Key metrics to determining potential buyers
This post was made Jun 05, 2009 by Jeff Noethen
Bryan Eisenberg recently wrote a post entitled “How many potential buyers are visiting your website?” In his post, he suggests that once you filter out the 3% of visitors who convert, the remaining 97% can be divided into two groups: potential buyers and disqualified traffic. I agree wholeheartedly with this posture.
He also states that you should be able to decipher from your marketing traffic the channels that are bringing ample amounts of traffic but with poor quality vs. those channels that bring both good traffic and good quality. However, Bryan stops here and states that your web analyst should be able to tell you the rest of the story: understanding the 97% more in depth; bringing in less disqualified traffic and more Potential Buyers; and more effectively turning those Potential Buyers into Buyers.
As a web analyst, I’m going to give you a further push in the right direction of figuring this all out. What is a potential buyer? Bryan suggests that companies that have a higher conversion rate than the 3% general average, focus on their repeat customers (possibly also called return customers). Traditionally this is almost a no-brainer, visitors who come back to your site, almost always more apt to buy, unless you have a large percent of repeat or return visitors who never buy (possibly why Bryan says repeat customer instead of repeat visitor). This could be an effective way of increasing your conversion, but if you hound these customers with offers and incentives you could drive them away and / or make them sour on your brand.
If these customers are already returning to your site without much effort on your site, these are your loyal customer whom you should respect and only occasionally incentivize as a way of saying thank you, not milk them dry. You want to keep your pipeline full, right?
I’m not saying that Bryan is wrong by suggesting that you corner your repeat customer market. It is a sound approach for short term sales, and maybe it won’t impact your long term sales, but I believe there is that possibility this could have negative long term results.
Instead, your analyst could start by examining your funnel and segmenting out those visitors who add to bag but do not buy. Those are your high potential buyers. Granted, many of these visitors will be back to buy anyway, why not focus on closing their shopping window? Next, look at your product browser group, i.e. those visitors who viewed a product page. How many products did they view? If they viewed one product and left, you can probably throw them out with the bath water, but 2-3 or more product views, these are the visitors that are also your potential buyer group. Sure you could throw in some other metrics like how long did they spend on said product pages and / or how long was their session.
You can apply these rules by marketing channel as well to really find out which channels are more effective over another. However, I don’t want to give too much away, because like Brian, I’d love for you to contact me for my services. As well, we discuss many specific analysis problems and give examples of possible solutions in our book!
