musicMagpie Case Study

  • PRODUCT: Recommend™
  • CHALLENGE: Personalisation based on behaviour and preferences and limited internal resources to optimise
  • RESULTS: 25% increase in AOV

musicMagpie is the best place to sell unwanted consumer technology, such as smartphones, tablets, game consoles and wearables, as well as the best place to purchase high quality refurbished technology. The company is the world’s biggest seller on eBay and Amazon, and the first globally to achieve 5 million in positive feedbacks on eBay. Its key focus is on consumer technology, but also buys and sells a whole host of media products such as CDs, DVDs, Blu-Rays, games and books.

In 2018, musicMagpie was looking to make personalised suggestions to their users based on their preferences and behaviour. The tool they were using for recommendations was very basic, and it required too much of the team’s time and attention to customise it.

musicMagpie set out to find another personalisation solution with more automation, AI and scalability to alleviate the optimisation pressures on the internal team. Dale Goodwin, Head of Marketing at musicMagpie tells their story:

“On reviewing other personalisation solutions, we found the pricing models weren’t very transparent. By comparison, RichRelevance was very clear and we were impressed with the ‘out of the box’ feature set and their customer list set them apart from any other solution we considered.”

Ultimately, we chose RichRelevance Recommend™ due to the rich feature set, A/B testing capabilities and ability to control and customise personalisation where appropriate. In addition, a key driver for us was the AI component of the platform which automatically optimises and makes decisions based on customer preferences and behaviour in real time.”

Recommend recognises musicMagpie’s customer preferences for different genres and tastes of music and films as well as models of phones and tech, making recommendations on this basis. Strategies are continuously tested and the team can confidently let it run and self-optimise. As a result, musicMagpie are seeing a 25% increase in AOV for media orders.

Dale explains the positive impact Recommend has had on the experience for their customers:

“We’re making personalised recommendations to customers depending on their individual actions and preferences, meaning the products they see are tailored to them. We can show them items they may not have found through search, or even realised we had. We can help them take advantage of promotions and 2 for 1 offers as the tool recognises other similar items and recommends them to users. This helps customers get better value from our range and increase AOV for us, creating a win / win”.

musicMagpie has some unique challenges with a constantly updating product feed with the products they sell constantly coming in and out of stock. RichRelevance were able to work through and resolve this for musicMagpie using one of the new product API features which was able to cope with the fast stock turnaround in real time.

Personalisation is key to the ecommerce strategy at musicMagpie, as Dale continued:

“We see personalisation as key to enriching the customer experience as well as increasing AOV by recommending other products that are personal to customers rather than just bestsellers that may not resonate with them. Going forward personalisation will feature heavily as we try to cross sell relevant products in our tech journeys and recommend other phones when we sell out of a particular model. The great thing about the RichRelevance personalisation tool is its ability to continually optimise and test for us, even when other projects take priority internally, RichRelevance is still there, improving performance.”

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