Unveiling Customer Behavior with Extended RFM and the BCG Matrix: A Simple Guide for Business Owners
Understanding your customers is like unlocking a treasure chest for your business. Knowing who they are, how they behave, and what they want can transform your strategy.
What is RFM Analysis?
RFM stands for:
Recency: How recently a customer made a purchase.
Frequency: How often they make purchases.
Monetary Value: How much they spend.
These three metrics have been a go-to for customer segmentation, helping businesses prioritize and target different customer groups effectively.
However, the traditional RFM model has its limits. It misses other important customer habits that could shape your strategy.
Example of data visualization for RFM Model using natural logarithms, log base 10 (Gustriansyah, 2020):
Enter the Extended RFM Model
The Extended RFM model adds an extra layer of insight by including a new factor:
Count Day: The number of distinct days on which a customer made purchases.
This small addition provides a clearer picture of customer engagement. For example, someone who buys small items frequently across many days might be more loyal than someone making a big one-time purchase.
How Does It Work?
Using data from online retail, the researchers behind this study [Gholamveisy S, Shemshaki M, Homayooni S, et al. (2024)], used a clustering technique called k-means to group customers into segments based on their RFM scores and Count Day. Think of it as sorting your customers into personality types.
Layering on the BCG Matrix
Once customers were segmented, the next step was to align these groups with the BCG Matrix. This classic business tool divides products (or in this case, customer segments) into four categories:
Stars: High growth, high engagement. Loyal customers who love your products.
Cash Cows: Steady buyers who bring consistent value.
Question Marks: New or irregular customers with potential.
Dogs: Inactive or disengaged customers.
Mapping customer segments to the BCG Matrix helps you see who’s driving your growth and who needs more attention.
Insights from the Study
After analyzing the data, customers fell into four clusters:
Platinum (Stars): Loyal, high-value customers. Keep them happy with personalized offers and VIP treatment.
Gold (Cash Cows): Frequent buyers with steady spending. They are key to consistent revenue, so focus on nurturing them.
Silver (Question Marks): New customers with potential. Make a strong first impression to win their loyalty.
Bronze (Dogs): Lost or inactive customers. Investigate why they stopped buying and see if you can win them back.
What This Means for Your Business
This approach combines the best of data and strategy to:
Spot high-value customers you should prioritize.
Focus marketing efforts on the right groups.
Improve product offerings based on customer preferences.
For SaaS founders, this might mean tailoring features for your most loyal subscribers or creating onboarding incentives for new sign-ups. For retail, it could shape your loyalty programs or promotional campaigns.
Final Thoughts
Combining the Extended RFM model with the BCG Matrix is like getting a crystal-clear map of your customer base. It doesn’t just show you where you are; it points out the best path to success.
Start small, look at your existing customer data, group it using simple RFM metrics, and see what patterns emerge. Once you’re ready, consider diving into tools like clustering algorithms to refine your segments further.
By truly understanding your customers, you’re not just selling products, you’re building relationships that last.
References:
Gholamveisy S, Shemshaki M, Homayooni S, et al. (2024). “Application of data mining technique for customer purchase behavior via Extended RFM model with focus on BCG matrix from a data set of online retailing”. Journal of Infrastructure, Policy and Development. 8(7): 4426. https://doi.org/10.24294/jipd.v8i7.4426
R. Gustriansyah, N. Suhandi, and F. Antony. (2020). “Clustering optimization in RFM analysis based on k-means”. Indonesian Journal of Electrical Engineering and Computer Science. Vol. 18, No. 1, April 2020, pp. 470~477. ISSN: 2502-4752, DOI: 10.11591/ijeecs.v18.i1.pp470-477
Ready to Unlock the Power of Customer Segmentation?
Your customers are the heart of your business, but are you truly understanding their behavior? With the right data analysis, you can:
✅ Identify your most valuable customers.
✅ Increase customer retention with targeted strategies.
✅ Allocate your resources where they’ll make the biggest impact.
Let me help you uncover these insights with advanced tools like Extended RFM Analysis and the BCG Matrix. Together, we’ll segment your audience, fine-tune your marketing, and grow your business effectively.
💬 Book a free consultation today and discover how segmentation can transform your strategy! Let’s turn data into decisions that drive results.
Listen to this AI-generated explanation, created with NotebookLM, I did minimal audio editing. Enjoy!
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