Subscription Boxes: Where Warm and Friendly Stylists Meet Cold Hard Data

Over the last several years, many predictions have been made about big data and the impact it might have on our lives, including how we work, shop, and spend our free time. At the crossroads of these interests is something not everyone pays attention to, but everyone needs: clothes.

Fashion-related predictions for big data have brought us more accessible ways to get the best deals, new methods for looking at things we already love, and different ways to shop altogether.

Though their share of the retail market has most noticeably increased in the clothing industry, subscription services are popping up every day, and for an increasing variety of interests. Whether you need the best grooming products for your equine family members (because all horses deserve to look as good as American Pharoah), are in the market for allergy-sensitive snacks, have a penchant for dressing like your favorite Marvel heroes, or are just overwhelmed at the thought of shopping at the mall, there’s a subscription out there waiting just for you.

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A busy shopping mall. Source: PhotoPin

Aside from obvious benefits such as convenience, value, and time saved, the popularity of subscription boxes represents a greater shift in consumer consciousness. Inundated with choices, trends, and price points, subscriptions can make the shopping experience feel unique, personal, and effortless. For example, services like Stitch Fix and Trunk Club are growing rapidly, and employ “stylists” that take into account user data, including measurements, preferences, past purchases, reviews, and returns, to tailor future boxes to them.

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Companies like Stitch Fix aim to personalize the shopping experience using customer data

Most subscription boxes work this way, and require similar types of data to curate boxes for each customer’s unique taste. Customer preferences are often initially gathered by a survey that contains image-based questions, such as “Choose the image that most closely reflects your personal style,” or “Which of these three dresses are you most likely to wear?” This data is stored and becomes part of a customer’s unique profile, which is continuously updated as that person uses the service.

Far more complex than results returned by a search engine (or even browsing an online retailer’s “Customers who viewed this also liked…” column), collecting and analyzing this data requires multiple variables that intersect with one another in different ways. In return, subscribers are no longer confined to their local mall or scrolling through hundreds of online results that match the query “blue cocktail dress.” This is how subscription services maintain value—by consistently translating customers’ profile data into clothing in preferred lengths, hues, fabrics, and textures arriving at their doors each month.

For developers, this means a new market for data science is emerging, and as Succinctly series author Katie Kormanik notes, “No good decisions can be made without the use of data.” Her book, Statistics Fundamentals Succinctly, will be available on the Syncfusion Tech Portal soon.

If you’re already working with data science, or just looking for an easy way to get started, be sure to take a look at the Syncfusion Big Data Platform. We recently updated this platform, which now includes a Cluster Manager that makes running multiple Hadoop jobs more accessible for everyone. This complete production environment enables users to process and distribute data solutions on Windows using familiar tools and languages, including C#, Java, Pig, Hive, Python, and Scala. No manual configuration is required—try it for free today.

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