You can actually see your ecommerce site as 2 parts: a browse section and a buy section. The buy section is everything starting from the shopping cart page. At that point, visitors are no longer just looking around, but have shown a clear intent to purchase.
The browse section is everything that happens before the shopping cart. For a typical ecommerce site, that includes the home page, the category page and the product page, as well as the search function.
DO NOT ONLY OPTIMISE THE BUY SECTION OF YOUR ECOMMERCE SITE
We all know that you can take the biggest steps in the buy section (and especially the checkout) to increase your conversion rate and thus increase your revenue. But do not limit yourself to just the checkout. If you also optimise the pages of the browse section, you can also increase your sales considerably. Your mission must be to persuade more visitors to consider a purchase and so continue to the ‘buy section’. Usually there are many opportunities there (and especially on the product pages).
POTENTIAL BUYER RATE: THE METRIC YOU NEED TO HANDLE YOUR BROWSE SECTION
Before you optimise your home page, product page or category page, it’s important to know what the percentage of potential buyers is. A potential buyer in this scenario we define as a ‘visitor who goes beyond viewing the product page in the purchase process’. Or to express it tangibly: Someone who has clicked on the ‘Add to shopping cart’ button. At that point, the activity is no longer just browsing, but shopping.
To find out how well your shop is doing in this area, we use 1 certain metric: the percentage of potential buyers relative to the total number of visitors. Or, in other words: the percentage who clicked on the ‘Add to shopping cart’ button. This is sometimes called the ‘add-to-cart ratio’ or ‘add-to-cart rate’. But we find that name rather abstract, because it does not sufficiently emphasise the importance of this.
We prefer to call this metric the ‘potential buyer rate’. That term better describes the content here: more important than the click on the ‘add to cart’ button is what this actually means. Namely, the visitor has taken a very important step at this point: he is no longer a random visitor or browser, but a ‘potential buyer’. That is why we use the term ‘potential buyer rate’.
Note that we are talking here about buyers, but to be very correct it is about sessions and not so much about visitors (or users, as Google Analytics defines it). The difference? A user may need 2 or more sessions before converting. But Google Analytics is very focused on sessions, so that is why we calculate our metric based on sessions.
In itself, that does not make that much of a difference, the most important thing is that we calculate it in one certain way and stick with that method so that we can monitor the evolution of the potential buyer rate. That way, we know if our optimisations are bearing fruit.
By the way, one of the reasons Google Analytics typically deals with sessions is that there is no water-tight method (yet) for cross-device tracking. Or stated simply: In most cases, Analytics (still) cannot find out whether someone who first looks on mobile and then converts on desktop is the same user. Unless, for example, the user is logged on to your site on both devices. But that typically happens in very few cases. That’s why we still talk about sessions. It may not be perfect, but more important than the figure itself is that we can keep an eye on its trend and see that trend evolve in a positive direction.
IMPORTANCE OF THE POTENTIAL BUYER RATE
If your potential buyer rate is on the low side, there are undoubtedly opportunities in the browse section. What is low? Well, that varies from sector to sector and shop to shop. But as a rule of thumb: If you are below 5%, you CERTAINLY need to work on this. Don’t quote me on that percentage, because as I said, it varies considerably. But of course you have to start somewhere. And there is always a margin for (substantial) improvement, no matter what percentage you have now.
Do not underestimate the impact of the opportunities that can be found here. Suppose your potential buyer rate is just 2%. Then it’s not that unthinkable for you to get to 3% through optimisation. That does not even seem like that big a difference.
But that means you’re sending 50% more sessions through to the purchase section. And if nothing changes in the buy section – in other words, the drop-offs in the buy section remain unchanged – then that means that you increase your conversion rate and, consequently, your sales by 50%. Not bad…
In addition to the overall conversion rate for e-commerce, the potential buyer rate is therefore one of the most important metrics for your ecommerce site. A high potential buyer rate means that you succeed in getting many visitors to take the step from ‘browsing’ to ‘buying’.
EVOLUTION OF THE POTENTIAL BUYER RATE
The potential buyer rate is, in particular, a metric for which you want to watch the evolution. If you have 6% now, that does not mean that you cannot make any progress.
