Purchases to Date – Part II [SiteCatalyst]

Last week I described a new way to track how much money visitors had spent on your site prior to their current visit. This week, I am going to expand on this topic and provide some other cool uses of this concept. If you haven’t read my last post, I suggest you do that before reading this one.

Revenue by Product Category

In the last post, you may recall that we were able to quantify how much money the visitor had purchased in the past and break down current reports by those amounts. In the scenario I described previously, we could only see the total revenue amount across all product categories (in the previous scenario the product categories we discussed were Electronics, Clothing and Furniture). However, there is no reason that you cannot create a separate Counter eVar for each product category (or your major product categories if you have too many!). Doing this will allow you to see how much visitors had spent on just Electronics, for example, prior to future Success Events like Cart Adds or Orders. This might be good for companies that have distinct teams focused on each product category. To do this, the code might look like this:

s.events=”purchase”
s.products=”;SKU111;1;300.00;; evar1=Electronics,;SKU222;1;400.00;; evar1=Clothing,;SKU333;1;200.00;;evar1=Furniture”
s.eVar40=+900
s.eVar41=”+300″
s.eVar42=”+400″
s.eVar43=”+200″

By doing this, there would be one Counter eVar which shows that the visitor in our example above had spent $300 (row five) in Electronics prior to his/her second visit which might result in a report like this:

You would then see a report like this for each product category, though I would still recommend one Counter eVar like the one first described, which combines revenue for all product categories combined. Keep in mind that you could also use Product Merchandising to see total previous revenue (eVar40 in our example) by product category, but since you only get two levels of breakdown in SiteCatalyst reports, splitting out each product category into its own Counter eVar provides one more level of breakdown…

Orders to Date

As long so you are going to go through the effort to see how much money the current visitor had spent on your site, why not also track how many Orders they had completed? Doing this is very similar, though it will use up more eVars. Here is how you would do it. First, set a new eVar in the Admin Console and set it to be a Counter eVar with an expiration of “Never” or possibly “1 Year” depending upon how long you want to keep the data. Once this is done, on the purchase thank you page, simply set the Order Counter eVar to “+1,” as you normally would set a Counter eVar like this:

s.events=”purchase”
s.products=”;SKU111;1;300.00,;SKU222;1;400.00,;SKU333;1;200.00″
s.eVar41=”+1″

Kind of anticlimactic huh? By doing this on every purchase thank you page, you can track how many orders each website visitor completed and can then use this in analysis efforts. Next time you want to see how many times people who have added items to the shopping cart today have ordered in the past, simply open this new “Previous Orders” Counter eVar and add the appropriate metric(s):

Here we can see that 21.13% of the Cart Additions that took place today were from visitors who had not ordered on our site in the past (ignoring those pesky cookie deleters!). If we wanted, we could also break this report down by Product to see which Products they had purchased. Also, keep in mind that this example shows Cart Additions, but that we could have just as easily added Orders, Revenue, Internal Searches or any other website metric we wanted to this report to see how many orders had taken place prior to that Success Event. If desired, we could also use SAINT Classifications to group this “Previous Orders” Counter eVar into logical buckets of say “1-2 Orders,” 3-5 Orders,” “5-10 Orders,” etc…

Final Thoughts

So there you have it! Between this post and the last one, hopefully you have some new ideas to try out on your website so you can leverage past purchase behavior when doing your web analyses. If you have any questions/comments, feel free to leave them here. Thanks!