Customer segmentation

Learn about an exciting new module coming soon to Phocas.

Customer segmentation, a core feature of the Insights module, automatically analyzes purchasing behavior to group your customers into meaningful segments and uncover key insights. The insights update as your data changes, so there's no need for manual recalculations.

Whereas you might already have a clear picture of your top customers and have strong relationship with them, it’s likely you don’t know much about those customers that don’t buy often or much from you. You might not be aware of potential risks of losing customers.

These insights give you a better understanding of all your customers, helping you to quickly answer key business questions and take informed, targeted actions to drive retention, loyalty, and growth.

Get started

In the navigation menu, click Insights, then select the required database. Insights opens on the Customer segmentation page.

Take a tour of Customer segmentation

The Customer segmentation page is organized into three sections, as identified by the numbers in the image and explained below.

1. Segmentation summary: A quick overview of your data. It shows the total number of customers who were active within the selected period (by default, the last 12 months). The summary cards on the right highlight the total sales value and the total number of active customers, so you can quickly understand the overall scale of your customer base and sales without digging into detailed data.

2. Segmentation chart and details: A visualization of how your customers are grouped based on their buying behavior, with supporting details.

   • The chart visually groups your customers into segments (Champion, Loyalist, At risk, and so on) based on how recently and frequently they buy and how much they spend. You can quickly see how many customers sit in each segment and how much revenue they represent.

   • Each block in the chart contains the segment name and number of customers in that segment. The size and position of each block corresponds to how that segment is structured (thresholds). It bears no relation to how many customers are in the segment. For example, segments higher on the chart show higher sales value; segments further right are more recent buyers.

   • When you click a segment, its details are displayed on the right side of the chart. See Analyze the insights below to learn more about using the chart.

3. Segmentation summary table: A table that gives you a high-level view of all the segments. It’s a quick way to compare the following metrics across all segments: Number of customers, average sales value, and total sales value.

Understand the segmentation

To understand how the customers were segmented, and the chart was created, click the purple Information button next to the chart section header. This opens the Segmentation setup where you can see a table of the RFM thresholds configured for the underlying database, along with descriptions and supplementary information. The RFM thresholds are grouped into five buckets (range 1 to 5). It's these thresholds that determine the size and position of the segments in the chart.

Learn more about how your data is segmented

The Customer Segmentation feature uses the Recency, Frequency, and Monetary (RFM) model to group your customers into meaningful segments and provide instant insights into customer behavior across their purchasing journey.

The RFM model is an industry-standard analysis technique. It’s often used to manage customer accounts. As its name suggests, this model uses three key metrics to assess and rank customer behavior, as described in the table.

Metric	Definition	Why it's important
Recency	How recently did the customer make a purchase?​Higher threshold = more recent	Customers who purchased more recently are more likely to buy again, compared to those who haven’t purchased in a while. They're also more likely to reactive positively to marketing campaigns and promotions.
Frequency	How often does the customer make a purchase over the time period?​Higher threshold = more recent	Frequent buyers are generally more engaged and satisfied, therefore, more loyal and valuable to the business.
Monetary	How much did the customer spend over the time period (total spend)?​Higher threshold = more recent	Customers who spend more are typically more profitable and worth nurturing. Combining monetary value with how recently and often a customer buys can help identify loyal, high-value customers.

How Phocas applies the RFM model

Phocas analyses the data in the selected database within the specified time period (the default is the last 12 months). It scores the customers on each of the three RFM metrics, on a scale from 1 to 5, where:

• 5 = highest recency, frequency, or monetary value.

• 1 = lowest recency, frequency, or monetary value.

It combines these scores into an overall RFM score from which it builds a 3D model of your customers’ behavior:

​ To present these segments more clearly to you, it converts the 3D model into a 2D chart.

Analyze the insights

After taking in the summary insights, you can drill deeper into the data to get more insights and answer questions.

View segment details

Hover over a segment in the chart to get a brief overview in a tooltip.

Click a segment in the chart to view its details on the right side of the chart.

Filter the data

Filter by a dimension, such as Territory, Sales Rep or Product, to narrow your focus to a specific area. For example, if you're a sales rep, you can filter to focus on your individual customers and see where you need to spend your time, who to call, and where to grow.

Click the Filter button in the top-right corner, then select the required dimension from the list. You can apply multiple filters to further refine the data. The segmentation chart updates to reflect your applied filter(s).

Take action

While the segmentation helps you understand different customer behaviours, it’s the follow-up actions that drive results.

The insights allow you to tailor business strategies to each segment, allowing you to:

• Make the most of your loyal and high-value customers

• Support newer customers who show potential

• Reconnect with those who might be drifting away

• Adjust your outreach to better match where each customer is in their journey

Examples of actions you can take include:

• Personalized marketing: Tailor campaigns based on each customer segment. Send the right message, to the right customers at the right time.

• Customer retention: Identify at-risk customers and re-engage them to drive growth. Predict and prevent customer churn.

• Resource allocation: Focus efforts on high-value customer segments at scale.

• Product recommendations: Suggest products based on buying behavior patterns. Note: Phocas is actively working on enhancing this area - watch out for new functionality coming soon.