3 Faulty Assumptions To Avoid Making With Analytic Data
Analytics are great. They provide us with loads of good information. The danger is what we do with that information and in the assumptions we make. Here are three faulty assumptions I see regularly. Please share yours, too. Your analytics tell you what people are searching for Recently, while waiting to speak at an online […]
Analytics are great. They provide us with loads of good information. The danger is what we do with that information and in the assumptions we make. Here are three faulty assumptions I see regularly. Please share yours, too.
Your analytics tell you what people are searching for
Recently, while waiting to speak at an online marketing conference, I was listening to another speaker share a B2B client case study. The president of a search marketing firm, he shared how studying the client’s analytics showed them searchers were using branded queries more than generic terms. As a result, they focused the client’s search efforts on branded search.
I looked around the room. No one questioned a thing or challenged the speaker. It seems obvious, but I’ve heard so many people buy this line of thinking, it warrants addressing the issue: your analytics don’t tell you what people are searching for; they tell you the queries for which you get click-through. There’s a big difference.
Don’t get so buried in your site’s numbers that you begin to view your market through them. Make sure you use a variety of keyword research tools to give you a more accurate view of searcher behavior.
High-volume keywords are the most important ones
Too often, site owners only look at the keywords that send the most organic traffic. They monitor them, make tweaks to increase the traffic from them, and obsess over any decrease in traffic from them. By focusing only on high-volume keywords, site owners miss opportunities to refine and improve their search marketing and conversion efforts.
Make sure you look beyond your high-volume keywords. Every month, you should do a complete scan of all of the keywords that drove traffic to your site. In doing so, you often find extremely low-traffic keywords that have high-conversion potential. You know what I’m talking about. Those queries right in your sweet spot. The ones you wish you had plenty more of.
Pay attention to those queries. Find out which search engine was used and where you are in the ranking for those queries. Chances are your low volume of traffic for these keywords isn’t related to low search volume. More likely, it’s because your content isn’t optimized well. Maybe the visit from that came from a searcher that pawed through eight pages of search results before clicking on yours. Make sure you look beyond the big numbers; there’s plenty of good information in the small ones, too.
The last click caused conversion
People don’t make decisions quickly in B2B. It’s a process. Visitors have likely been to your site several times before they take trigger any conversion events in your analytics. Yet, most often we look solely at the details surrounding the visit in which conversion occurred. What was the keyword of that visit? What was the ad? From where were they referred?
If we look only at that visit in which conversion occurred, we’ll make some poor decisions. We’ll ignore the value of the display ad that triggered the first visit to the site. We’ll miss the fact that PPC triggered the second visit and the referral from editorial content that caused the third. All of these impressions begin to build trust and reduce the searcher’s perceived risk of taking action. But if we don’t look beyond the details of the last click, the fourth visit in this hypothetical example, we’ll devalue the impact and importance of the earlier channels, possibly even deciding to eliminate them. Be careful not to do that. Before you act, make sure you look at the whole picture.
For more on the issue, last year Business.com published a study on B2B analytics (registration required) that explored this problem. It’s worth reading and understanding.
What faulty assumptions have you made or seen others in the B2B world make?
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