Online fashion platform SilkFred was set up in 2012 to help bring together smaller independent brands and fashionistas looking for an alternative to the offerings on the high street. Co-founder and CEO Emma Watkinson explained that she and her staff rely on the data from customer interactions and purchases, to inform business decisions. SilkFred never gives opinions of the brands it features but leaves it up to the customers to decide what is popular.
"We look at the data. It has always been behaviour-driven."
Watkinson said: “It is about what the customer thinks is good. And how do we know that? We look at the data. It has always been behaviour-driven.” Since implementing big data analytics platform Looker, it has been easier for all SilkFred employees, no matter their level of technical expertise, to pull out the information that they want about the business and customers' choices.
The need for such a platform became apparent when Watkinson realised that the tech team had a backlog of requests to extract data on figures such as sales. The SilkFred data team has been in existence for a year and a half, but was limited to pairing up with the developers to run queries alongside the database. “They would design the reports that they wanted to see and the things they wanted to look at, and they would work with a developer to build that report,” she said.
The problem was that different people would be looking at the data in inconsistent ways. For example, a merchandiser might look at average transaction value as their core metric, while an assistant merchandiser might look at average item price, resulting in incongruent stories after both people had built reports with the developers.
As well as there not being a ‘single version of the truth,’ the technologists were not able to use their skills to their full potential. Watkinson said: “For the developers who are very talented backend programmers, it is not really the best use of their time to be running queries against that database all day long.”
Now with Looker in place, there is far less inconsistency with the numbers and far more efficiency in the use of developer time. Looker was set up within a month and very little training was needed because “it is relatively self-sufficient. You can just look at it and get going.”
One report that is currently being built by SilkFred is assessing the success and impact of in-house photography. Watkinson said that SilkFred has photoshoots every day, producing thousands of images every month, generating a wealth of information. The images are created by the shoot and production team, who are non-technical creatives, and with that information they are looking to pinpoint the hallmarks that make one photo much more successful than another. The team is tagging attributes such as the model, the photographer, and the brand to see if there is a blueprint for success and therefore avoid shooting images that no one is interested in. This in turn will save the company time and money.
“It’s hard to isolate what makes a photo one that sells a product really well, however using this data, it seems reasonable to expect that there would be some consistent things that link our most successful photos together,” said Watkinson. She added that the Looker is so easy to use, it does not matter that the shoot and production team is not technical.
With this new platform in place SilkFred is now saving a lot of “dead time” and its non-technical team members are empowered to make better decisions and build their own reports.