- RETAIL SEGMENT: Home and Garden Improvement
- PRODUCT: Recommend™
- CHALLENGE: Homebase sought to optimize its website experience for customers— taking stock updates, trends or personalization into account—while gaining visibility on impact for any implemented initiatives. They also sought to change the manual process for updating related items on its product pages.
- RESULTS: Following the implementation of RichRelevance Recommend, Homebase:
- Averaged one additional item to the shopper’s cart
- Increased the average order value by 30%
- Attributed nearly 10% of online revenue to a Recommend influence (over 12 months)
«RichRelevance have been a pleasure to work with, providing very helpful and timely support through our implementation as well as advice and guidance since going live. We are now looking to leverage their consultancy services to see what further benefits they can provide.» – Todd Coughlan, Commercial Optimization Executive, Homebase.
Homebase is a leading home and garden retailer selling over 38,000 products for the home and garden. In addition to more than 265 large, out-of-town stores throughout the United Kingdom and Republic of Ireland, it has a growing internet offering at www.homebase.co.uk.
Confronted with a manual process to update related items on product pages, Homebase sought a personalization solution that would not only relieve pressure on internal resources, but would also help them improve the customer experience.
In June 2014, Homebase partnered with RichRelevance to implement the Recommend™ product recommendations solution.
Not only does Recommend automate personalization functionality, saving significant internal time and resources, but also the recommendations drive revenue and relevance to consumers through its relevance modelling. The ensemble modelling leverages over 125 algorithms, which compete for the opportunity to respond to each shopper request, taking into account user details and the context of the request. This advanced algorithm gives shoppers the right recommendations and helps drive sales and basket size. Recommend also gave Homebase the ability to analyze performance at a granular and top-line level as well as perform intelligent tests to further optimize performance across the mobile, application and desktop devices.
In addition to the revenue driving capabilities, Homebase really liked Recommend for its intuitive, self-learning ability to constantly test and optimize for the best recommendation, based on shopper interaction. This helped Homebase cut resource costs by freeing up internal resources to be more strategic, rather than tactical in their daily responsibilities.
“RichRelevance provided a complete recommendations engine for us which we felt was the best choice for a sustainable solution moving forward,” said Paul Canavan, Head of Digital Programme & Operations at Homebase.
Since implementing Recommend in October 2014 across category, item, cart and add-to-cart pages, Homebase has seen on average a 30% increase in cart sizes for those customers who interact with product recommendations. Plus, customers who engage with the Recommend product are proven to add (on average) one additional item to their cart.
Paul Canavan added: “We’ve seen particularly good results since the addition of the mobile and tablet channels, with the ‘add to cart’ placement demonstrating really good uplift. It’s not always about basket size; sometimes it’s just as important to recommend similar products that the customer may prefer. The use of RichRelevance technology is a great way of highlighting the product range we have.”
In addition to the increase in basket size and average order value, following the implementation of RichRelevance Recommend, over the last 12 months nearly 10% of online revenue could be attributed to a Recommend influence.
Because Homebase is so happy with the success of Recommend, the company has decided to invest in a resource to fully manage the Recommend product. The resource allocation demonstrates how the company understands it can further increase its positive performance by trialing new placement locations and merchandising strategies, which are included as part of the Recommend product. This resource will also focus on optimizing the system by testing and learning using the data provided through RichRelevance, as well as producing new metrics and key performance indicators (KPI) for the business to understand the purpose and performance of the tool.DOWNLOAD