What is your web analytics communication strategy?

Judah’s recent post titled “what does your web analytics team look like” reminded me of something that has been on my mind a lot since I presented my Web Analytics: A Day a Month webcast for the American Marketing Association last month. As I travel the world talking about web analytics to companies of all shapes and sizes, one thing I’m struck by is the number of differences in how companies approach sharing web analytic data and information.

It’s not as if there is any one “right” way to communicate about web analytics, but it is clear that there are many, many wrong ways to do it. But rather than dwell on wrongness, I prefer to focus on rightness so here are a few thoughts on developing a clear strategy for communicating web analytics.

This post may seem pretty basic to many of you, but if it does I would encourage you to ask yourself these questions:

• What decisions are web analytics driving in your organization?
• Are those decisions largely tactical or are they truly strategic?
• Do you feel like most people in your organization understand web data?
• Are you producing reports that are going under-used, unused, or are flat out being ignored?

If you are less than impressed with your responses I would encourage you to read on. I’m not saying you’ll necessarily learn anything new, but maybe you’ll read something that you think your boss should hear.

STEP ONE: DEFINE YOUR BUSINESS OBJECTIVES

I know, I know, you’ve heard me say this before. I’ve been saying this since 2002 but I’m going to keep on saying it since it bears repeating. By clearly defining your business objectives you get two things done:

1. You remind everyone in your organization why you have a web site and why those of you who work online come to work every day.
2. You build a framework against which you will define the core activities and interactions that are worth measuring and communicating

The second point is important: You cannot measure everything effectively and efficiently — you have to have some basis for deciding what to measure and what to report. I have seen any number of companies work hard to collect “all possible data” only to realize that few people are actually asking for that data and even fewer are doing anything with it.

When you define your business objectives and get consensus on what is most important to your online business, the measurable activities that you will be communicating across the organization become clear. Suddenly rather than struggling to measure every aspect of every page across every segment you’re able to focus on critical measures in critical paths in your most important visitor segments.

I covered all of this in Analytics Demystified what seems like years ago and again in Web Site Measurement Hacks (which you can now purchase direct from my site, had I mentioned that?) but again it is worth repeating. And while it is far less common now that I will ask companies about their business objectives and get conflicting opinions, many companies have still not gone through the process of clearly documenting these objectives and the associated activities to serve as basis for their measurement efforts.

STEP TWO: DETERMINE WHO OWNS ANALYTICS AT YOUR COMPANY

One of the biggest problems I see in web analytics today is a lack of clarity regarding ownership of analytics inside the organization. On this point I will be as clear as possible:

The owner of web analytics in your company NEEDS to be someone senior enough to ensure that analysis is being produced and used!

I spend an awful lot of time as a consultant talking about ownership and structure in analytics. Your executive sponsor needs to be closely connected to web analytics and have a clear understanding of the value and opportunity measurement provides. If this is not the case, you may spend an awful lot of time producing reports that go unread and analysis that goes unused.

I suspect that my fellow blogger Daniel Shields can attest to the goodness in this recommendation, working for a great boss at CableOrganizer, but more often than not when I ask the question “Who owns web analytics?” I get responses that talk about budget centers, middle-management who haven’t got budget authority or enough political clout, or worse yet, nothing but uncomfortable laughter.

Clients almost always ask “Where should web analytics live? Should it live in Finance, I.T., Marketing, or Research?” to which I almost always answer “Who is the most senior, well-connected person in your organization that is likely to really understand what web analytics is good for?” and then give their department as my answer. Here are some additional thoughts:

• Finance: Analytics living in your finance organization is fine because your CFO understands how to produce detailed analysis and make that analysis valuable internally
• Marketing: Marketing is great since in many cases marketing has the most to gain (or lose) based on web analytics data and analysis
• Research: If you have a market research organization this is also a great home since the analysis team in research usually has an excellent understanding of the customer and their (offline) behavior
• Information Technology: I personally don’t usually recommend that web analytics live in I.T. There is often too much baggage and a disconnect between I.T. and the business for this to work (but I do know of a handful of examples where I.T. ownership of analytics does work)

At the end of the day the most successful analytics organizations are those where the executive sponsor “gets it” and is able to champion for the cause at a very high level. They will need money, resources, and time from the rest of the company to deeply integrate the necessary web analytics business processes, so seniority is an absolute must.

