"Market segmentation is a natural result of the vast differences among people."

– Donald Norman (author of “The Design of Everyday Things” – excellent read! I’ll never look at doors the same way again.)

Donald nailed it when it comes to customer segments. Your customers are all unique. They all have their own interests and motivations for looking at your product and service offerings. You (hopefully) use your analytics data to gain insights for improving marketing initiatives. So why wouldn’t you arrange your data in a manner that captures these differences in motivation and behavior? Analysis of all-encompassing data can yield some interesting sticking points, however it can just as easily mislead you with regards to customer behavior.

What Can Be Done to Avoid This?

As marketing professionals and analysts, it is our duty to get to the information that leads to more effective campaigns. So if you haven’t considered segmenting your data, here are four steps to take to get it done in your web analytics tools.

  1. Look at your high-level offerings. Before jumping into the creation of segments in your solution, it is a good idea to take a few steps back. First look at your organization from a high level. What are the core service and product offerings of your organization? How do your target audience and customer demographics align with these service offerings? This information will give you the foundation on which to base your analytics customer segments. If you already have this figured out, great! Move on to the next step.

  2. Identify touch-points with your customer segments. Now that you know who your customer segments are, it’s time to determine how your analytics solution will identify them. For this, you’ll want to identify how they are discovering your brand. In the case of web analytics, are customers in a particular segment arriving via search engines (organic or paid)? If so, what search phrases did they use? What landing pages did they use? Use the trending you see with these questions to create the rules for each segment.

  3. Create your segments! You’ve identified your segments and how you can find them in your analytics data. Now it’s time to set up these rules in your solution. In the case of Google Analytics, set up the proper Include rules using Regular Expressions for related search phrases and landing pages.

  4. Make sure the segments actually work! At this point you may have put some significant time and effort into creating these customer segments. Don’t let all of that hard work go to waste. Make sure it separates and organizes your data properly. Test them with different date ranges to ensure the results are somewhat consistent and make sense.

As modern day analysts and marketers, most of us do our best not to think in silos. This mentality should translate over when it comes to data analysis. Though some questions may warrant looking at high-level, all-encompassing data, the best insights will come from segmentation. Adapting these tips to your own process should help you discover hidden gems for converting more customers.

Have some other helpful tips for segmentation of data? Feel free to leave a comment and share the wealth! Also be sure to follow us on Twitter (link to the right) to stay up to date on the latest tips for better analysis.

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