Why Big Data is capturing the Fashion Industry?


Why Big Data is capturing the Fashion Industry?

Through the accumulation and analysis of data from consumer buying processes, GPS profiles, and Social Media Behaviour, companies can recognise our needs before we are aware of them.
In particular, in the Fashion Industry there are promising possibilities to improve the consumer experience and to better react on their needs. Trends can be foreseen, the client language can be individualised, and high quotes of return can be avoided.

What is Big Data?

The term Big Data is on everyone’s lips. Big Data is a huge amount of data volume, structured and unstructured, which is exceeding the capacity of the conventional IT-Structure.
The handling of Big Data requires new IT-infrastructures to process all this data. It’s not the amount of data that’s important. It’s what organisations do with the data that matters. Big Data can be analysed for insights that lead to better decisions and strategic business moves. The term Big Data is often split in 5 Vs: Volume, Velocity, Variety, Veracity and Value.


An approach to Big Data in the Fashion World
Since a few years, fashion companies are evaluating the purchase behaviour of their clients and are trying to get more information about their target audience. With the help of Big Data, a personalised and objective driven communication can be achieved for each client.
Through the development of new data basis, for example IoT (The Internet of Things, refers to the connection of devices, other than computers and smartphones, to the Internet), a data amount that exceeds the size of the conventional data processing possibilities is created.
With the help of Big Data, unstructured data from internal and external sources can be structured and analysed in real time. For the fashion industry it means that information from the Online Shop, movement profiles in the Internet and on the street, check-out data and travel path of the client to the shop, as well as opinions and behaviours on Social Media can be collected and assimilated to a detailed profile of each person who has contact with the respective brand.

A better customer contact

The primary field of application of Big Data in the Fashion Commerce is the first touch point of the target audience and the brand.

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Big data is valuable for a pre-targeting strategy as it allows personalised product recommendations. As a matter of fact, this technology allows to analyse consumers’ purchasing behaviour and to suggest products to someone based on what other consumers with similar purchasing behaviour already purchased.
With a Sentiment Analysis, Fashion retailers can deduct our behaviour towards their brand. For this particular analysis, the content we created and consumed on Social Media is evaluated and compiled to a so-called trend mood. Editd, a big data tool for retailers, supports fashion retailers with the pricing of fashion items and accessories, and also in marketing their products better. This tool measures customers’ sentiments with the help of data stream from different social media platforms.
The basis for a successful communication relying on Big Data in the Fashion industry is the transparency of the data collection. Sometimes the customer is not aware that information about his behaviour is continuously collected. To avoid that personalised communication influences the image of the brand in a negative way, it is crucial to tell the client where the data comes from and to give him the possibility to control the level of the transmission of his data.

Optimised product line and pricing

During the purchase process, fashion retailers can optimise their product line and pricing online and offline with the help of Big Data. In particular, in the online sector real time analysis for click rates, page views and the general Internet-surfing behaviour can be analysed and used for a personalised presentation of the online-shop.
A flexible range design with the help of Big Data is not only possible for the E-Commerce. It can also be applied for shopping in the physical boutique. By using video cameras and transponders in shopping trolleys, fashion retailers can analyse our route and are therefore able to optimise the sales area for a particular collection.

Less returned goods

For the fashion commerce the stage after the purchase is a crucial success factor. Returned goods rates over 40% are not uncommon. Preventive returned goods avoidance, with the help of Big Data Technologies, can increase the success of your company. Text Mining Technologies recognise with the help of Machine Learning return goods models in product assessments and Social Media comments. At the same time product ratings (from Social Media or other assessment platforms) on the online shop are filtered according to “returned goods” relevant words. Keywords, such as “Colour not as shown on the picture” or “wrong size” are grouped thematically, in order to be able to detect a possible fault in the product description.

Some examples of brands using Big Data

By integrating Big Data with similar technologies such as artificial intelligence, machine learning, and the Internet of Things (IoT), fashion retailers can analyse real-time insights to create the next generation of innovative fashion trends. Some of the fashion brands, which are using the power of Big Data are:
• Ralph Lauren is applying the power of Big Data. This brand is attaching sensors to their polo shirts to track buyers’ fitness level. With the help of a Smartphone application, buyers can keep track of their health whenever they wear a Ralph Lauren polo.
• Nordstrom has used data analytics to provide a great shopping experience across their online and retail stores. They have been tracking Pinterest and Instagram fashion trends and then using this data to promote and highlight those popular products both in store and online. Nordstrom has even set up their own research lab, “Nordstrom Innovation Labs” to develop and test products.
• TopShop the UK fashion retail brand is using the latest technologies to create a unique and personalised shopper experience. Many of their retail stores have virtual fitting rooms, which allow customers to select specific articles and see how they would look wearing them.
• Ted Baker has been using in-store beacons to send push notifications straight to their customer’s smartphones while they are walking around the store. These beacons allowed Ted Baker to see which display attracts the most attention.

Using Big Data and building up a powerful marketing strategy behind

Big Data is providing numerous starting-points in the Fashion industry to optimise processes, save costs, have a more specific client approach and grow revenue. By 2022, a worldwide revenue of $ 713 billions in the e-commerce fashion industry is forecasted.
The most important aspect not to forget is that Big Data is only delivering the information. Indeed, to be successful, an effective marketing strategy needs to be set up in advance and the relevant information of the Big Data transmitted into individual campaigns.
Eminence, your digital marketing agency in Geneva, helps you to set up a successful strategy for turning your Big Data into Smart Data.
We use powerful technological tools to collect your relevant data and implement a marketing strategy relying on Big Data. Our experts in Big Data business intelligence will setup an extensive strategy in order to obtain the right data and use it for your prosperous growth and your online deployment.