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What Is Customer Segmentation?

May 3, 2017 at 4:16 PM

Effective communication helps us better understand and connect with those around us. It allows us to build trust and respect, and to foster good, long-lasting relationships. Imagine having this ability to connect with every customer (or potential customer) you interact with through communication that addresses their motivators and desires. In this blog post, I take a brief look at ‘customer segmentation’ and how it can foster the type of communication that leads to greater customer retention and conversion rates.

What is Customer Segmentation?

Customer segmentation is a way of gaining a deeper understanding of your customers by dividing them into clusters or groups, so that those in the same group are similar to each other but are different to those in other groups. Generally, the greater the similarity within groups and the greater the difference between groups, the better or more distinct the segmentation.

Segmentation can be done based on various types of customer-specific data, such as demographics, geography, behaviour or psychographics, for example - and can be applied to both your current or potential customer bases. The types of customer-specific data to base your segmentation on depend on your desired outcome. For example, if you want to gain more insight into how your customers interact with your products or services, you might conduct a behavioural segmentation. However, if you would like to know more about your market by area, such as rural/urban areas, cities, regions, or provinces, you would run a geographic segmentation.

You can always overlay other types of variables to better understand your customer segments. For example, suppose you have a behavioural-based segmentation. These segments can then be overlaid with demographic information to determine their most likely age, income or gender distribution. If, however, you had a demographic-based segmentation, you could overlay these segments with psychographic data to find out what each segment is likely to value the most or be the most interested in.

What type of techniques can be used for Customer Segmentation?

There are several techniques that can be used for customer segmentation, from the more simple k-means algorithm to the more advanced model-based clustering.

The method to employ will depend on a number of factors, such as:

  • the type and amount of data you have;
  • how you define the resemblance of individuals; and
  • whether you want an unsupervised or semi-supervised approach

Different techniques can lead to different results, with each one having pros and cons, so it is important to have a strong argument for your chosen methodology up-front.

After segmenting your customer base, and analysing the resulting clusters, you should have a better understanding of who your customers or potential customers are. For example, you may have greater insight variables such as:

  • their age, gender, and income;
  • where they live and work;
  • what their preferences and needs are;
  • what they are buying and where;
  • what media they are consuming; or
  • what beliefs or opinions they have.

Having this additional information will help you identify which customers to target, how much potential these customers carry, and how or where best to communicate with them.

The Benefits of Customer Segmentation

Targeting the right customers with the right messages at the right time can pay off in various ways, such as higher conversion rates, higher average order values, and increased profits.

This can be seen in a recent study done by MailChimp which shows how segmenting your email base improved open and click-through rates in segmented campaigns compared to non-segmented campaigns by over 14%. In another example, an online retail company saw their conversion rate (where conversion is defined as a purchase) improve by 208% following a simple segmentation to their email list. 

In addition to the above factors, targeting the right customers in a manner that resonates most with them can also lead to:

  • brand advocacy and word-of-mouth advertising;
  • valuable product insights;
  • improved customer retention and new customer acquisition;
  • decreased churn rates; and
  • greater overall customer satisfaction.

Porsche successfully segmented their target market and directed their efforts to a portion of the market that they had otherwise missed. This saw an increase in sales year-on-year since the campaign was launched. 

Customer segmentation allows you to gain deeper insights into who you customers or potential customer are. Having this additional knowledge will help you to send out personalised and more effective messages to better target the customers with the highest profitability potential. Not only will this help drive up profits, but will also leave your customers feeling more appreciated and will build the foundations of good, long-lasting relationships.

 Need some help with your customer segmentation? Read about our Customer Analytics consulting offering here. Or, if you want to go a step beyond - read about our Insight-as-a-Service offerings for Customer Growth or Customer Retention.

Learn more about our Insights-as-a-Service analytics engine, Genius.

Megan Wilks
Megan Wilks
Megan Wilks is a consultant within the Decision Analytics team at Principa. Prior to joining in 2016, she worked in the consulting and data analytics field, covering a range of industries, including retail, credit and non-profit in Southern and East Africa.

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