Do you know what you cart abandonment is costing you in sales?
Cart abandonment is where a visitor has added a product to your shopping cart and then for some reason does not proceed. It’s a measure of lost sales. Firstly let’s look at how you can work out what your Cart Abandonment Rate actually is, so we can see how eCommerce Conversion Optimisation can improve your sales. Even in the most basic eCommerce Reporting setup, you should be able to see your Cart Abandonment Rate. For example, in Magento, you’ll see this figure in Advanced Reports in Sales > Cart Abandonment.
In this screenshot, you can see weekly Abandonment Rate of between 80% and 85% with Abandonment of $1.54m over 4 week period.
No need to weep yet, as that $1.54m figure is not a real reflection of lost sales, as it’s impossible to have a 100% Cart Completion Rate. But is there room for improvement?
If you have inside knowledge of your industry you can get an inside picture of Cart Abandonment Rates to benchmark against. If not, you can start to look at some industry averages. Based on major surveys studies over the last two years, the average Cart Abandonment Rate is 73.47%
So in the example, above if we take the median Abandonment Rate at 81%, then a move to 74% (surveyed averages) would have a huge impact on sales – over $133,000 over a 4 week period, or $1.7m over a year.
Even a 1% change in Cart Abandonment would be worth almost $250k a Year.
There are two main things you can do:
A large portion of cart abandonments are simply a natural consequence of how people use e-commerce sites – many visitors will be doing window shopping, price comparison, saving items for later, exploring gift options, etc. These are largely unavoidable cart and checkout abandonments, and probably represent around 60% of abandonment.
But what about the others?
When you want to influence people’s behaviour, you can use this simple model.
Getting someone to complete a shopping cart checkout is no different.
The main difference in how you approach this, to a standard optimisation project, is that users have already shown a degree of motivation by adding the product to your cart, so Reducing Friction will be your main focus, and this means understanding all the friction points in your Cart.
So if you are working on Reducing Friction, you need to get a strong understanding of where the frictions points are in your checkout process.
It is essential that you have a clear view of the dropout points in your checkout.
If you are using Google Analytics this means you should configure Enhanced eCommerce tracking. You can then see the dropouts at the various stages of the Funnel.
Your Cart Software can also display your Cart Funnel, depending on the Plugins and Reporting Modules you have installed. Best practice would be to track visitors, based on the sections of the Checkout they have completed so that even if you have a single page checkout, you can see at which stage in the form they are dropping out.
It’s all very nice to have the data, but there is nothing like EXPERIENCING your cart like a real customer. We highly recommend that you install customer journey video tracking software to get real insights into where customers are coming un-stuck and dropping out.
Note: We believe customer journey video tracking is a quicker and more effective way to get insights into your customer behaviour in your cart than controlled usability studies. Why? Because usability studies are done under artificial conditions and are task-based – they don’t reflect the different motivations and distractions the real customers feel.
Firstly, there is no one right answer to reducing friction. Instead based on your data, customer videos, and previous case studies, you should look for potential improvements to A/B test in a controlled Conversion Rate Optimisation process.
Secondly, you need to develop a Shopping Cart CRO process with clearly defined objectives, and an A/B testing plan where you can measure results in real $ revenue. The second article in this series will look at how to develop a Conversion Rate Optimisation process, and the most common Quick Wins to test.