Our Data Science team looks into the advanced analytics methods within the Fashion sector.
We recently discussed the impact of Web Analytics within the fashion sector and how it is having a serious impact on the industry. In conjunction with this, our Data Science team has informed us a little more about how advanced analytical methods are being utilised and the impact they’re making within the global fashion scene.
Chris Morton, co-founder of Lyst (a global fashion e-commerce aggregator) revealed that half of their team are made up of Data Scientists, who are tracking, analysing and evaluating consumers’ behaviour. The data collected allows scientists to examine when and how consumers are making their purchases, the timeframes and predicted purchasing patterns.
The one thing the numbers can’t always conclusively tell us is why consumers are purchasing specific items. Fashion is subjective, there is only so much you can discover using quantitative data, which does not represent every purchasing pattern. Data Science is trying to fill in some of the gaps – colouring in the blank spaces.
Sentiment analysis and text mining are going some way to helping solve this problem. Social media provides us with an excellent opportunity to get a better understanding of a number of factors including, for example, why did a consumer respond to a particular dress? Is there a reason why they want to buy it? Is it due to the colours on offer, the general shape of the outfit or have they seen Kim Kardashian wearing it? Seriously though, only through examining this can we get the emotional reasoning behind consumers purchasing decisions.
Fashion relies on Data Science as much, if not more, than most industries. The greater significance of social media leads to more potential data to analyse and gain a competitive advantage from. EDITD, a market leader in real-time analytics, has facilitated retailers like ASOS who saw a direct increase of 33% in their sales from using the metrics business.
So the hottest trend in Fashion is data. As with Web Analytics, utilising the numbers alone can’t give us any insight into a person’s free will – but Data Science is beginning to give us a good shot at it.
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