Gymshark, the gym wear brand with one of the fastest rates of profit growth in the UK, is sold exclusively online through its website and a network of affiliate partners. It also has a lot of social media data, generated by ‘Gymshark ambassadors’ who promote the apparel line to their Instagram followers.
To date, the brand has been tagged in 6.6 million Instagram posts. The Birmingham-headquartered company works with more than 100 athletes and influencers around the world, has over 60 affiliate partners and 2 million customers.
The data from this network could be very hard to get to its teeth around. However, as a result of using a self-service data analytics platform, the company has benefited from quick access to insight and which can then be embedded into decisions.
Samantha Robbins’s role as customer insight analyst involves helping the company to understand its audience really well. One problem that the customer insights team had was that with the affiliate platform it was not easy to a detailed view of the affiliate accounts, without downloading and appending Excel sheets on an ad hoc basis. “That left a lot of room for error,” said Robbins.
The detailed information they wanted was; the type of merchandise the different affiliates were selling, the point in the customer journey at which the purchases were taking place, whether a particular channel was attracting a lot of new or returning customers, which promotions or discount codes were working well and how was a particular channel performing overall.
Robbins found the solution was to build a simple API call using the download and JSON Parse tools that are available in Alteryx, a self-service analytics platform.
She said it was really simple to do “just using the documentation on the affiliate partners site,” followed by a little bit of data cleaning. “Then we had all of the information and data we needed available in one table that we were then able to push into Exasol to be used in the next step,” she said.
The next step involved blending that data with internal data on customer information and with Gymshark’s transactional data to get a full picture of how the programme was doing.
The ability to schedule the API call was of great benefit to the company. Robbins said that the API call and the blending of the data took place at 6am, so that it would be ready on time for when the customer insight team got into work. “All this information, once blended, was able to be pushed into a Tableau worksheet. This gave all of the information in one place, including metrics on things like how many orders are being processed and how much revenue is generated by a particular affiliate,” said Robbins.
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