Revenue attribution is how you (or the software tracking your online marketing activities) decides where to place the credit for the sales that occur on your website.
If someone who has never been to your website before does a paid search, clicks an ad caused by a keyword you bought, then makes a purchase, the attribution is easy. They keyword that you paid for to get the click, should get credit for the revenue generated by the purchase.
But very often, this is not the scenario that leads to conversions which take place on your site.
- People come multiple times before purchasing.
- They often come from different sources each time the come, occasionally repeating sources along the way.
- They sometimes make a series of purchases, either after all of their visits or interlaced among their visits.
These are just a small sampling of the issues and don’t begin to define or describe the complexities.
And this is not the post where I’ll try to do either. (Those will come.)
But was we work to sort out the right way to handle revenue attribution within ClickEquations, we’re capturing some data that I thought it would be interesting to share.
The following images document real-life ‘click-chains’ – sequences of visits to a website with resulting or intersperced conversions. They are a tiny tiny fraction of the sequences found in one account in a 30 day period.
- Rows with green ‘P’ cells are visits that came from paid search keyword clicks.
- Rows with white ‘N’ cells are visits from organic search, email, affiliate links or other sources.
- Rows with yellow ‘C’ cells are conversion events.
- The number in the first column represents the visit number for that person over all time.
- Only visits within a 30 day window are included although the visit count may have begun far earlier.
And if you’re into this kind of thing, they’re very interesting.
Click-Chain Histories
#1 – Our first contestant is a frequent visitor (note we’re starting with visit 37), loves those paid search ads, but does buy at least occasionally.

Four more after the jump (as they say)
#2 builds up a head of steam with a bunch of Dec 30th visits and a purchase, then wham-wham, two more buys with no more paid-click-charges over the next few days.

#3 is another guy an online marketer could love. One paid search, three purchases in a row.

#4 is a jack-rabbit, clicking six paid searches over two days, but coming through with the purchase in the end.

#5 is another consistent visitor and shopper, with purchases before and after their two paid clicks.

For each of these, assuming for a moment that we’re only concerned with paid search, how would you allocate the (yellow) revenue to the (green) keywords?
Now make it harder – assume that for each (white) ‘N’ we can tell you if it was a bookmark or email or affiliate link. How would you allocate revenue across all the visits?
Hint: There are no right answers. Much more later.
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