New Capabilities from Springbot Helps Merchants Analyze Customer Value to Better Drive Sales

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Springbot automates RFM modeling to help online merchants segment and tailor messages to quickly target their most valuable customers

By automating RFM modeling and providing it directly through Springbot’s dashboard, we simply and easily present analytics to merchants with advanced customer data that was once reserved only for large retailers.

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Springbot today launched RFM Segments as a way to help retailers streamline the process of segmenting their customer purchase data so they can better meet consumers’ increasing expectations for personalization.

RFM Segments — a feature which automatically groups customers based on the recency, frequency, and monetary value of previous purchases — help online merchants quickly identify their most valuable customers and develop targeted email campaigns to reach those customers groups. Merchants have long needed the power of RFM segments to personalize messages. Whether the offer is free shipping for large orders or a discount off the total purchase, the RFM model matches the right offer with the right buyer in an attempt to maximize sales.

The RFM segmentation model is proven to help retailers uncover how groups of customers behave. Armed with this knowledge retailers can drive more sales, increase profitability, and strengthen customer loyalty because the RFM model analyzes three key criteria:

  • Recency: When a customer last placed an order
  • Frequency: How many orders a customer has placed over a period of time on a per store basis
  • Monetary: How much the customer spent, i.e. lifetime purchase amount

Springbot streamlines and automates the segmentation process by examining a merchant’s customer data and providing a historical picture of customers’ behavior. This is used as an indicator to predict future purchase activity. Each segment is ranked on a scale from high to low on each criterion then placed in one of nine segments based on their score.

“Retailers understand that within their customer purchase data is knowledge that if tapped into would create immediate business value, but they lack the time to take on the daunting task of manually developing an RFM model,” said Erika Jolly Brookes, CMO at Springbot. “By automating RFM modeling and providing it directly through Springbot’s dashboard, we simply and easily present analytics to merchants with advanced customer data that was once reserved only for large retailers.”

The Springbot RFM data breaks down into nine RFM segments within the Springbot dashboard. The segments are:

  • All Stars – Coveted customers that bought recently, buy often and spend a lot.
  • Most Loyal – The most frequent purchasers.
  • High Rollers – Purchases who spent a lot of money over their customer lifetime.
  • New Money – Customers that made significant purchases on their first order.
  • Old Faithful – Trusted customers that buy often, but tend to have a low average

order value.

  • Blue Moons – Occasional customers that don’t purchase very often, but spend a lot

when they do.

  • Long Shots – Customers that spent small amount, purchased very few times, and

last ordered a long time ago.

  • At Risk – Customers that have not made a purchase in a while.
  • Lost Customers – Customers that have stopped purchasing.

“The customer data paints a historical picture which can be used as an indicator for future activity, upcoming marketing strategies, and as a key driver for sending personalized email offers to each segment,” said Brookes. “This strategy helps retailers make the leap from knowing anecdotally about their customers to really understanding their customers' buying potential.”

As email lists grow with new customers and prospects, segmenting these lists into manageable groups becomes critical for personalization, addressing customers’ interests, and driving sales. Utilizing RFM segmentation provides retailers with the data they need to send focused and personalized communications in an effort to identify the customers with the highest RFM score and target them with exclusive VIP offers – thus engaging valuable customers and growing their business.

To learn more about Springbot’s RFM segments, visit http://www.springbot.com/2016/02/springbots-rfm-segments/.

About Springbot
Springbot delivers an eCommerce marketing platform to small and medium businesses that has combined the power of marketing automation and marketing analytics to deliver its Marketing Robotics service. The cloud-based offering integrates and makes simple the data, content and multi-channel marketing tools (social, online, email, etc.) eCommerce website owners need to drive more traffic, conversions and revenue. Springbot helps eCommerce Shopify and Magento merchants grow their revenue by taking smarter, data-driven marketing actions.

To learn more information about Springbot, please visit http://www.springbot.com/.

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