It’s no secret: the retail industry is struggling. With people choosing not to spend their money on clothes, retailers need to know where to look.
But while mall stores struggle, fast-fashion giants such as H&M, Zara, and Forever 21 are thriving.
This is in part because of strategies that are based in data and analytics. By understanding what the consumer is craving, these companies can drive sales.
This is not a new phenomenon.
“Fashion, especially ‘mass fashion’ has always been about data,” Anush Prabhu, Partner and Chief Channel Planning and Investment Office at advertising agency Deutsch said in an email to Business Insider. “Retailers see what designs/products of some of the more expensive designers are selling and they then create ‘reproductions’ of those designs/trends. For example,when a quilted bag from Chanel is seen to be trending, a Forever 21 or Kate Spade comes out with quilted bags that are similar.”
Fast fashion companies know the importance of curating data more than anyone.
“Retailers, especially fast-fashion retailers, are always at the forefront of innovation because they work with razor thin margins and are more focused on the direct results/performance of ads than any other group,” James Green, CEO of Magnetic, a company that specialises in providing data to marketers, said to Business Insider.
And the more information that’s available, the easier it becomes.
“Today, given the extent of data available, retailers in fashion can be a few steps ahead of the game — for example, they have access to millions of conversations in social media and can be more predictive of what is going to catch on before it does,” Prabhu said. “Access to shopper behaviour based on weather, mobile data on store visitation, etc. can be capitalised on further to change the game. For example, retailers like Gilt a few years ago started focusing around the time of day when in office browsing activity was the highest — activating against that data changed how people shopped for fashion online.”
And perhaps more obviously, when an e-commerce retailer “suggests” items for shoppers to buy, it utilises data based on the shopper’s browsing and search histories.
Further, this data can also help companies create intelligent, specific marketing campaigns.
“Remaining on the cutting edge involves running advertising campaigns that are knowledgeable about the customer base; these campaigns cannot simply show different ads to different folks based on their “intent,” but also need to target consumers based on their past purchase behaviour, loyalty and other data,” Green said.
For example, this could include using information to create a consistent tone.
“Combining customer information with advertiser outreach is critical for reaching the correct consumer base for a few reasons: First of all, consumers have grown to expect a consistent experience from all brands — and are increasingly happy when technology provides a solution without being prompted,” Green explained. “We see this when Google sends an alert reminding you about your next appointment; for a retailer, it is more subtle but just as compelling. Telling someone that the product they bought six months ago is currently on sale is now a well-received tactic by consumers. The opposite effect occurs when a consumer is still receiving special offers for that H&M bag, the Topshop coat, or any other product that has already been bought. The likelihood of this annoyance happening is reduced or even eliminated if advertising is tied to a CRM system.”
Another way to make sure retailers don’t have misfires is to utilise testing and cull the results for information.
One brand that executes this practice is Adore Me, a fast-fashion lingerie company that has experienced tremendous growth. It was named Inc.’s No. 2 retail company and No. 14 overall company on its prestigious Inc. 5000 list. Inc., which notes that in three years, the company has grown a whopping 15,606%.
Just look at the numbers: in 2012, the company brought in $US1.1 million. By 2013, the company brought in $US5.6 million. And in 2014, it raked in $US16.2 million. (To put it in perspective, this summer, director of business and brand development Sharon Klapka told Business Insider it was on track to out-sell lingerie stalwart La Perla.)
In fact, Adore Me attributes much of its success to its strong marketing, which hits the right note, thanks to its testing practice.
“We A/B test our lingerie models through an A/B testing platform created in-house,” Camille Kress, a business and brand development associate at Adore me, said to Business Insider. “For each set of lingerie, we shoot multiple versions of images to run on our website. The difference between two images might be as simple as the model having her hand on her hip or in her hair. For every 1,000 people that come on our website, 500 will see picture A and 500 picture B — we then see which images shoppers click on more and which one leads to more sales.”
Some of the tiniest clues — like how women respond to brunettes more positively than blondes, in Adore Me’s case — can help bring in more sales.
It’s also important to avoid mistakes — especially in the case of a fast-fashion e-commerce retailer, like Adore Me.
“Because lingerie lead times are huge and because we are fast-fashion, it is very important not to have any missteps. We take our crowdsourcing data into consideration when launching new products and collections — which leads to less “fashion misfires” as we can predict better what will work and what won’t,” Kress said.
While fashion giants have wider sets of data at their hands, it’s remiss for up-and-coming companies — especially e-tailers — to think they can count on intuition.
“E-tailers absolutely cannot rely on intuition or what they think they already know. Online fast-fashion brands have a great advantage: easy data collection. This data cannot go to waste and needs to be a constant source of inspiration and a decision-making tool,” Kress said.
And experts agree.
“Without data, marketers know nothing,” Green said. “Humans are terrific pattern matchers, but for us to identify a pattern the data points have to be limited. For example: a flock of birds suddenly taking flight indicates something dangerous might be present. But there is simply too much data available for any individual to spot a pattern. So we need powerful analytical tools available to spot trends, run tests and find out what causes outcomes. For fast fashion retailers who are trying to churn out trends at an even more accelerated rate, utilising analytics in an efficient manner is even more vital to their business model. We all know that the amount of data available today is unprecedented and it continues to grow at an exponential rate. There are amazing insights in that data if you’ve got the tools and the scientists to search for them.”
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