Part 1. Discussion Session
Part 1. Discussion Session
Data surrounds us everywhere and it has implications for every one of us, whether we want that or not. Simply put, every single part of our lives is somehow related to data. Whether you are shopping, running, eating, or even talking with a friend on a phone, these actions usually leave big data trails through your phone, the apps you use, internet browsing history and in many other ways.
As a fashion technology company, we feel that there is a huge gap between the fashion business and such big opportunities as using data. These series of blogs will try to answer the main questions when it comes to the Big Data and how to use it in the fashion world. This time, let’s discuss what is actually “Big” in the Big Data, to whom this data belongs and why shops should consider “reading” their own information.
What is “Big Data”? What does “Big” mean in this context?
Du: Big Data has a lot of different meanings, depending on whom you ask. For me, Big Data is anything pertaining to working with, handling, manipulating data, which is so big, that it cannot be reasonably done on one machine only. That means, that Big Data often resides on several machines or in the cloud, and manipulating data has to be done by several machines as well.
Carlene: I believe, that Big Data is the driving force behind analytical decision-making. EasySize is built on big data in two ways — data that allows a size to be calculated, and data from the customer interactions that allow us to revise and improve the company. “Big” is associated with gigantic, bigger than you’ve ever imaged, more data than you can wrap your head around.
David: Simply put, Big Data is a “junkyard”, which is full of data and some of it might be structured, some of it might be not. The main point is that this Big Data requires skills and knowledge to maintain it. The word “Big” means that it is not a “trashcan”. The main difference between a “trashcan” and a “junkyard” — it’s their size. The small amount of data can be easily analysed. But when it comes to “junkyard” sizes — you need to consider a lot of things and find a right approach before mining.
Customers expect something in return for the data they provide. Agree or Disagree? Whose property is the “Big Data”? Is it users’ or does it belong to the people who are collecting it? Why?
David: Well, to begin with, Big Data is not always about customers’ personal info. However, if we do talk about the personal information and the data which is collected in a legal way (along side with a signed confirmation from the customers), then, in this case, it belongs to someone who is collecting it. What is more interesting, the rewards for providing personal information are always increasing the number of the data providers. That is something worth to consider for the online shops.
Carlene: I have to agree with David. Shortly, customers should get something in return. Cliché answer, but I believe, that data belongs to both, the customer and the company. Without the customers’ data, companies could not improve. On the other hand, without the company, the customers’ life will not improve in that way, so it is beneficial to both parties to in a sense own this data. There is a point where privacy comes into play, though.
Du: Customers definitely expect something for their data. The problem is that people have varying expectations on what their data is allowed to be used for. As for the ownership of data, I believe, this is an area which cannot be clearly defined. For example, intentional user data should belong to the user, this is the data which a user specifically creates (for example, data from posting pictures or writing blog posts.) When it comes to the incidental user data, it should belong to the user, although, the platform on which it is generated, should have a license to use it for its own purpose (this could include tracking data of people using a website or browsing data on a netshop.) Finally, user data collected by third parties for the purpose of surveillance, should belong to the user and should never be accessible by those who collect them.
How online shops using Big Data versus the ones not using it, are more strategically superior?
Carlene: Statistically speaking, yes, they are more strategically superior. You could say it is the same with the sports teams. If you use the data to your advantage, on top of all of the other resources you have, you will gain on your competition.
Du: Good point, Carlene. Shops using Big Data are indeed more strategically superior. Without the Big Data, shops have to make strategic decisions based on limited evidence and on “gut reactions”. Big data is a powerful tool, that can elevate strategic decisions if it is used correctly.
David: In addition, shops, which use Big Data (again, in the right way), have more understanding about their customers in so many ways, therefore, those shops have more potential to fight in this highly competitive market.
We couldn’t agree more to this quote: “The Big Data is just starting to explode. Its volume available to retailers is unprecedented. Some retailers feel daunted by this overwhelming data and prefer to stick to their tried-and-tested business strategy. On the other hand, there are some retailers, who’ve upped their game to capture value and leveraged unique opportunities from Big Data to devise data-driven, innovative strategies. According to a McKinsey study, retailers who successfully tapped the Big Data analytics recorded a whopping 60% increase in their margins and improve in labor productivity by 1%.” (Big Data in Retail)
It is clear, that the ability to read and use Big Data will have a huge impact to the fashion e-commerce business. Stay tuned with the next post, where same discussion’s participants will try to answer these questions:
- How to use the Big Data?
- What is the personalisation and experience aspect of the Big Data?
- How important is Big Data in Fashion in general?
P.S Huge thanks to the EasySize team for participating and sharing their experience and opinion. If you would like to discuss and/or get in contact with any of the participants- feel free to drop us an e-mail.
Ieva Smitaite, Communications at EasySize