Work on the browse section and keep an eye on how that figure evolves. This tells you whether your efforts are paying off. If you test changes with A/B tests, then you know for certain, but not everybody has enough traffic for testing, and then you need to make optimisations based on conversion research. In that case, it is definitely important to keep an eye on the evolution of that potential buyer rate.
POTENTIAL BUYER RATE AND A/B TESTS
The potential buyer rate is also a very good metric for judging your A/B tests in the browse section.
Of course, you also have to look at the impact of an A/B test on your transactions. But if you only have just enough traffic and conversions to do A/B testing, it can be handy to also look at other metrics so that you can reach a conclusion more quickly. This typically involves page goals. On a category page, the goal is, for example, to get your visitors to click through to a product page. Then you can use that as a goal.
But you can also look at the potential buyer rate when analysing your A/B tests on a category page. You will then learn which version is more likely to trigger considering a purchase – which is an important insight. And because there will be more add-to-cart events than final conversions, this is a handy metric for reaching conclusions faster.
THIS IS HOW YOU CALCULATE THE POTENTIAL BUYER RATE
But how do you get that figure?
There are several ways to find this figure in Google Analytics, each with its own pros and cons. Here are 3 possible ways:
The advantage of this method is, of course, that you can easily see how many sessions there were with ‘add to cart’: 4.91% in this case.
In my humble opinion, however, the biggest problem with this method is that the enhanced e-commerce is often not set up 100% correctly. With virtually all of the Analytics setups we see, there are data from the enhanced e-commerce reports that are not right. And that makes it dangerous to draw conclusions from this. If you draw conclusions based on incorrect data, you might also make the wrong decisions. However, if you’re 100% sure that your enhanced e-commerce has been correctly implemented, then you can easily get your potential buyer rate.
The best way to get the potential buyer rate is to add event tracking to the add-to-cart button. Then you look at the number of unique add-to-cart events. And then at the number of sessions. Now divide the number of unique events by the number of sessions:
In this example, the percentage is 18766/255068 = 0.074 or 7.4%. Advantage of this method: This is the most watertight method. The biggest disadvantage of this method is that you have to calculate the figure manually, so that you cannot easily use it in reports for in-depth analyses. However, there is a simple solution: you just set a goal with the add-to-cart event:
You then go to Advanced > Conditions and fill in the condition based on which you can determine whether a visitor got further than the product page. In this example, someone who clicks the ‘shopping cart’ button is immediately redirected to the shopping cart page, and we thus know that whomever visits the shopping cart can be considered a potential buyer.
Important: Choose ‘sessions’ here. As mentioned earlier, we look at everything based on sessions, so we should apply that consistently. In this example, you will see this result on the right in the segment preview:
We see that just 1.25% of all visits go to the shopping cart page. That means that there is still a great deal of work to do ‘upstream’ on the ecommerce site (on the homepage and product and category pages).
An important nuance of this latter method: This is not always watertight because it depends strongly on the site and the default ‘behaviour’ on the site. In the example above, it is fairly simple to identify a potential buyer, since you will be taken to the shopping cart immediately after clicking on the ‘add to shopping cart’ button. However, that is not the case with all ecommerce sites. For example, if you stay on the product page after adding something to the shopping cart, then you may have added something to the cart but might leave the site without ever looking in the shopping cart. In that case, it is more accurate to add event tracking to the button.
On some ecommerce sites, you can also just skip the shopping cart, for example, by clicking ‘checkout’ in the dropdown on the shopping cart icon at the top right (a.k.a. ‘the mini-cart’). In that case, it is not correct to look at visits to the shopping cart page, since some people will skip it. And it is also not correct to just look at visits to the checkout, as some visitors will first go to the shopping cart. In this situation, we recommend that you set up the event tracking correctly on the add-to-cart button.
Your conversion rate for ecommerce is, of course, important. But make sure you look beyond that. You also need to know how many sessions actually show a purchase intent. The potential buyer rate will help you with that and gives you better insight into the browse-to-buy evolution for your shop. If you set this up through event tracking and then a goal, then you can monitor your potential buyer rate relatively easily , and you can use it in custom reports for, among other things, analysis of A/B tests in the browse section. The potential buyer rate thus gives you additional insights when testing. And those insights will, in turn, help you with further targeted optimisations of your shop.