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Measure for Measure posted on Thursday, 08 May 2008

You’ve invested money, time and resources building a great website. But is it performing up to expectation? Do you even know what kind of performance you can reasonably expect?

By Patty Loessberg, Vice President of Business Intelligence, Interactivate, Inc.

If you aren’t tracking, measuring and analyzing visitor behavior at your website, you are missing an opportunity to turn data into actionable intelligence – the kind that increases revenues and reduces customer support costs. In a little more than a decade, an entire industry has sprung up to assist you with those tasks: web analytics.

Hits and Ancient History
Back in the Internet old days, around 1995, web counters were all the rage. Every with-it website had a little odometer-like counter that recorded how many hits the site had received. It was a meager metric at best because it revealed nothing except that someone (maybe the same someone repeatedly) had visited the site. Soon the quest was on to capture more information and to parse it in ways that were useful and user-friendly to marketers. Web analytics went through several evolutions, each more sophisticated than the next. By 2000, it was a well established discipline with many practitioners offering increasingly complex solutions for dealing with the growing volume of data available, which created more challenges.

Avoiding Analysis Paralysis
It is now possible to track a dazzling amount of data. It is also possible to drown in it. The challenges are to balance what you can know with what you need to know and to understand what you can do with all that intelligence once you have it.

The best way to approach the balancing act is to clearly define your website objectives, be they lead generation, sales, information distribution, or something else, and then establish the key performance indicators that complement your objectives. Think of it this way: it might be fascinating to understand how an internal combustion engine works and how aerodynamics affect fuel consumption – but none of that knowledge is required if your only objective is to drive a car to work. The same is true at your website. Avoid analysis paralysis by measuring only that which will help you achieve your objectives.

What Data Can Tell You
Initially, typical web analytics reports were pretty bare-bones: hits, referring sites, browser testing and basic search statistics. Today you can access a much richer data set and gain deep insight into your target customers’ preferences and behaviors. Based on what they do and don’t do on your website, it is possible to segment your customer base by a near-infinite number of demographic and preferential criteria. But here again, it is best to limit those criteria to data that align with your goals and your customers’ needs. The end game is always greater conversion (sales, leads, requests for information, etc.) for you and greater relevance for your customer.

Some of the advanced reporting options now available include:

• Click Path Analysis – By tracking the paths visitors take through your site to reach defined goals, you can chart the drop-out rate at different pages along the path and use that knowledge to eliminate unnecessary layers and create a smoother experience.

• Behavioral Segmentation – By understanding customer demographics, psychographics and preferences, you can develop campaigns and content that target different segments with different messages. You can even present these different segments with customized site experiences. For example, some customers might prefer content delivered via video, while others prefer text. Behavioral segmentation also allows you to interact differently with your customers based on where they are in the customer lifecycle. A prospective customer, for instance, will want a different level of information than an established customer.

• Trend Analysis on Behavioral Segmentation – Since your target audience profiles can shift over time, it’s important to track trends within specific target segments. Trend analysis tracks targeted demographic variables over time to determine if your target market is shifting as your product or service matures.

• Predictive Modeling – This uses data from the past behavior of your online customers to predict probable future behavior. For a new visitor, this model considers metrics such as referral source, keywords used, initial click-path taken, time spent viewing a page and so forth. For a returning visitor, the model might look at purchase history, frequency of visits, or time elapsed since the last visit. Armed with this data, you can present different segments with customized paths, which will improve their experience and the likelihood they’ll take the desired conversion step.

What Quantitative Data Can’t Tell You
Even the most sophisticated quantitative analytical tools cannot accurately answer the “why” behind consumer behavior. You may speculate that a person who spent only five seconds at your website left because of reasons X, Y or Z. But you can only know the real reason with any degree of certainty by asking. Traditional market research conducted online via surveys, by phone or in personal interviews provides the “why” that complements the who, what, where, when and how revealed by quantitative analysis.

As vice president of Business Intelligence at Interactivate, Patty Loessberg oversees a multi-disciplined team of experts in Web Analytics, Search Marketing and Email Marketing. She has 20 years’ experience as a senior marketing professional leading integrated marketing teams in the service, consumer goods and retail business sectors.

Posted by John Lincoln