Personalised product recommendations improves online shopping experience for customers
Personalised product recommendations improves online shopping experience for customers
High Street adult and lingerie brand Ann Summers is using to dynamic e-commerce personalisation software from RichRelevance.
When they shop online, Ann Summers customers will now receive personalised product recommendations to help each shopper discover products that are uniquely relevant to them.
RichRelevance’s enRICH personalisation engine facilitates competition among 60 independent recommendation strategies to deliver the most relevant experience. Using RichRelevance’s technology, Ann Summers will be able to take the wealth of information known about each customer, including preferences and shopping history, demographic details and referral sites, and marry it to the data the merchant holds on relationships between products or product categories and the behavioural patterns of similar shoppers.
Cross-channel upselling opportunities
By establishing a personalisation initiative, Ann Summers hopes not only to create a deeper connection with its largely female online customer-base, but to gather information about shopping behaviour and product associations that will increase sales across all channels.
“Through our personalisation initiative, we are gaining valuable insight into our customers and the way they shop for and discover our products. For example, we can access vastly more kinds of associated data about what people viewed after viewing a certain item,” said Andrew Harber, e-commerce director at Ann Summers. “By partnering with RichRelevance to manage and analyse our customer data, we are more in-tune with our customers’ behaviour and can take a more holistic approach to merchandising and promotions.”
In selecting RichRelevance, Ann Summers cited the company’s Amazon.com heritage as a key factor in the decision, alongside ease of implementation and technical knowledge. “Everyone is familiar with Amazon’s recommendations and to be able to tap into the intellect behind the algorithms was very appealing,” added Harber.
