Purchases to Date – Part I [SiteCatalyst]
Website visits don’t occur in a vacuum. People who are on your site today may or may not have been there in the past and if they have been there, some have purchased items and some have not. But how do you know if the current reports you are looking at in SiteCatalyst reflect those who have purchased in the past or not? How do you look at SiteCatalyst reports by how much they have purchased in the past? Having this context can greatly improve the analysis you are doing so in this post, I will share some techniques which allow you to easily segment your visitors by how much they have spent in the past…
Why Do This?
Before diving into how to do this, let’s explore the rationale. Imagine that you are a retailer selling Electronics, Clothing and Furniture. One question you might ask is “I wonder how much money all of the people who are on my site today have spent in the past?” Wouldn’t it be cool to see that 25% of the people who bought something today had purchased $500 or more in prior visits? Do people who have purchased more than $700 in the past convert at higher rates than those who have only purchased $300? Do people who have bought $400 or more in Electronics tend to only buy and look at Electronics products? As you can see, there are an endless number of analytics questions that can be studied once you know how much money current visitors have previously spent.
Surprisingly, however, there is no easy way to see this in SiteCatalyst. One way to do this is to create Segments. However, since there are so many segments that could be built, this is not always an easy option. To answer the questions above, you’d have to create different segments for each dollar amount and product category (i.e. people who have spent $100, $200, $500, etc…). Plus, you’d have to pull the data using DataWarehouse or ASI. Of course, this becomes much easier in SiteCatalyst v15 (if you are lucky enough to have access to it!), but it still requires a lot of segments to be built. Therefore, I will share a different approach that you can consider to accomplish this using a Counter eVar. As a quick refresher, a Counter eVar is a type of eVar that you increment as needed and retains a numeric value for each website visitor. This counter can be incremented by “1” each time it is set, or it can be incremented by any other number as needed. In past posts, I have described using Counter eVars to track # of Pages Viewed and Ben Gaines described how to use Counter eVars to score visitors. If you want to learn more about Counter eVars, please review this old blog post.
With the set-up and refresher out of the way, let’s dig in. As mentioned above, in this scenario, we are a retailer selling three main product categories and want to see how much money each visitor has spent prior to the current visit. To do this, in addition to setting the Products string during the purchase event, we would set a Counter eVar equal to the amount that is being purchased like this:
Notice that we have added up the purchase amount and passed it to a new Counter eVar40. In the above example, if the current visitor hadn’t previously visited the site, the value in his/her Counter eVar after this purchase would be $900. Since Counter eVars don’t have a notion of currency, the value that will be stored in the Counter eVar report in this case would be “900.00” (I would suggest that you round numbers to the nearest dollar since having decimals will make applying SAINT Classifications difficult). Keep in mind that you should set the Counter eVar to be Most Recent (Last) Allocation and set expiration to “Never” (or something like 90 days) in the Admin Console. That is all of that we have to do from an implementation standpoint.
So now let’s see how we use this. If the above visitor comes back to the website next week and adds a few products to the shopping cart and we pause time for a second and were to look at the resulting SiteCatalyst report, we would see something like this:
As shown here, we can now answer the question of how much money visitors had spent in the past at the time they added items to the shopping cart today. In this case, it looks like about half (49%) of people adding items to the cart today had not purchased previously. The visitor mentioned above would fall into row five in this report as part of the 1.38% of people who had purchased $900 in a previous visit. The same principle would apply to Orders and Revenue, so you could see a report like this:
When you extrapolate this principle by thousands of website visitors, you can see some interesting trends about what percent of website visitors transacting today had purchased in the past and how much they had spent. Next we can make this report more readable by applying SAINT Classifications to the Counter eVar to bucket the dollar amounts spent into logical groupings:
Now we have a new report that was previously unavailable! Pretty cool, huh?
In addition, if we wanted to take things to the next level, we could break this report down by Products to see which Products made up the Revenue in past visits:
So that is one way to see how much visitors on your site have purchased previously so you can add that to your existing web analyses. Next week, I will continue with “Part II” of this topic and go into some additional ways you can apply this concept so stay tuned…Thanks!