702 total views, 3 views today
In this blog post, we’re going to take a look at an illustrative story of how Google Analytics can be used to track the abandonment rate of your customers. This post will teach you how to calculate your abandonment rate and what you can do about it if it is too high.
And I’d also like to mention that this post is available in text, audio and video format below.
Fran, the owner of a children’s clothing store, was able to track her website’s shopping cart abandonment rate using Google Analytics, with helped her whole operation.
When I met Fran she didn’t have a way of tracking her website’s shopping cart abandonment rate, and so she was really unsure about how many visitors were starting the process of purchasing a product, but then cancelling. She had tried to address potential cancellations by clearly showing her shipping rates and pricing on her website, but still she was wondering if there were too many steps involved in moving a visitor from just visiting her shop to becoming a customer.
Fran already had Google Analytics on her website, but she tended not to use it much. She wanted to understand her conversion rate better over the next year, and was planning to learn more about it.
With this in mind, Fran booked a strategy session and as part of this session I showed her how to track her website’s shopping cart abandonment rate. Here’s the steps you need to follow to do this yourself.
Step 1: You need a Goal
What are Goals?
Goals enable you to match website visitors with the actions that you want to track. With goals you can easily compare different groups of visitors to see if some groups of visitors are more frequently buying products than others.
We added two Google Analytics goals so that Fran could track her eCommerce conversions when a visitor purchased an item or reached the checkout page.
Step 2: You need your Goal to fire whenever a visitor buys from you
When a visitor bought a product from Fran’s website, the website created a unique thank you page URL based upon the order number. We were able to create a destination goal for the unique thank you page using what is called a regular expression.
What is a regular expression?
A regular expression is a way of matching all the website pages that follow a certain pattern, so that if a visitor goes to any one of those website pages it will then trigger the goal.
The Goal needs to be set up in such a way that it always fires when a visitor buys, but never fires at any other time.
Step 3: Turn on Funnel
In the setup of the goal we turned on the Funnel option. Funnelling enables you to see if people abandon at any step in the process. This then provides you with the cart abandonment rate.
Fran’s store has three steps that a visitor has to go through in order to buy a product – 1. Add an item to the cart, 2. Checkout, 3. Pay and complete the order. We added the first two of these steps to the Funnel for making the purchase.
Step 4: Wait…. And then look at the results
You want at least a month’s worth of data before you look at the results, so that you have enough visitors coming through your website.
Using the Goal Flow report, we were able to see that the step in Fran’s process with the largest abandonment rate was the ‘Visitor goes to Checkout’ step.
More than 50% of the customers who had got all the way to the checkout step did not continue their purchase! And almost all of these customers chose to leave the website altogether rather than continue shopping.
So we now know how many visitors we are losing during the purchase. Is there a way to stop losing so many visitors?
To investigate the more than 50% of customers that are leaving Fran’s website from the checkout page, there are a few things that we can do.
Investigation #1 – What is the visitor doing on the webpage immediately before they decide to leave?
We can set Fran up so that her website records events in Google Analytics whenever a user interacts with any element of her Checkout page. This way we can be certain of what the last step is that visitors are reaching before they decide to abandon the cart.
If we find that the majority of people abandon at a particular step then we would know which parts of the user interface would benefit from an upgrade.
The advantage of setting up events in this way is that over time we will have a detailed report of exactly what the last event was that was triggered before the visitor abandoned the checkout. And we can also compare across time periods if the abandonment rate changes.
Investigation #2 – How long is someone spending on the checkout page before they decide to leave?
We can reasonably assume that people who are leaving the checkout form immediately have a very different issue compared to the ones that get halfway through the form.
For example, if most of the visitors are abandoning the checkout as soon as they get to it, it may be that the user interface is not what they were expecting to see. Alternatively, they may be getting to the checkout simply to see the final price, if this is not obvious earlier in the shopping process.
On the other hand, if visitors are getting most of the way through the form before leaving then there may be a technical issue that is causing visitors to leave.
To conduct this investigation, we can split out website data into a couple of different groups of visitors, and then compare the amount of time they spend on the checkout page. Group #1 contains the visitors who exit from the checkout page, and Group #2 contains the visitors who complete their purchase. If there is a significant difference in the time spent on page in these two approaches then this gives us a clue as to where the problem might lie.
Investigation #3 – Wouldn’t it be nice if we could see how the abandoners are using the form?
What we can do is set up a visitor mouse tracking tool on the website, and analyse the recordings to see how visitors are using the checkout page. This will enable us to see what visitors clicked, what they typed into forms, if they had any technical issues, or if they just left without filling anything out.
Investigation #4 – Is anything distracting the visitors when they are in the process of buying?
It is important to remove any distractions such as signing up to a newsletter or other promotional events while visitors are in the process of checking out.
If you’re not sure if something is a distraction or not, it is possible to use heatmap tools that display areas of high mouse activity on a page. If you have a checkout page, and a heatmap tool shows that any area of the page other than the checkout form is getting mouse activity, then we can try to remove the distractions in order to increase the number of people completing their purchase.
So we were able to improve the situation with Fran’s abandonment rate, by applying some of these simple principles. This helped Fran attract more customers and business, and her clothes store thrived as a result.
Web Data Analytics specialises in growing your conversion rate online. Current and past clients include e-commerce in B2B and B2C industries, lead generation websites and corporates. Petra Manos is experienced in tracking and interpreting website visitor interactions, improving website conversion rate, and attributing online sales to marketing channels. Please call Petra on 0405 123 696 today, email firstname.lastname@example.org, or visit http://www.web-data-analytics.com.