#2: Inaccuracy of collected data

Quality not quantity is still a problem for big data. Fashion businesses are collecting data about millions of customers, yet there may be some fundamental inaccuracy – or rather, incompletion – about the data they are collecting.

For example, the ASOS returns note has eight different return options, including ‘doesn’t fit properly’ and ‘doesn’t suit me’. Within these two phrases is a multitude of data waiting to be collected. Anyone who has made their own clothes or personal style overhauls will know these statements could actually mean anything from “The sleeves were too short for my arms” to “The hips fitted but the waist gaped at the back as I have a curvy bum”, or “The lace collar made me look like Peter Pan” to “The colour was significantly different in real life than on my monitor”.

The same lack of comprehensive data collection can be said for the online adverts marketing brands pay to be served up on third party sites like Facebook. Take the advert below which I was recently presented from Missguided for their plus-size clothing. The options to get rid of the advert are generic (not fashion-related) and there is no further option to give detail around why exactly the advert was irrelevant (my selected reason).

If they offered the option, they’d find out I am interested in clothes, womenswear, fashion, trends and everything Missguided was offering – except for the size, which is a fundamental barrier to purchase.

Solution: Collect comprehensive data

If fashion brands, and their third party platforms, can collect data more comprehensively, then fashion’s big data will be much more accurate and can be used more effectively.

The industry is starting to lean towards more detailed feedback mechanisms, although right now they’re not viable on a large scale due to consumer’s lack of time and the brand’s lack of resource to data-crunch. But personalised customer service could be a way round this. For example, after an item is returned, certain customers could be contacted and asked to fill in a more detailed feedback form with the offer of winning their next delivery or item free. On third party advertising sites, a simple text box would be enough to allow consumers to give more detailed feedback.

Small businesses – with smaller customer bases – are operating data collection and feedback loops much more effectively, especially if they are crowd-funded or rely on community interest to purchase products. When you have millions of customers, your loops become much more difficult to manage – but without a proper rethink of how and what data fashion businesses are collecting, the data itself is always going to have limited value.