"Market segmentation is widely regarded to be one of the key elements of modern marketing" - The Market Segmentation Workbook, Sally Dibb and Lyndon Simkin
Imagine you did a survey of the entire state of Utah and found out that the most popular cereal was Cheerios. Ok, great, but what does that mean? What can you do with that data? Well, not much.
Now imagine that you segmented Utah by age, gender, income, and hobbies and found that women in their 20’s with an income below $50,000 who are active runners, overwhelmingly prefer Special K. That data becomes much more valuable when applied to a specific segment. The same idea is consistent with web analytics. The deeper an analyst gets into a segment, the more valuable the data becomes and the more likely it is to induce action. In the words of Avinash Kaushik, “Segmenting allows you to quickly hone in on areas of deeper dive from which will emerge key insights that will drive real and meaningful action.” 
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The deeper and more precisely you can segment, the better chance of producing data that can actually benefit your company. Segmentation allows analysts to get past the surface and start to truly understand customer behavior, preferences, and engagement. Through this customer understanding, corresponding actions and decisions can be implemented. As stated by Garry Pryzklenk, “Get closer to the customer by implementing non-personally identifiable customer “keys” that can help turn “unique visitors” into “customers”.
There are a variety of general segments that analysts can use to segregate their data. For example, looking at paid search vs. organic can be very beneficial in looking at the different behaviors between the two groups in terms of customers you are paying for and customers that are “free”. However, it is when analysts dive beyond the general segments that a lot of critical data starts to materialize. 
When focusing on more specialized segments, in can often be difficult to know where to start and how to group customers. Avinash Kaushik recommends focusing on three different categories: 1) Acquisition 2) Behavior 3) Outcome.  Using these categories as guidelines, analysts should then pick subcategories that relate to direct organizational goals and issues within the company. With these three categories in mind, Kaushik recommends the following process :
- Ask the question to identify what's important / high priority for the business.
- Create a segment (and then micro segments) for that one thing.
- Apply on the relevant reports to measure performance using key performance indicators.
- Take action. It will have an impact!
Garry Pryzklenk states that, “Aligning with the business equates to careful attention to detail and making your audience appreciative of analysis and open to change.” Segmenting based on business goals leads to an analysis that is more likely to be well received by upper management. Showing segmented data to your managers and decision makers allows your data to tell a clear story that can easily portray real and meaningful conclusions without an in depth understanding of web analytics.
The bottom line is that segmentation is key to effective analysis. It is how data transforms ideas into actions that can ultimately improve your business. Do you have any other tips on segmenting data?
1. Kaushik, Avinash. Web Analytics Segmentation: Do Or Die, There is No Try!
2. Kaushik, Avinash. Excellent Analytics Tip#2: Segment Absolutely Everything
3. Pryzlkenk, Garry. Top 10 Web Analytics Segmentation Tips