Fashion retailers must tackle the ‘flaw of averages’

There is nothing average about the fashion industry and retailers can't rely on average data.
28 December 2018 | 772 Shares

Facade of Ralph Lauren flagship store in Baku. Source: Shutterstock

It’s time for fashion retailers– both apparel and footwear brands– to start considering the ‘flaw of averages’, and the negative impact that using customer average data can have on their businesses, according to Lars Rabe, Managing Director of True Fit Europe.

Average has never been enough when it comes to fashion; it goes with the territory that excellence and high creativity should be pushed to the fore in an industry that is all about expression and excitement, and the same approach must be taken to data collection and analysis, Rabe argues.

Using customer average data when building personalization strategies or targeted marketing campaigns does not do apparel and footwear retailers any favors.

What is meant by the flaw of averages in data?

Data creates opportunities for retailers to both power personalized customer experiences and identify insights that can be used to transform internal operations and the way they do business day by day.

In the competitive fashion retail environment, where the growing fickleness of consumers is arguably at its fiercest, data and the sophisticated use of it has the potential to give brands the upper hand over their rivals.

However, the complex characteristics of individual consumers, products, and changing shopping behaviors are all-so-often oversimplified into concepts like ‘averages’ or ‘segments’ and leave customer experiences as what can only be described as generic and uninspiring.

Many companies looking to aid apparel and footwear brands in their mission to get closer to customers could actually be creating more of a division, by supplying them with generalized data and data management tools that, in all honesty, they probably already have access to if they crunch the numbers in their freely-available analytics packages.

Data that means something

Retailers from Ralph Lauren and Kate Spade at the higher end, to Macy’s and Next in the middle market, are looking to personalize their customer interactions, with the ultimate goal of driving sales and engendering customer loyalty.

All of these diverse businesses are increasingly aware there is no such thing as normal when it comes to people’s body size and style choices, and they are making moves to ensure people shopping online are only served up products matching their individual needs.

This includes enabling customers to make purchase choices based on nuanced data points stretching from the basics like cut, coloring and size to other more complicated details such as how often a product is returned and where fading occurs around pockets.

It is online shopping fuelled by sophisticated data science behind the scenes that allows consumers to make purchasing decisions based on comprehensive information. The ultimate aim is to display options to consumers relevant to their personal behaviors over time. That is online personalization that can only be achieved when thousands of data points are considered.

Fashion is too personal to rely on assumptions based on averages. When a customer finds a garment they really love, it feels like an extension of themselves– that is what all brands should be striving to achieve and, in the process, they will create the compelling experiences their shoppers are seeking.