Segmentation is not a new concept to retailers. Looking into the analytics framework which has been developed over time, segmentation was traditionally one of the easiest ways to target customers. Ever since the birth of commerce, every retailer has been segmenting his customers based on their gender, class, purchasing power etc. Analytics and segmentation were simply regarded as ‘experience’, ‘trader’s instinct’ or simply ‘gut feeling’. However, with the rapidly changing customer psyche, mere segmentation is not enough. To meet this challenge, statisticians started segregating customers into groups based on multiple dimensions or as it is formally known – micro-segmentation.

Retailers worldwide observed that the response rates for mass campaigns have consistently been very low. Due to this, they revisited the customer databases and started campaigns targeted toward micro-segmented customer pools. India is a 1.2 billion strong country with an intricate mix of cultures and taste, and with the number of options available in market today, the one-shoe-fits-all theory cannot sustain among such diversity. New expectations from customers can be met by providing an offer which is suitable to them and makes them feel special, which can be made possible using micro-segmentation.

In international markets, large retailers have already made headway using micro-segmentation. Retail major Tesco has started dividing its customer pool into 5000 micro-segments with 250,000 personalized offers to target them with. Every retailer has experienced very high returns on micro-segmented campaigns, primarily due to personalisation. It requires minimal investment when compared to other operational investments. To arrive at such high number of micro-segments, it is necessary to validate those segments while drilling down from 3 or 4 segments to 1000-fold more. This is not a one step process, in fact, it is required that it be proceeded in an experimental manner validating each level of drill down.

Marketing has always been an expensive proposition; the marketing managers are finding it very hard with each passing day to justify the cost of marketing and its impact on the business. Print, electronic, OOH – There is a massive clutter across all media which demands a bombardment to get the message through, be it ATL or BTL. On the other hand, micro-segmented campaigns allow the managers to validate each activity and garner profit from each one of them. With any plain vanilla offer, we have observed a response rate of 1.46%, which increases to 2.58% when the activities are personalized and sent to the right customers. Response rate can also go up to 25% based on the number of micro-segments, segment characteristics and design of the offers to that particular segment. Most of the time, running micro-segmented life cycle based campaigns along with loyalty rewards can increase the topline sales by 5 – 10%. Simply put, it’s all about “the right offer to the right customer at the right time”. Due to this, micro-segmentation (personalisation) can also create word of mouth as similar to ATL, but for a lot less money.

Recently, a popular F&B brand who is also a Capillary customer, adopted the next generation of customer engagement solutions for their home delivery business in India. In a complete, end-to-end approach, Capillary Technologies designed separate lifecycle journeys for the different customer type. Based on the available customer data, specific offers were then created for each micro-segment which suited the customer’s taste as well as the purchase behavior. For example, within the ‘Golden Pool Premium’ customer segment, the customers were given a ‘non-aggressive offer’ which has standard discounts and offers which are suitable to the customer’s taste or benefits (in-store promotions) and a customer which is in ‘High Value Explorer’ segment will be given an ‘aggressive offer’ with more benefits if a purchase is made.

Capillary then clustered the customers based on their behavioral indicator such as preferred day and time for ordering – weekday or weekend, lunch or dinner, customer spend etc. and use these to trigger the campaigns. This enabled the F&B client to reach out to the customer when they are most receptive to these offers and therefore increase the acceptability of the offer. For example, using micro-segmentation, Capillary identifies that a particular family of 4 members, often calls on Saturday afternoons to order the food. Using this information, the system can identify the right offer and send an SMS to them on Friday evening or Saturday e.g. Dear Mary, Enjoy your Saturday afternoon with your “favorite food”. Your voucher code is ASD313. Call at xxxxxxxx to place your order now. Within days of the launch, we witnessed a phenomenal increase in the hit-rate across all micro-segments. Customers also found these campaigns accurately relevant and thus responded to each campaign favourably.

Though micro-segmentation is a powerful tool, it also relies on some factors to produce the best results. Ideally, the volume of customer data should be huge. Large data allows the customers to be micro-segmented in a much deeper level, thus increasing the level of accuracy. The diversity of the customer pool also plays a crucial role, varied cultures and characteristics define the different segments much better. The right time to micro-segment is when the market is saturated or retailer is losing to the competitors. These are clear indicators that the customer is asking for a “differentiation” and the campaign response rates are not favorable, thus creating the need to micro-segment and reassess the marketing activities.

It will also help the retailer to identify the right offer from the pool of offers and personalize them as per customer needs. Moreover, it increases the customer retention with a visible rise in the repeat business. Micro-segmentation, when done correctly, can increase the brand loyalty manifolds, within a short period of time, truly bringing the retailer to the next stage of retail evolution – The Personalisation Era.

Kapil Raj
Kapil Raj has been writing about consumer behaviour, consumer businesses and technology in the fintech and IT space.
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