Do You Know Your Segment Name?
Are you a bit confused? Okay, I’m talking about your CRM segment name. According to the brand at which you’ve been shopping, you have a specific name that you don’t know. Like loyal costumer, at risk, about to sleep, hibernating…
Let’s little dive into the CRM!
What is the CRM?
Customer Relationship Management (CRM) analysis is the process of examining and evaluating data and information related to a company’s interactions and relationships with its customers. CRM analysis helps businesses better understand their customers, improve customer relationships, and make data-driven decisions to enhance customer satisfaction and loyalty.
So how we do segment the customer?
First, we need RFM Analysis.
What is the RFM Analysis?
RFM analysis is the method for the customer segmentation. RFM is formed from the initial letters of Recency, Frequency, Monetary.
- Recency (R): Recency focuses on how recently a customer made a purchase. Customers who have made recent purchases are often considered more engaged and valuable.
- Frequency (F): Frequency looks at how often a customer makes purchases within a specific time frame. Customers who make frequent purchases are often seen as more loyal and valuable.
- Monetary (M): Monetary value refers to the total amount of money a customer has spent on purchases. Customers with higher monetary value are considered more valuable to the business.
After when we reach these metrics, to make RFM metrics more comparable with each other, we need to convert them into scores. RFM scores range from 1 to 5
For companies, ‘Recency’ and ‘Frequency’ metrics are prioritized as they provide more insights into customer behavior and loyalty, thus Monetary value is disregarded.
And Between recency and score there is negative correlation. I mean, Recency : Today’s date — Customer’s last purchase/interaction date, according to this formula, if the result is large, it means it’s bad, and it receives a low score.
Based on the results, let’s return to the title: “What is your segment name? :)
Okey, we’ve covered RFM metrics. Now, let’s shift our focus to CLV!
What is the CLV (Customer Lifetime Value)?
CLV stands for Customer Lifetime Value. It is a metric used in business and marketing to assess the total revenue a company can expect to earn from a customer over the entire duration of their relationship. CLV takes into account factors such as how often a customer makes purchases, the average amount spent during each purchase, and the length of the customer’s relationship with the company.
CLV is a crucial metric because it helps businesses understand the long-term value of their customers and enables them to make informed decisions regarding customer acquisition, retention, and marketing strategies. By calculating CLV, companies can allocate their resources more effectively, tailor their marketing efforts to different customer segments, and prioritize customer relationships for sustainable growth and profitability.
Customer Lifetime Value Prediction
Predicting Customer Lifetime Value (CLV) involves estimating the future value a customer is expected to generate for a business throughout their entire relationship. This prediction is valuable for strategic planning, marketing, and customer relationship management.
In CLV Prediction, we use two model called BG/NBD and Gamma Gamma model.
BG/NBD MODEL
The BG/NBD (Beta Geometric/Negative Binomial Distribution) model is a statistical model used to analyze customer behaviors and predict customer lifetime value.
GAMMA GAMMA MODEL
The Gamma-Gamma model is another statistical model used in the context of Customer Lifetime Value (CLV) prediction. It focuses on estimating the average transaction value or monetary value for a customer.
We have gained thorough knowledge for CRM analysis. In the next article, we will be conducting a practical CRM analysis, so stay tuned…
Big thanks to Vahit Keskin.
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