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RFM segments
An introduction to Customer Segmentation using RFM analysis
An introduction to Customer Segmentation using RFM analysis

RFM analysis – an industry renowned calculation based on purchase recency, frequency, and spend – to measure customer loyalty.

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Marsello's RFM analysis allows you to target specific customers based on their shopping behaviors based on how recently they shopped, how frequently they shop, and how much money they spend when they shop with you!

What is customer segmentation?

Customer segmentation is the process of dividing customers into groups, allowing retailers to do more targeted and effective marketing. There are lots of different types of segmentation, a few of the most common are:

  • Demographic segmentation: uses common customer characteristics to segment customers based on variables such as age, gender, life stage, etc.

  • Geographic segmentation: uses customers' location to segment customers based on country, state, city, etc.

  • Behavioral segmentation: uses customer purchase data to segment customers based on their activity at your store such as last purchase data, etc.

Marsello uses behavioral segmentation to help retailers identify their most valuable customers and develop effective marketing strategies through the use of RFM Analysis.

Why customer segmentation is important?

Every customer database is diverse. It's made up of lots of different customers that all have different purchasing behaviors with your store. Segmentation allows retailers to send the right message at the right time, to the right set of customers.

Segmentation can help:

  • Understand your business better: know who your best customers are, who is about to slip away, and better identify growth opportunities.

  • Improve customer loyalty: identify your loyal and best customers, and continue to grow these relationships. Identify your repeat customers – these customers have the potential to turn into loyal customers. Ensure their experience with your store is positive and memorable, then following up with timely emails and promotions will grow your relationship and encourage them to shop again.

  • Improve your email marketing: send targeted emails to specific segments and get better results. Customers are more likely to engage with targeted emails, increasing open rates and click-through rates, and resulting in decreased negative reactions to your emails; this, in turn, increases conversion.

  • Minimize marketing costs and improve ROI: identify valuable customers and focus their marketing efforts. Un-targeted marketing campaigns can be costly and ineffective. Identifying key customer segments and using their data to create relevant and targeted campaigns will reduce costs and increase conversion.

How are the customer segments calculated?

Your customer segments are calculated using RFM analysis. RFM is made up of 3 important parts:

  1. Recency - when the customer last made a purchase

  2. Frequency - how many purchases the customer has made

  3. Monetary - how much money the customer has spent

Using RFM, customers can be organized into segments. These segments range from 'Best' customers (very loyal and huge fans of your store) to 'Lost' customers (unlikely to purchase with you again).

When you connect Marsello to your eCommerce or POS site(s), your customer database and order history (last purchase date, total spend, number of orders) syncs into Marsello and distribute customers across the 6 RFM segments appearing on your dashboard.

Segment definitions:

  • Best: ordered recently, ordered the most often, and spent the most!

  • Loyal: ordered recently, ordered often, spent good money.

  • Promising: ordered recently, ordered more than once, and spent an average amount.

  • New: made their first order recently.

  • At risk: haven't ordered recently.

  • Lost: haven't ordered in a very long time.

📝 Note: These segments are mutually exclusive, meaning that each customer can only be in one segment at one time.

Extra eCommerce segments:

  • Window Shoppers: has a store account and has never made an order.

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