Lesara: Big Data Is the Hot New Trend in Fashion

Big Data is a red hot buzzword for good reason. Technology allows us to track events that take place in the real world with remarkable accuracy. Simply by crunching numbers, we can predict droughts, identify consumer trends, and improve security, among a million other applications.

One industry that is ripe for Big Data disruption is the fashion industry. Fashion companies plan their product lines around the decisions of a few elite designers who showcase their styles at a select few fashion weeks every year. This is how the industry has operated for decades, and much of it still operates that way today – but that is beginning to change, and it’s because of Big Data.

A great example is the Berlin based startup Lesara, which has raised $23 million dollars in funding. It’s anything but another online clothing retailer: Lesara is pioneering a new way forward for fashion businesses. At its helm is 28-year-old founder and CEO Roman Kirsch, who will confidently tell you that his designers do not go to Fashion Weeks.

Lesara is not so much a fashion company as it is an agile retail company. Agile retail companies use Big Data analytics to identify consumer trends, utilize highly efficient production and distribution systems, and only sell online. The result is products that people want, at prices they can afford, without having to go to a mall.

As Kirsch describes it, “What we sell is fashion, but what we do is smart data”. Why should should fashion companies and retailers care about this? Speaking with Kirsch, he described the following reasons that should pique major fashion companies’ interests:

1. Waste

“Anytime companies have excess product that ends up being sold at discounted retailers, you have a clear use case for why smart data matters so much,” says Kirsch.

This type of waste occurs when companies over estimate sales of a specific item and get stuck with excess inventory. These items then get sold to discount retailers like TJMaxx and end up costing the company not only financially but also in many cases can dilute their brand. Data would allow these companies to determine consumer demand and produce in appropriate quantities. This can drastically reduce the amount of over-ordering that takes place.

2. Mass Production

Agile retail is influencing the fashion industry much like the rise of Fast Fashion did over a decade ago. Fast-fashion companies like Zara and H&M disrupted the market by being able to produce 10,000 to 15,000 new items per year for their customers.

Much smaller agile retail companies like Lesara are able to manufacture 50,000 to 100,000 new items each year. That ability comes from their use of data to quickly determine which products are working and quickly increase or decrease production accordingly.

3. Aggregation

Instead of pulling solely from internal datasets, companies today are able to pull from a variety of datasets across the web to determine not only what their customers want but also what their competitor’s competition wants. Kirsch notes:

“We are constantly looking for new data sources to add to our repertoire. We use our own web traffic, social media, search engine trends, and other sources that are our own private secrets. Once we determine something has the potential to sell, we are able to design, manufacture, and start shipping to our customers in 10 days.”

It now becomes clear just how useful big data may be for the fashion industry, so it should come as no surprise that this industry adopts it in its activities, just like the insurance industry and call centers, for example, are doing.

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Written by:
25 y/o, born and living in Portugal. Majored in Biology, but tech and computers were always a passion. Wrote for sites like Windows.Appstorm and MakeTechEasier.
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