Web Analytics: New Year - New Opportunities

Many of you may be looking back at last year and asking yourself what you accomplished On the personal side, you hopefully had a great year. But looking back 12 months, did you accomplish the goals tied to your business, job function, and specifically, your Web site?

As this is a common time to reflect on the past and plan for the future, I wanted to examine a few common frustrations. If you're like others in the space, you probably entered the year thinking one or more of the issues below.

They'll sound familiar to many of you All are probably things we'd have loved to have solved back in 2005. Unfortunately, most people are waking up on the first business day of 2007 and realizing they still face the same issues they did last January. Now hopefully, if you've been reading ClickZ and over the past year you've made some progress on some of these, In any case, let's look at these top five issues and try to understand the underlying problem.

Analysis of Five Issues

1. I know there's a ton of value in Web analytics, but we aren't doing anything with it now. Where do we start?

Have you considered how you might want to use this data? How it can help you do a better job? Have you allocated the responsibility of Web analytics to someone? This wouldn't be someone within IT, it would be someone with a strong Web strategy marketing background. Do they need to be an expert statistician? Not at all. This is a major misconception about Web analytics. It shouldn't be an IT person, it doesn't need to be a stats pro, but it does need to be someone who understands Web strategy, the business, and how to use data. Think MBA rather than IT pro.

2. It seems we have a mountain of data, reports, and scorecards, but we really aren't getting any insight from all that data. Why not?

Typically this happens when people are not focusing in on the right data. Do you feel the Web channel goals have been correctly defined and agreed upon? Has someone taken the initiative to formulate KPIs (key performance indicators) and the metrics that support those KPIs which can help interpret fluctuations? If you company is still struggling with number one, make sure you focus in on what matters, get that nailed in Q1, and come this time next year you'll be in much better shape. Once you have the important behaviors nailed, through out 98 percent of the other data coming from your Web analytics tools and just focusing on understanding the data that drives those behaviors. We will look back at the other 98 percent, but not until we get the basics nailed.

3. We identify all these great opportunities, but we just can't get others to act on them and improve the site through testing or otherwise, how can we get others excited about the opportunities?

This is most commonly related to a lack of others understanding what they can get out of Web analytics. It's imperative they understand how it can help them do their job better. In many cases, it takes a small win by someone on the team to understand. Find the most receptive person on the Web team, ideally one of the leaders. Help them get a win leveraging data and improving the site, then share that story throughout the team. Once you get this under your belt you can move onto bigger things and into systemized testing. Executive support is key for taking it to the next level and investing in an optimization tool (i.e. Offermatica, Optimost, etc.) and the related support for testing. More on executive support to come in the future, by the way.

4. Wouldn't the Web analytics and other data like attitudinal, competitive and call center data be much more valuable if I could use them together?

Three different people or groups within a company own these three or four different data types. Typically, none understand the other data types, how they could be of value, or how their data could be valuable to others. Add to this another common under-estimatation: the power of all of this data together is much greater than the sum of all the parts. Yes, this takes executive support as well.

5. Culture of analysis: How do we get our company to start basing decisions on data?

This is without a doubt the biggest transition of all. Becoming a data-driven organization shifts the way all decisions are made. Instead of making decisions based on gut feelings or "past experience," we strive to build a culture where all decisions are made based on a combination of data insight and educated decisions. In order to get your company willing to make the investment to transition the way they look at the Web channel and make decisions, there must be a proven track record. Executive support isn't optional, but an absolute must. Things won't get done without this level of support. Source