Social media and POS data key to fast-fashion insights

  Lori Mitchell-Keller

By Lori Mitchell-Keller, Senior VP and Head of Global Retail, SAP

When is the last time you told a big-name fashion brand what you wanted them to design and sell?

As it turns out, we [the customers] are telling them all the time. In fact, more often than not, big-name fashion brands are looking to customer behaviors and social commentary to dive into the consumer mindset. From there, they gain insight to the styles consumers want to wear, what colors shoppers like and even which celebrities they trust when it comes to must-have fashion items. 

Many brands are still playing catch-up from the days when they set the trends. Now that the tables have turned, a lack of real-time insights into consumer preferences has forced some brands to chase the trends instead of capitalize on them.

Mining the depths of social sentiment is one way to access insights. But to truly understand how fashion data can help drive real-time design decisions, brands need to correlate sentiment with historical demand data from POS and syndicated data.

What are the hot trends this summer?

SAP recently tapped our social sentiment team to demonstrate the potential of mining fashion-forward insights from social media. The results identify this summer's top fashion preferences trending around the globe based on social media commentary.

Tried-and-true black and white was the top color combination mentioned globally, followed closely by blues in many hues. While these colors were at the top globally, tastes still differ in individual markets.

While North Americans will be stocking up on black, white and blue this summer, Eastern Europeans love metallics, and consumers in the Greater China region are all about the reds.

Fashion brands should also be ready to meet consumer demand for prints this summer. Social sentiment showed animal prints as the clear summer front-runner worldwide. Stripes, polka dots and plaid, however, are on the decline, so fashion brands should stick to the exotics.

How fast is your fashion?

While trends differ, the way retailers can leverage consumer preferences is universal. Fast fashion relies heavily on the ability to quickly translate consumer demand into merchandise on the shelves. In fact, fast-fashion retailers live by this—through a process of quick-turn design and production; inventory optimization that supports fast turnover; and integrated marketing, merchandising and pricing strategies that move product out the door.

Relying on social sentiment alone can inform broad trends and directions for product. Like the analysis shows, brands can focus on colors and fabrics to drive design concepts. Correlating social sentiment with historical demand data from POS and syndicated data helps brands determine whether significant changes in consumer sentiment—positive or negative—will contribute to corresponding swings in actual purchase behaviors.

By using the right tools and partners, companies can collect and analyze real-time consumer data through an efficient and automated process. Feeding the supply chain, production and marketing teams' insights that show what consumers said they wanted on social media, in comparison to what they actually purchased, can help brands develop better risk and cost profiles. It also sheds light on inventory management practices to make better, more informed decisions on production and stock. 

When these insights are pushed through to the retail channel, manufacturers and retailers can customize and streamline in-store promotions for success in various regional markets and more accurately time price markdowns. This leads to increased inventory turnover and customer satisfaction—all critical in today's fast-fashion environment.

In our social age, consumers are constantly talking about how they plan to spend their money. Fashion brands can, and should, take advantage of these conversations in a way that can help meet consumers' increasing expectations of fashion-forward, fast and convenient shopping experiences.

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