Customer segmentation is relevant and important in order to make or sell a product or service. It’s a precursor to any marketing plan. This article covers the phases of development of customer segmentation, from planning to implementation stage with various illustrations and segmentation matrix.
Customer segmentation is the practice of dividing a customer base into groups of individuals that are similar in speciﬁc ways, such as age, gender, interests, spending habits. Segmentation helps businesses to understand markets effectively and allocate resources optimally.
NEED FOR SEGMENTATION?
Segmentation helps one better understand various customer types and their relative importance to one’s business. It gives the ability to differentiate the customers, to communicate, to target and to measure the segments for different marketing activity. It provides a framework to allocate marketing budget more effectively by monitoring the effectiveness of one’s marketing strategies. Good segmentation leads to better marketing by taking consideration of each customer segment.
WHAT ARE THE DIFFERENT WAYS TO SEGMENT?
There’s no right way to segment. The approach depends on availability of data on what one is trying to achieve. Common approaches to segmentation are:
Planning is a key stage in segmentation development. The initial step is to make it clear what you are attempting to accomplish. Helpful queries include:
The development process includes; understanding the problem, considering the distinctive methodologies, looking into the alternatives, and picking the best alternative for your business. The beginning point is understanding the data. Perform both univariate as well as multivariate examinations, to comprehend the information.
The implementation strategy should consider how frequently the segmentation should be run – all the more every now and then for quick evolving situations (month to month). Consider new customers also, how they are to be taken care of in the segmentation e.g., put into a beginner fragment for the initial three months. Track historic segment allocations so that all marketing is on the same page and targeted to the same segments.
MEASURE AND REVIEW
As customers and business sector environment changes, segmentation needs to change to reﬂect this. True value of segmentation comes from the measurement of results and review of the process so it can be improved to enhance marketing efforts. Measure and report the key measurements for all periods and segmented buckets.
REAL WORLD EXAMPLES OF HOW SEGMENTATION CAN BE — USED FOR TARGETED MARKETING.
We perform different types of segmentations which are as follows.
This is a value-based segmentation which is performed on customers based on their spends and frequency of shopping. Our clients don’t want to treat all of their customers in the same way. They want to incentivise a customer who visits them frequently and spends more compared to a person who visits once in a year and spends very less. Such differentiation is possible by RFM segmentation.
Initially we segment the customers into active and dormant shoppers and proceed accordingly.
Then we divide customers based on spends and frequency. We allocate them to a low tag or medium tag or high tag based on the cut-offs taken. At the end of this step, you’ll have this grid where customers are divided as follows.
Since maintaining nine different segments for a customer base results confusion, we combine segments with similar characteristics. If you observe the above ﬁgure, customer with spends high and frequency high/medium are combined into a single segment and are referred to as High spenders. Customers with less frequency and low/medium spend are termed as laggards and campaigns are sent very rarely to this segment .
After segmenting the customers, the key performance indicators are as follows:
High Spenders: High spends matched by high and medium frequency
Potentials: Medium spends matched by high and medium frequency + high spends matched by low frequency
Strivers: Low spends matched by high and medium frequency
Laggards: Low frequency matched by medium and low spends
The numbers are just for illustration purpose but closely simulate the real world scenario:
On observation, we can ﬁnd that the KPIs are in an inverted pyramid. It decreases as the segment moves down. The high spenders segment which has only 20% of the population is contributing to 47% of the revenue, whereas laggards who are as high as 27% contribute only to 7% of the total revenue. So using segmentation business can design differential marketing campaigns catering to different segments and their contribution to KPIs.
This segmentation divides customers into different segments based on their behaviour. Behaviour can be anything. Few examples include price point of the customer, whether he purchased high priced goods or low priced goods. It can be based on seasons, whether he is an EOSS (End of Season Sale) shopper or Non – EOSS Shopper. It can also be based on promos, if the customer is a promo seeker (i.e., shops products on discounts) or a non-promo seeker. It can also be based whether he shops during festival season or normal seasons too.
After segmenting the above customers based on their purchase on EOSS and non-EOSS, customers are segmented as follows:
The numbers are just for illustration purpose but closely simulate the real world scenario.
Only EOSS’ are those customers who’ve shopped only in the EOSS period.
‘High EOSS’ are those customers who’ve shopped throughout the year, but shopped for a higher bill amount in the EOSS period.
‘High Non-EOSS’ are those customers who’ve shopped throughout the year, but shopped for a higher bill amount in the Non–EOSS period.
‘Only Non-EOSS’ are those customers who’ve not shopped in the EOSS period.
‘Only EOSS’ and ‘High EOSS’ customers are those customers who visit stores mainly during the EOSS period. So during the EOSS period, we can minimize our campaign spends by promoting the EOSS with Only EOSS and High EOSS segments.
CRITERIA FOR SUCCESS
For segmentation to be successful it must be:
This means that the consumers allocated to each segment should be similar in some relevant way. Consumers in each segment should be similar in terms of needs and/or characteristics.
Each segment of consumers should be relatively unique, as compared to the other segments that have been constructed
Measurements are very important to be able to evaluate the overall attractiveness of each segment. We can apply test and control methods to check which segments are performing better
Segmentation should be easily deployed and understood by the business. Business should be able to implement a distinctive marketing mix for each market segment
Nishit is working with the Consulting-Econometrics and analytics research team at Hansa Cequity and is based out of Mumbai ofﬁce. Nishit is a data science enthusiast and is trained in data science and business analytics from IIM Bangalore and LSE. He has worked as an economist with RBS and UBS and as a consultant with NCAER before joining Hansa Cequity. He can be reached at firstname.lastname@example.org
Varun is an alumnus from IIM Trichy and currently working with the analytics team at Hansa Cequity. Prior to joining Hansa Cequity, he worked with Infosys. He leverages his skills to explore more meaningful avenue for analytics with the clients at Hansa Cequity. He can be reached at email@example.com