Regardless of sector, size, or specialty, companies everywhere have one thing in common: They want to get to know their prospects better. By learning more about the pain points, preferences, and even lives of the people interested in them, companies can deliver better experiences that are more likely to entice prospects further down the funnel, converting them into paying customers or subscribers. Segmentation is an excellent tool for companies that want to connect with prospects more personally.
What Is Segmentation?
Segmentation is the technique of splitting a whole prospect or customer base into different groups, or segments. Prospects are placed into groups depending on certain defining characteristics that are likely to affect their behavior in the sales funnel. Groups are defined by characteristics like age, gender, occupation, income, education, family status, location, and any number of other criteria. Different companies in different sectors will have a wide range of additional factors to use in segmentation. Sports websites, for example, can powerfully leverage a data point that's almost totally irrelevant in all other sectors: team or player allegiance.
Segmentation is the heart and soul of optimization testing. The more segments a company researches, the more robustly it can build buyer personas, and the more effectively it can deliver unique, personalized content. (Please note: A buyer persona is often several segments rolled into one; for example, the unmarried, college-educated male prospect in his mid-30s who lives on the west coast and works in software could be Persona C.) Companies can start segmenting many different ways depending on what they want to learn about prospects, what purpose new insights would serve, and how much data they already have their disposal.
Company Research vs. Customer Identification
Some brands attempt to bridge the gap between themselves and prospects with self-identification, which is a type of segmentation that has proven effective. Self-identification, which many Internet users encounter at some point, is what it sounds like: A website asks users to label themselves according to their background, interests, experience, or intended purpose for visiting. An insurance site, for example, may ask people to name the most important factor in their potential purchase—price, coverage, or waiting period—before giving them the right experience for their needs.
Company-conducted segmentation, however, is a better method for prospect discovery than self-identification. When done right, segmentation done by a company itself delves much, much deeper than a simple website entrance quiz ever could. Also, it reveals information about prospects that prospects may not be willing to divulge or may not even know about themselves.
A Couple Key Principles
Companies should keep two things in mind as they attempt to categorize prospects. First: The more segmentation factors they implement, the deeper the insights they'll gain. Therefore, while it may be tempting to run simple tests with binary results—discovering if a page performs better with women or men, for example—analyses like this can be too rudimentary to reveal anything of long-term significance.
Markets should attempt to bolster the commonplace factors like age and gender with more intricate ones, which may relate to prospects’ personality or lifestyle choices. To quote Adele Revella, CEO of the Buyer Persona Institute: “Too often, buyer profiles are nothing more than an attractive way to display obvious or demographic data.” So, move away from the basic and self-evident: Leverage factors that uncover specific, perhaps hidden information about prospects.
This brings us to the second key principle of segmentation: The more options available for each factor, the better. In other words, while income is a good segmentation factor, the more detailed an answer could be for the question it represents—"What is this prospect's income?"—the more valuable the resulting data.
For example: Using “high,” “medium,” or “low” as potential options for the income factor makes it easier and less resource-consuming for companies to segment each individual prospect. However, the simplicity of these potential answers also means the data companies gain will be less granular. A more detailed list of answers might break a prospect’s income out into ranges: “$40,000-49,000,” “$50,000-59,000,” and so on. A company would have to think long and hard about the size of the ranges it employed, as well as the number of ranges it wanted to measure. But it would get more descriptive data by using a number of specific ranges. Later, if it wants to consolidate these ranges into more straightforward "high," "medium," or "low" labels, it always can.
At Maxymiser, we recommend clients have between eight and 10 options for each factor, when possible and reasonable. This ensures factors are sufficiently detailed but also protects against companies’ receiving more data than they can use.
Never Stop Segmenting
Segmentation is an ongoing process. Buyer personas aren’t meant to live forever, unchanging; they’re dynamic, representing people in the real world, so they’ll always need tweaks, clarification, and deeper dives. Once companies have a solid foundation of segments upon which to build their buyer personas, they can begin optimization testing into the preferences and behaviors of those personas . But there will always be more to learn about existing segments, and there will always be new segments to discover.