Market segmentation existed long before web analytics.  It’s a method for dividing a population into specific groups (segments) that share one or more characteristics.  The goal of segmentation is to maximize future value of that segment by optimizing your marketing mix.

Segment analysis will tell you different things about your audience than you will realize from studying overall population metrics.  In traditional market research, segments are created from demographics (such as age), psychographics (such as attitude), geography (such as zip code), behavior (such as usage patterns), and value (revenue earned and cost).

Using a web analytics tool to segment your online audience requires a bit of upfront thinking and requirements gathering before getting down to business.  Like all things web analytics, segmentation requires process.  Here are some tips that may help you create a process for web analytics segmentation:

• Determine your business objectives.  Like everything in web analytics, you can’t optimize what you haven’t defined as a goal.  A business objective driving segmentation might be to “increase conversion rate (over historical numbers)” or “to improve frequency” by offering something valuable to that segment.
• Define segments. Basic dimensions for segmentation in web analytics include: new visitors, repeat visitors, geography, time, referrer, keyword, and campaign type.  Many more dimensions and attributes can be used for segmentation too.
• Identify expected segment behavior.  By reconciling goals, historic performance data, and VOC research, you should be able to identify the expected behavior of the segment.  If your business objective is to “increase conversion rate,” your expected segment behavior might be to “complete the form” or “click on a link.”
• Measure current segment behavior. Sounds easy, right, but it will take system configuration and the right tool.  Pages may need to be (re)instrumented, tracking codes may need to be applied, query string parameters may need to be parsed, and in the worse case dimensions you want to segment or the metrics you may want to measure against may not be available in your web analytics tool.  For example, how would you use your tool identify the “conversion rate” for a segment of repeat visitors from newsletter X who came from Tokyo and previously downloaded a whitepaper?
• Create “optimization hypotheses.”  Once you’ve measured current behavior, create a hypothesis or hypotheses to test in order to optimize the behavior.  You may want to perform controlled experimentation whether a simple AB test (i.e. champion/challenger), multivariate test, or experience test.  For example, I may have detected that repeat visitors from Newsletter X responded better to Y offer after being exposed to a certain element than those visitors in the same segment who did were not exposed.  That element could have been a content theme, offer, call to action, creative, and so on.  Thus, I might create a hypothesis to test that combines elements of the user experience that I feel are key to persuading the behavior and thus fulfilling the business objective.
• Optimize content, offerings, user experience, and other site elements.  Based on your hypothesis, make subsequent changes to the elements that you think will drive the desired segment behavior.  For example, you may split traffic to two landing pages each with a completely different offer, creative, and call to action.  Or you may choose to switch out specific elements on one landing page (such as an image or call to action) using multivariate methods just to get Visitor X to “complete that form” or “click that link” to improve your “conversion rate.”
• Analyze segment behavior against hypothesis.  How did the segment perform against expected behavior and business objectives based on testing your hypotheses?  Tools that provide drill-down/drill-up and cross-dimensional capability allow to analyze segments and answer such questions. The tools I’m talking about are advanced and powerful, such as Unica NetInsight, Visual Sciences Visual Site, Omniture Discover, and WebTrends Marketing Warehouse.  Capabilities for segmentation analytics vary by tool, so make sure to dig deep into the offerings because not all tools with let you correlate metrics like “conversion rate” with dimensions like “keyword,” let alone build complex multi-dimensional segments.  In fact, some free web analytics don’t allow you to segment data at all (just filter it)!
• Go with what works.  Web analytics segmentation analysis will let you know what appeals to and works for a segment.  Success with web analytics segmentation means that you met your business goals and improved key performance of that segment.  Rinse, lather, and repeat the segmentation analysis and optimization process so your campaign outperforms and margins soar!

As a result of well-executed web analytics segment analysis and hypothesis testing you can realize new value in your customers and new opportunities in your campaigns. 

Add to the Conversation

Name:

Email:

Your email (required) will not be published.

Website:

Your Thoughts:

Please note that contributions are moderated and may take a little while to appear.