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Five Keys to Effective Customer Segmentation

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Customer Segmentation

We have more data about our customers than ever before.  Unfortunately, only 25% of companies believe they are effectively using the data they have to create better customer experiences.  One way marketers can more effectively use their information is by creating customer segments.  Customer segmentation is the practice of dividing customers into like groups for marketing purposes.  Customers can be segmented based on age, interest, attitudes, spending habits, location and so on.  In this post I want to highlight five keys to effective customer segmentation.

1. Make Segmentation Adaptive

Making segmentation adaptive means customer segments are constantly changing as customer behavior changes.  For example, if you have a segment that represents people who have spent over $1,000 on your website over the last 365 days, this will likely change daily, with new people coming in and people leaving that don’t fit the segment criteria anymore.  It is critical to have the tools in place to always keep segments fresh, as they should be a living thing, not a static list.

 

2. For Major Segments Create Personas

Creating buyer personas is a great way to better understand your customers and create a few broad segments within your organization.  Personas are created as companies look at customer trends, market research, and talk in-depth to their customers.  From there they are able to create a full persona explaining their background, demographics and highlighting motivations to purchase.  When this information is identified and understood, it allows marketers to relevantly speak to this audience.  We have found as some of our customers go through this exercise, they realize they have a few different personas buying the same or similar products with a very different set of motivations.

 

3. Segmentation Isn’t Just for Marketing

As companies invest in creating personas, this information should be shared across the entire organization.  Many companies use persona information to create new products and address customer needs and wants they hadn’t seen before.  This understanding of the customer can be shared across executive, product, customer service, and other teams within the company to holistically improve a customer’s interaction.

 

4. RFM Analysis Allows for Effective Segments

RFM (Recency, Frequency, and Monetary) Analysis could and should be a blog post on it’s own.  This analysis allows companies to rank customers based on three distinct characteristics – how recently they purchased, how often they purchase, and how much they spend.  This is a powerful tool as it allows marketers to watch macro and micro customer trends and easily create new segments.  For example, customers who score high in each of the three categories could easily fit in a segment called “Top Customers.”  Customers who score high in frequency and monetary, yet low in recency could be a customer segment called “Rescue Customers,” and would then be the object of campaigns to bring them back to the store.  Understanding this information allows marketers to more simply understand customer behavior and create segments relevant to their business.

 

5. Predictive Segmentation is Needed

After companies conquer the basics of customer segmentation it is highly valuable to move towards a predictive analytics model.  Predictive analytics uses technology to analyze large sets of data and find relevant patterns that predict how customers will react to certain interactions and offers.  This allows marketers to move even closer to one-to-one customer interactions.  While traditionally this technology has been reserved for large companies because of the investment required to effectively enable it, we at Oro are working hard to offer this capability to mid-market companies who need these technology-enabled marketing tools to compete in a new world of enhanced customer experience.