The Challenge

In this day and age where the industries are battling a cutthroat competition to keep their target customer intact and garner a new customer base, one of our clients who is a leading apparels store in the USA with a customer base of 1000 customers wanted to adopt a strategic approach to market their business. They faltered to find the right customer base to market and sell their goods. Their problem was not a novice one.

We helped him to offer and intently analyze the buying habits of his target customers and discern what his customers were looking to buy or what they would buy in the future, through thorough study and summarization of the charts and graphs of their buying habits. This analysis technique gave them an edge over his competitors in the industry.

By understanding the target market, the client could increase the business by
75%

The Solution

Implementing RFM based customer segmentation

We employed our analytical techniques to identify the purchasing patterns through the customer segmentation model. Through this model, we focused on categorizing the customers based on three key performance indicators, also known as KPI.

  • The first indicator is Recency. It analyzes the freshness of a customer’s activities in terms of its purchase and visits.
  • The second metric is the Frequency which answers the question – how often does a customer purchase from your business?
  • The third KPI is the Monetary indicator which is the purchasing power of the customer.

How RFM based customer segmentation helped our client?

Analyzing these factors helped our client to categorize his customer base into different segments. By understanding these factors, our client judiciously planned his marketing strategy to target his different customer segments. This empowered him to serve his customers with precisely what they are looking to buy, when they are looking to make a purchase and how he can convince customers to make a purchase.

How did we identify customer clusters based on the RFM segmentation?

We helped our client to identify his customers and segregate them based on their purchasing activities. This allowed him to strategize his marketing activities and plan ways to revive the purchasing activities for each of the customer clusters. Based on the customers’ purchasing activity, we broadly categorized them into the following:

Champions
Potential Loyalists
New customers
At-risk customers
Hibernating customers
Lost customers

Understanding the system better

The customer segmentation system for our client elucidates the RFM score of the customer cluster. The recency, frequency, and revenue cluster has been graphically put together and summarised.

Front-end built in
Back-end developed in

This system helped our client to assist in strategizing his custom marketing plans as the system drew insights from the clusters assigned to customers based on their score.

The system also comprises the product dashboards and product insights and helped our client to know the highest and lowest performing products based on varied criteria like

  • The product price segmentation
  • The product material segmentation
  • The product gender segmentation
  • The product category segmentation
The customers who have given recurring business within 2 months of channelized marketing efforts.
68%
Within a quarter the company increased its revenue by
74%
Target-based product selling increased by
83%

How did customer segmentation influence business decisions?

Based on the customer segmentation, our client was able to shoot periodic emails to his customers who were inactive on his web store for over a month with new lucrative offers or products.

  • Our client tracked down the top 20% of his best-performing customers with the analysis of his customer base and the revenue generated.
  • He sent them a monthly email with special discounts and coupons. This helped him create a channelized automated marketing for his customers, who generated most of his revenue.

Based on his customers’ data through their registered profile and their purchasing pattern, our client accessed the customers’ data and used them to custom market his products to them. With the changing profile and custom fields, our client could tweak his marketing strategy for his customers accordingly.

The customer segmentation and analysis allowed our client to identify the most popular products with a particular segment of his customers. This allowed him to promote particular products to a specific customer base segment, thus boosting the sales and revenue generated.

We segmented our client's customers into the slots who viewed products in a particular time period. If they haven't purchased in a couple, of days, we suggest a few products to convince them to make a purchase.

HP Consulting

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