RFMT Based Segments

Enhance Customer Engagement and Retention

If segmenting your clients or customers by age or geographic location does not create precise enough segments, then RFMT-based segmentation is the right solution for you.

RFMT-based segmentation will enable you to segment customers into more relevant groups, allowing you to better understand each one. The resulting data will be invaluable for future campaigns.

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How behavior based customer data can benefit you

The acronym RFMT stands for Recency Frequency, Monetary value, and Tenure. In simple terms, this segmentation allows for the quick identification and grouping of users into related segments. It is primarily based on customer activity data.

As the acronym suggests, RFMT-Based Segments are designed and created based on the following factors:

  • Recency – How many days ago was the purchase made (the fewer, the better),
  • Frequency – How often the customer makes purchases or the number of orders within a given time period (the more, the better),
  • Monetary value – How much money the customer spends on purchases (the more, the better), and
  • Tenure – How many days have passed since the first order (the more, the better).

RFMT analysis will allow you to identify groups of customers who are likely to buy from you again. It will also provide accurate data on how much revenue comes from new versus returning customers, as well as how to turn occasional buyers into regular customers.

Target customers with campaigns tailored to their relationship with your brand

Many companies face the problem of customers making a single purchase and never returning. RFMT segmentation helps identify customers who have recently purchased but rarely make repeat purchases. Based on this data, targeted strategies can be created to re-engage them, such as loyalty programs or personalized offers.

RFMT segmentation can also help with:

  • Increasing the effectiveness of marketing campaigns,
  • Strengthening trust in your company or brand, boosting customer loyalty and engagement,
  • Reducing churn rates,
  • Tracking the activity of loyal customers, and more.

Segmenting in this way will allow you to tailor your marketing campaigns to different customer or client groups with specific goals.

Testimonials

Goran Pavlovic
BI, Big Data Analyitcs Director @A1 Serbia
5 Star Rating

“As a long-time client and a partner of ThingSolvers, I’ve always been impressed by their practical solutions-driven spirit and mindset, combined with deep expertise in data analytics & data management.

 

What I truly believe sets them apart is their strong commitment to collaboration, paired with a no-nonsense approach—a combination that makes even the most challenging projects manageable.”

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Stefan Cvorovic,
Marketing Director
5 Star Rating

“Anticipating customer behavior and creating strong loyalty programs are no longer future, but the present of modern retail business. Experienced, dedicated, and extremely open-minded professionals from the Things Solver team helped us to dig deeper into our customer database. They developed a powerful tool which helps us to understand our customer’s behavior and provide them the best possible service.”

Oleg Ivanov
Digital Account Manager
5 Star Rating

Our online shop, www.gbs.rs, has been using the Solver AI Suite service from Things Solver for several years, and we are extremely satisfied with the results their AI search tool delivers. Thanks to this solution, our shop’s users can easily and quickly find products that the AI algorithm recommends based on personalization, as well as
products that best suit their needs, significantly contributing to their satisfaction and making the shopping experience seamless.

 

We would also like to highlight the professionalism and kindness of the Things Solver team, who are always ready to collaborate and quickly adapt the tool to our specific
needs. Every personalization and additional service has been implemented efficiently and within the agreed timelines, which is of great importance to us.

 

Golden Beauty Shop is an online shop where customers can find a wide range of decorative cosmetics from the Golden Rose brand, hair dyes from Elea, MM Beauty, and
Miss Magic brands, as well as hair and hand care products from the Aroma brand. With the support of Things Solver, our team is able to deliver the top-notch customer
experience our shoppers expect and deserve.

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Vladimir Ćuk
Head of Marketing
5 Star Rating

Things Solver has become an essential part of our operations at Gigatron, enabling us to make informed and faster decisions. Their advanced solutions for analyzing website visitor behavior, advanced segmentation, and customer profiling have significantly improved our operational processes, particularly in optimizing sales strategies. Thanks to Things Solver, we have been able to identify key trends, personalize offers, and enhance team efficiency. Their team is highly professional and always ready to provide support, making collaboration with them straightforward and productive.

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Predrag Simic
COO MTEL DACH
5 Star Rating

“We began the cooperation with the Things solver team couple a of years ago, after thorough analysis with whom we want to make our business smart wise. As of then, we have expanded our cooperation in all three countries (Austria, Switzerland and Germany) and the first results have become visible in two months. Planning our sales and retention strategies become an interesting field to expand our strategies through Things Solver Suite.

 

Beginning with smooth onboarding from Things Solver sales guys, through sharing the context of our data with clever and thorough data analysts, I may say that we have become satisfied and much smarter Things Solver clients. Every day, in every respect, we are progressing more and more Together!”

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Sinisa Arsic
Director of Department for Data, analytics and intelligent automation of business processes
5 Star Rating

“Partnering with Things Solver has completely changed the game for us, turning us from a traditional Telecom into a data-powered company that really gets our customers and makes smarter business moves. With their AI skills and cloud data lake technical implementation support, we can try out new ideas fast in the hyperscaler environment
and see results right away. Working with Things Solver means we don’t just understand our customers better; we’re also ahead of the curve with best practices and fresh ideas – because they’ve always got our back with guidance and support, in a very easy-going atmosphere!”

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Aleksandar Popovic
CEO Super Kartica
5 Star Rating

“Working with Things Solver empowered us to start transforming our business from being a marketing platform to a data-driven organization that utilizes data to build up
customer relationships and make better business decisions. With Things Solver Suite you can test and learn quickly. Learn not only what your customers want, but also learn best practices in the business, because Things Solver guys won’t let you out in the dark. They are always there for us to support, advise and deliver! As important as all beforementioned – working with you guys brings so much fun and joy!”

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Irena Radakovic
Head of CRM and Analytics
5 Star Rating

“Collaboration with Thing Solver is a comprehensive journey which leads from discovery to delivery. Their rapid adoption of the latest market trends and receptiveness to our needs, combined with friendly conversation, brought us added value in a relevant business context. Keep it up!”

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Frequently Asked Questions

Find answers to the most common questions you may have.

RFMT segmentation provides better understanding of your customers, increases loyalty, improves the effectiveness of marketing campaigns, helps retain profitable customers, and reduces unnecessary spending on inactive customers.

Using RFMT, you can precisely target customers based on their specific behaviors and value to your business. For example, you can create special offers for customers who have recently purchased or encourage those who haven’t bought in a while to return.

Typical RFMT segments include:

  • Best customers: Those who buy frequently, have made a recent purchase, and spend the most.
  • At risk of leaving: Customers who used to buy often but haven’t made a purchase recently.
  • Inactive customers: Those who have made only one purchase or are very inactive.
  • Potential loyal customers: Customers who have recently made a purchase and shown interest but haven’t yet bought frequently.

Purchase data is key – including the date of each transaction, frequency of purchases, total spending, and time intervals between purchases. This data is used to calculate RFMT metrics for each customer.

Implementing RFMT segmentation requires tools to analyze customer data. Our platform automates this process, allowing you to quickly and easily segment customers and create successful campaigns.

By segmenting customers based on their value and engagement, you can target the most valuable customers, encourage less active customers to buy more frequently, and reduce investment in low-conversion segments. This approach directly leads to increased sales and better Return on Investment (ROI).