Data as a service: Now’s the time to prove its value to customers

Data as a service: Now’s the time to prove its value to customers

Data is a privilege and not a right – and it’s now time to show consumers that you’re taking their data seriously by using it to help them, much like Uniqlo does.

If you had concerns about the effect that General Data Protection Regulation (GDPR) enforcement had on your customer reach, it’s worth asking yourself why your customers might not have given the green light for you to keep their information.

Naturally, there were plenty of apathetic reasons why consumers may not have responded positively to your GDPR-themed marketing emails:

  • They only ever shopped with you once, e.g. signing up with the promise of a one-time discount;
  • Your email had a permanent residence in the spam folder from a lack of interaction or habitual deletion; and
  • As countless businesses simultaneously asked for permission to retain data due to GDPR, you were simply lost in the crowd.

But while these don’t seem to be particularly damning reasons for you to lose out on customer data, in reality, they’re among the worst of them all. Customers with no opinion of your brand, or any meaningful, long-lasting engagement with your company may as well be counted as consumers that actively don’t like you.

Consumers are more precious about their data than ever, not least because of horror stories on the Cambridge Analytica scale (despite, of course, this largely being information they’re willing to share through social media). But demonstrating that their data is being used by your company for good, helpful reasons – instead of just emails and other marketing efforts – is imperative to retaining it, as you not only build loyalty but, as several companies have shown, it can also enhance your product offering.

Uniqlo's high-street presence is often very blatant.

Uniqlo by name, unique by nature

One such brand using data incredibly cleverly is Japanese fashion retailer Uniqlo, which continues to make waves in the UK. While its high-street presence continues to develop, it offered 11 stores in London alone by September 2018 – one for every year it had been on British soil. For the uninitiated, Uniqlo specialises in stylish yet simple, functional clothing, and its prices compete with H&M, Topshop and New Look – despite offering arguably higher-quality clothing. Queues often run out the door, whether it’s for a new store opening, or just another Thursday in February.

One major reason for its success is how Uniqlo has collaborated with designers and companies as diverse as Disney, Pharrell Williams, Lego, KAWS and Nintendo. As a result, its limited-run ranges sell out fast, but are regularly replaced with new alternatives, and at a rate more akin to TK Maxx than Asos – making visits to its website more regular than a monthly browse for its fans.

Pharrell Williams partnered with Uniqlo.

Personal fawning aside – though there’s a lot to love about the company on an objective level too – it’s Uniqlo’s approach to customer data that truly enhances the experience.

As it mostly operates in the UK as an online retailer, the company is aware of the hurdles it faces when bringing a new audience on board, especially one that’s not used to its product sizing. Speaking from experience, Uniqlo’s men’s clothing tends to reflect US sizing rather than European, which may go against UK customer expectation that a Japanese clothing manufacturer would make smaller-than-usual clothing, reflecting its domestic market.

While it offsets its larger sizes by offering most products in XXS to XXL, its unique measurements will inevitably lead to increased returns. Luckily, it only stocks its own products, immediately making things easier when explaining its sizing.

Data as a service

Naturally, Uniqlo provides the industry-standard sizing chart. Yet for many of its core products, which use the same base sizing (e.g. T-shirts), it has harnessed the power of customer data from both successful and return orders, as well as reviews, to inform buyers of the best fit for them.

By using its “find your perfect fit” function, men are questioned over five simple stages:

  • Height and weight (with options for imperial and metric measurements);
  • “Belly shape”, from three options;
  • Shoulder broadness, again from three choices [hips for women, alongside bra size];
  • Age, as it “has an impact on how your weight is distributed”; and
  • Fit preference, with seven choices between “very tight” and “very loose”.

The

The output is a bar chart featuring sizes ordered by similarly-built customers, splitting options between two sizes that worked for others, avoiding a hard and fast recommendation but always erring towards one over another. Furthermore, it remembers this data when checking the fit of other products.

What’s clear throughout is the transparency with which Uniqlo explains the process, pairing this honesty with a simple UI on both desktop and mobile. This approach makes shopping with Uniqlo easier and more personal, and also underlines its desire to satisfy customer needs, especially new users. What’s more, it endlessly refines this guidance as more data is gathered.

The immediate benefits to Uniqlo are threefold:

  • As Uniqlo collects more information, it constantly improves the accuracy of the data, meaning fewer returns and happier customers;
  • Users feel more confident to shop at Uniqlo due to the fact they’re treated as individuals, leading to return visits and happier customers;
  • Those who have shared data with the company know it’s being put to good use, on both individual and community levels, meaning they’ll happily keep sharing it, leading to happier customers.

If you work for the customer, the customer works for you

Presuming Uniqlo only has standard customer contact data (name, email address and postal address), alongside the exact fit of their customer – something that could be updated with future purchases if a shopper believes their body shape change – then it has all the information it needs to fully tailor outreach to that specific person, meaning it can better recommend something where the size is in stock, or may be more flattering to their build.

If you can mimic this transparent demonstration of the helpfulness customer data can bring them, they’ll be much more willing to share it with you. Be as up front as possible with why you want it, because if you aren’t, you’ll continue to shed your consumer insight on a base level, pushing your customer further away and into your rivals’ laps.

One of Uniqlo's unmistakable store fronts.

Get a strategy to use data properly – and get it in the first place

Before you ask shoppers for their data, you need to make sure you have the tools and people to maximise their value. Now is most definitely the time to invest in data analysis, so you can evolve its value as you accrue more.

There needs to be a purposeful use for this important information before you collect it, and without data scientists and the appropriate in-house machine-learning algorithms to sift through and spot relevant patterns across vast amounts of data – as well as clever CRM strategies to leverage these trends to maximum effect – the data you have may be nothing more than a warm, fuzzy feeling.

Ultimately, your strategy must put the data’s function first. While it feels a bit clichéd to simply say you need to “know your audience”, it couldn’t be more important than in this data gathering exercise: you need to make it perfectly clear to customers that their data adds value to their relationship with your brand.

Common positives to consider in fashion, for example, include convenience, inspiration, sizing or even editorial content. Uniqlo uses its product range and partnerships as an inspirational factor, opting to focus its data use on ensuring people don’t fall foul of its individual sizing. It’s a simple combination, but one that clearly works for the retailer.

By keeping data use both transparent and simple, businesses can focus on other ways to satisfy their customers. Uniqlo isn’t exactly a golden child elsewhere; while it might have mastered a clever and unique approach to data use, it’s still subject to damning reviews for its customer service and delivery. While its “perfect fit” feature will undoubtedly help the company lower the frequency of orders that need returning, it still needs to find a returns policy that perfectly fits the expectations of its new and existing shoppers.

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