Social Data in the Fashion Industry – Recap

 

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Fashion, Data, and Social Media: The Findings from BBI’s Latest MeetUp

Fashion is never finished and neither is the data that helps the world’s biggest fashion brands make informed decisions about their audiences and their products.

That’s why we decided to explore the topic in-depth with the help of our friends at Big Boulder Initiative (BBI). Co-hosted by Bitly and Brandwatch, experts from both organizations and Gilt came together to dig into the numbers behind some of fashion’s biggest trends in this year.

Taking Networks Seriously

An October report from Brandwatch analyzed trends, topics and audiences for Twitter and Facebook conversations surrounding top luxury brands like Chanel, Dior, Calvin Klein and more. What was the key takeaway?

99.63% of the conversation is driven by consumers, according to Paul Siegel, data scientist.

And what do we know about those consumers? They’re overwhelmingly female, for starters.

The report also breaks down the types of professions tweeting most frequently about these brands. Artists, executives, students, and journalists top the list. Brandwatch also found that these people tend to rally around other interests like music, sports, and family and parenting.

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This chart looks at the type of clothing people were talking about, as well as their color preferences.

After considering the 30,000-foot view, it’s important to look at the local story, according to Siegel. Brands have to begin considering more targeted questions like: Who are the movers and shakers in the conversation? What are their spheres of influence? What content is being shared and how?

Unlocking the Power of the Link

In a survey featured on Social Media Today, 78% of respondents said that companies’ social media posts impact their purchases and 4 in 10 social media users have purchased an item online or in-store after sharing it or marking it as a favorite on Twitter, Facebook or Pinterest.

With a number of the world’s major fashion brands using our enterprise product, Bitly has access to a wealth of data like the types of devices consumers are using, what days they’re most active, and what social channels are getting the most love. And sometimes the data can surprise you.

Caitlin Rashbaum, customer success manager at Bitly, compared clicks between Black Friday and Cyber Monday for one major fashion brand. One might assume that Black Friday would see fewer clicks and more in-store purchases, while Cyber Monday would see more clicks with less brick-and-mortar activity.

However, Black Friday proved to be a much more fruitful day for digital, seeing 116,504 clicks with 104,277 uniques, versus Monday, which saw 44,710 clicks with 38,355 uniques. This simple comparison may very well impact the company’s social strategy next year and beyond.

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This chart illustrates encodes (shortened URLs) and decodes (clicks on those URLs).

Caitlin also shared an analysis of all 2015 encodes (Bitlinks created to fashio brand domains) and decodes data (clicks on Bitlinks to fashion brand domains).

Overall, the fashion world saw the most social engagement during Memorial Day Weekend, Fashion Week, Black Friday & Cyber Monday, and December 1.

December 1 was the most active  day of the year when it came to social engagement, with 4.3 million links created and 152 million clicks across the top ten fashion brands using Bitly.

Visualizing the Wisdom of the Crowd

Gilt offers its members top designer labels at up to 70% off retail. Seven million members, to be exact.Igor Elbert, Gilt’s principal data scientist, gave meetup attendees a peek behind what reach like that looks like:

5 million-plus daily email distribution

  • 2,500 brand relationships
  • 5.6 million-plus mobile downloads with more than 2 million push notifications
  • 500 million-plus monthly press impressions
  • 6 million-plus unique visitors per month
  • 20-40% of sales generated through mobile
  • 1 million-plus social media participants across Twitter, Facebook, Pinterest and more

In addition, Gilt members are affluent, young and educated. A whopping 89% of them are active on social.

All of this data results in many large affinity matrices that help the team personalize algorithms for each user. Like that Louis Vuitton satchel but feel the prices are a little out of reach? You’ll get a notification that other people liked a similar bag that may be more affordable. Like these heels from Dolce & Gabbana? They might pair nicely with this little black dress. Mapping tools help organize and make sense of the data.

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2016 and Beyond

There were two major themes in all three presentations: personalization and customer experience. Anticipating users’ wants and needs (especially when they might not even be aware of them), and getting them from Point A to Point B in as few steps as possible — especially on mobile — will, more than ever, differentiate good companies from great companies.

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