related metrics must be absolutely reliable and tracked correctly. This includes:  

  • The number of times your site suggested a certain payment method (with the possibility of determining a result which accounts for a margin requested by your service provider). 
  • The number of times your visitors generated an error linked to this payment method (entry error, form submission error, etc.). 
  • The number of transactions that occurred with this type of payment 

Cart abandons are not always voluntary. We tend to underestimate technical problems (issues with payment, 3D Secure, speed…)  

Benoit Gaillat, CEO of Mobibot.io 

Maximum acceptable shipping costs 

How much should you charge for delivery? This is a question all e-retailers must answer, and there are different pricing strategies to respond to this question:  

  • A flat shipping rate, no matter the order value  
  • A shipping rate that decreases as order value increases  
  • Free shipping on orders of a certain amount  
  • Free shipping on all orders  

No matter what you choose, your shipping price must not be a deal-breaker. While you might not necessarily always offer free shipping, you must find the right balance to cover the costs of your delivery provider. To understand how visitor behaviour relates to shipping cost, calculate the total turnover from your orders, as well as the share attributed to shipping. 


To examine the impact of shipping cost, focus on visitors who haven’t yet converted but who have nonetheless made it to the shipping options page. Examine the proportion of shipping costs to the total cart value. 

You might come to one of the following conclusions:  

  • for orders with a low total amount, you might determine that shipping fees are too high 
  •  for other orders, you can determine a shipping fee threshold, which can vary depending on the purchase cycle and the product in question. On certain sites, customers expect free shipping for purchases over 50€, whereas on other sites, this threshold might be 100€ or even 200€.  


Precisely measure order confirmations 

As the order confirmation page is critical, be sure to implement monitoring and alerts on the page’s availability and number of loads. But beware when measuring confirmation pages, as your information can be skewed due to 2 pages that (much too) often fly under analytics solutions’ radars:  

  • The payment form 
  • The payment confirmation page  

The reason for this? To measure an interaction, a JavaScript script is required. And a JavaScript script requires action on the customer’s browser. The problem here is that the form and confirmation page are generally hosted on the payment service provider’s (bank) site.  

The consequence? There’s no link between the 2 browsers and it’s impossible to measure finalised orders (at least in JavaScript). The technical solution (available with AT Internet) is to measure transaction confirmations or cancelations from server to server, without using the customer’s browser. Without this server-side measurement, you miss out on 30% to 40% of order confirmations in your analytics tool. Think you can manage your performance with such a huge discrepancy? Good luck…  

To conclude, and to underline the issue of data quality we’ve just touched on, we should remind you that many analytics solutions (which happen to be American and free of cost) provide sampled data. And for us, sampling is unacceptable, especially in e-commerce when dealing with sensitive transactional data. If your web analytics solution uses sampled data, the revenue/turnover and number of orders reported will only be ballpark values if your traffic exceeds a certain volume. The reliability of this data is therefore quite questionable. And according to certain estimations, metrics produced from sampled data can vary by 10% to 80%… so you’ve been warned! 


Want to know more? Get many more best practices, tips and recommendations from e-commerce experts in our series of articles dedicated to e-commerce, and download our practical guide:  


Editorial Manager. Bernard is responsible for the content strategy of the AT Internet brand. He has almost 10 years’ experience in technical and marketing writing in the Software industry. A word specialist, Bernard’s job sees him working on many different mediums including blogs, white papers, interviews, business cases, press, infographics, videos etc. His specialist fields? Marketing and digital analytics content of course!

Comments are closed.