Seven Reasons to Switch Web Analytics Tools
1. Somebody installed this tool back in the Dark Ages and it simply does not work. We looked at some reports and they just make no sense. Our most popular pages don't even show up! This is clearly old, broken technology and no good.
2. It costs waaaaay too much and there are free ones out there from Google and Yahoo!
3.It's free -- how good can it be?
4. A cross-functional team spent four months reviewing different tools and they selected one they considered the very best for us. After three months of negotiation, two months of actual acquisition and six months of implementation, we went back to the selection committee to sign off -- and discovered none of them work here anymore.
5. We're redesigning our whole Web site and putting in a new content management system. Time to throw out the bath water and everything that's in it.
6. When we wanted to slice and dice our Web data by time of day and source of visit and business outcome across a few more customer segments over the past eight months, the tool we're using fell over and died.
7. Nobody can agree on the actual, real purpose of our Web site -- so we tend to use these reports as a drunkard does a lamppost, for support rather than illumination.
8. (bonus) The only numbers that matter are profit and loss -- and these Web data reports are all about bounce rates and conversion rates and social media influence vs. sentiment ratios. It's just too geeky. We need a business tool.
The solution? Love the one you're with. (Yes, that's a Crosby, Stills, Nash & Young reference.)
Tools will never provide insight. They can show anomalies, point out trends, and set off alarms when things go out of scope. Some of them can even highlight the most significant correlations. But they can't tell you why things happened -- and they certainly can't tell you how you might put that information to use. For that you need analysts.
Step One, Tech Check: Make sue all your pages are properly tagged.
Step Two: Data Check: Make sure you're not measuring employees, bots, etc.
Step Three: Identify your most important goal.
Step Four: Do not read any of the reports; ask questions instead.
Step Five: Analyze your data. Think about it, play with it, discover patterns in it.
Step Six: Devise tests to try out hypotheses and engage in continual improvement,
If all that doesn't significantly improve the value of your Web site and the utility of your Web analytics tool, you might want to consider switching.