STEP THREE: DETERMINE YOUR ANALYTICS ORGANIZATIONAL STRUCTURE

This is the step I’ve been thinking a lot about lately, how analytics organizations are structured and integrated into medium-to-large-to-very large companies. As I’m sure you know, this piece is far from a no-brainer — whether you subscribe to 10/90, 10/20/70, or some other percentage-wise distribution of effort, I think we can all agree that people are critical to web analytics success.

But as Judah deftly points out, just hiring someone is only the beginning of the work: The more important piece is determining how those resources are going to actually provide benefit back to the entire organization. You need to have a clear strategy for leveraging these resources to produce the maximum number of insights possible.

For about four yeas I have been talking about the “hub and spoke” model for web analytics organizations, especially to medium, large, and very large companies. The hub and spoke is basically a centralized/decentralized model for measurement, one that centralizes deep analysis expertise for use across the organization but mandates that each individual department and line of business takes responsibility for their own reporting needs.

The folks in the analytics hub are directly responsible for things like:

• Producing analysis, real analysis, to support business decisions
• Providing training out to the rest of the organization on tools and data
• Communicating about the goodness (or lack thereof) in the data collected
• Interfacing with the vendor(s) providing measurement software and services
• Managing multivariate tests and analyzing their results
• Working with I.T. to make changes to data collection and integration

Perhaps most importantly, the hub work directly for the executive sponsor for analytics (see STEP TWO above.) Establishing a real web analytics hub is the first thing you need to do if you want to STOP spending 80 percent of your time generating reports (something a prospect recently referred to as being a “report monkey” which they didn’t seem super-excited about …)

The folks in the individual departments and LOBs are responsible for things like:

• Paying careful attention to their key performance indicators and react to observed changes
• Spend enough time learning the available technology to answer at least basic questions when changes are observed
• Generating whatever reports are necessary on a regular basis and modifying those as required
• Interface with the analytics hub to ensure that requests for testing and analysis are clearly communicated
• Respond to test results and analysis by putting the insights generated to work for the organization

The best possible news is that the folks in the spokes don’t have to be web analytics experts! Hell, they don’t even need to read the available literature if they don’t want to (but they should.) They really only need to take enough time to learn what their KPIs are telling them and which reports in the analytics application(s) are relevant when things change.

Thinking about the relationship between the hub and spokes:

• The hub does analysis, and the spokes do reporting
• The hub executes multivariate tests, but the spokes recommend them
• The hub work directly with I.T., the spokes get to continue avoiding I.T.
• The hub helps to plan, manage, and monitor KPIs, the spokes live and die by them
• The hub runs something like Omniture Discover or IndexTools Rubix, the spokes use SiteCatalyst or Google Analytics

This is great news because there are many, many people out there that have a 0.2, a 0.33, or a 0.5 FTE for web analytics — not nearly enough time to really get deep into web analytics but enough to create the expectation that they’ll use the data to make business decisions. The hub and spoke model creates a business process to support partial FTE in their endeavor to use and benefit from web analytics, which those partial FTE seem to truly, truly appreciate!

In my experience, over time the people who really like this kind of work will pop up and ask great questions, looking to push the boundaries of their understanding of “our little craft.” They’ll read books, blogs, go to conferences, etc. and over time may realize that they really want to work in the field of web analytics full time. Which is great, because without those people flowing into the system, the multitude of recruiters and companies across the globe looking for experience web analytics professionals haven’t got a prayer.

Since Judah, Daniel, and I have been talking about the length of out posts lately I think I’ll stop here and publish Part II of this post later this week.

The key takeaways from the thoughts here are:

1. You have to have a web analytics communication strategy
2. You have to clearly define your business objectives and supporting activities
3. You need to define and establish an analytics organization
4. Your analytics organization needs to report to an appropriately senior person
5. The hub and spoke model for web analytics has many advantages, especially in large organizations
6. Web analytics done well has a tendency to make people more, not less, interested in web analytics (which is good!)