The world of online fashion is notoriously fast-paced and fickle. Trends can soar and crash within a 48-hour period and meticulously market-researched products can end up failing. Silkfred, a British online retail platform that carries over 600 fashion brands, has adopted a data-first approach to stay ahead of the curve in a market that includes long-established players like Asos and Boohoo.
To deliver these vital insights, the company selected data analytics platform Looker. They're now measuring a vast array of data points covering the performance of products, understanding of the customer and even sentiment towards ad campaigns. This data is then fed back to a range of teams across the company, and used to further refine approaches across various areas.
Emma Watkinson, CEO and co-founder of SilkFred says that one of the greatest benefits has been the ease of data collection and organisation, within one system and one central place: "For example, say the marketing team wants to see what our top 20 products where the returns rate is under 40 percent are, they can build a report that shows that over time."
She adds that this approach can easily be taken for other metrics such as repeat rate of customer behaviour and the frequency of certain buying behaviours. This is in contrast to how the company used to work, where the IT team would have to build custom reports from scratch each time.
According to Watkinson this has led to an influx of data, which has even spread to business areas that have not traditionally been led by data, such as the photography team. "Historically, in the industry, this team doesn't have much of a data function," she says. "However, Looker has allowed us to build reports that show which models or which photographers get the best response."
This insight is then channelled into the production process for the next ad campaigns. "Putting that data in the hands of non-technical team members, and also teams that aren't normally used to dealing with data and information is really helpful," says Watkinson.
On the customer side, she adds that data insights sometimes end up smashing expectations: "The brand might have had an assumption about who a customer was and how they like to shop, but by looking at data in more detail sometimes you'd be surprised.
"You might think you were targeting an 18-24 demographic with a certain product but find it's actually more popular with over 35s."
This then prompts the team to rethink attitudes they may have held about what a 20-year-old or 35-year-old wants to buy.
Due to the sheer amount of data processed at the company, she says it is hard to draw concrete examples of the impact of data insights on KPIs. However, one metric that is easily quantifiable is the amount of time saved, which in turn means money saved.
"Before, at least half of tech team's output was producing reports and information for the team," she says. "Now, they're more focused on new feature development."
In fact, Silkfred’s developers have enjoyed a 15 percent increase in time available since the company started using Looker.