Traditional shopper segmentation treats people as a cohort – a group of people with similar tastes and interests. It focuses on categorizing, labeling, and boxing people, instead of treating them as individuals with specific style preferences and needs. It offers a rather myopic view of categorizing based on limited data points that usually are just broad fragmented categories.
While the term ‘personalization’ is thrown loosely around, not every retailer has managed to utilize its full potential. In most instances, ‘segmentation’ and ‘personalization’ are used interchangeably, despite both being two independent techniques.
When the two terms are interchanged, we hear cases like a shopper being recommended mosquito nets after purchasing one a week back. Or a person waking up to a dozen of promotional emails about baking trays after buying an oven. These examples don’t imply that they aren’t ‘personalization’. It implies that they are ‘irrelevant personalization’, which would be regarded as a failure.
For example, out of the 100% oven buyers, there might be a percentage that needs trays. However, sending all of them a prompt to buy ‘tray’ reflects that the brand has put everyone from that group under one category, instead of mapping their individual needs. This illustrates the outcome of confusing segmentation with Retail personalization.
Real personalization requires brands to invest in AI & automation and prioritize it (not just on paper) to individualize their strategy, understand shopper intent, and provide relevant recommendations that add value in real-time.
Brendan Witcher, VP & Principal Analyst at Forrester Research disclosed that 90% of organizations are going to invest in retail personalization but only 40% of consumers say that the information they get from a brand is relevant to them. He added that one of the reasons for this gap between the brand’s effort and actual results is ‘segmentation’ in the garb of ‘personalization’ as it creates a wrong experience for consumers