Buying Evolution

Predicting fashion trends has long been a tricky skill perfected by those who move up the buying ranks of organizations around the world. Always a step ahead of the next best-selling trend, buyers are often focused on one specialized sector of a company to perfect the art of predicting what consumers will purchase, but could there be a more accurate way to anticipate trends evolving from the introduction of interactive Web 2.0?

Social media platforms are providing an unprecedented plethora of knowledge regarding individual’s fashion preferences. Women and men alike are tweeting their favorite designers, instagramming their latest outfits, checking into stores on Facebook, and ‘pinning‘ favorite runway looks world-wide, and big-time organizations are catching on.


Social media is not the only outlet large retailers are analyzing, but with the popularization of e-commerce in recent years, buyers are gaining insight into top stock searches and purchase behaviors like never before. In the same way, organizations can cease production on not-so-successful garments in an effort to reduce unnecessary inventory that will inevitably end up in the back corner sale section of stores.

Suggestive Selling

This collection of information is sometimes leading customers to purchase things they didn’t even know they wanted. Suggestive selling using big data from e-commerce sites has led to increased web traffic and conversion rates for those e-tailers who have mastered the art of using big data correctly.

Companies such as Zara have taken this task further to physically place handheld devices in stores so that sales personnel can input actual customer feedback regarding garment specifications to better match consumer demand. Criticisms such as ‘this dress hits a little too high above the knee’ or ‘this top would be great sleeveless’ have been noted in changes to production in as little as two weeks time. This focus on keeping inventory low and receiving constant feedback creates a high turnover ratio and alters the focus to give the consumer exactly what he or she wants.

Data analytics advocates are capitalizing on this opportunity by creating platforms used to analyze big data facts rather than old-fashioned intuition. A variety of software options such as Teredata and Hadoop are continually being introduced; each improving on the relational implications of the last. These applications are taking social media content, e-commerce interaction, and digital sales reports into consideration while taking the ‘guessing’ out of a once intuitive career, and could one day potentially do the job without the help of a human hand altogether.

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