Machine learning and continuous testing across search relevance and product visibility support conversion rates that are three times higher than the market average. Since its launch in 1997 Swedish online book retailer Adlibris has enjoyed astonishing growth. Today, it operates a catalogue that runs beyond 10 million products, serves three million visitors per month, and sells 300,000 products per day.
Voyado has played a vital role in enabling Adlibris’ growth in recent years. When Adlibris broadened its product range with three new product categories, the launch presented a number of challenges, according to Rubie Oliphant, Product Specialist at Adlibris:
“The challenge was to market a new product range to an already established user base with specific consumer needs. Add to that the fact that we already had a catalogue consisting of more than 10 million products, and it’s obvious that it would be tough to deliver the visibility and search relevance we needed manually or based on static rules.”
With Elevate already in place, Rubie and her team already had the ideal solution – an AI powered, machine learning solution that could step in instantly and whose performance would only improve over time. Rubie explained:
“Elevate provided the perfect solution for our visibility challenge. It immediately ensured that our product panels started recommending articles across categories. But as it learned more about user responses to different panels, so the recommendations improved. Now we have a fully-fledged automated cross selling recommendation system on the website – one that learns and tests as it goes and requires only minimal input.”
AI and the future of online retail
As the e-commerce market continues to adapt to changing user behaviour and ever more demanding customers the challenges multiply, the argument for AI couldn’t be stronger.
“Today, the big challenges are related to product discovery, relevance, search speed and personalising the user journey, Rubie pointed out. And in response, AI is only going to become more important. These are not challenges that can be solved based on human input alone.”
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