Why it works: personalizing the customer journey builds loyalty, says Retail Rocket

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Online retailers can take a leaf out of the retail sector’s book and provide a personalized shopper experience to drive sales and win loyalty, says Teresa Sanchez-Herrera, Marketing Manager of Retail Rocket

Teresa Sanchez-Herrera: each customer gets their own version of the webshop

High end stores recognise the value of providing a personal shopping service.

Personal shoppers encourage customers to spend significantly more with some retailers revealing that their clients can spend up to four times the average transaction value.

In an increasingly competitive retail sector, personal shoppers engage more directly with the customer, boosting shopper loyalty and the conversion rate. They work by increasing exposure to products. During a visit, shoppers are introduced to a wider range of products than they would normally consider. Stores are also able to cross-sell merchandising categories, prompting and suggesting complimentary products or matching items and accessories, for example. Crucially, personal shoppers are also able to curate product offers, tailored to a customer’s taste, their individual buying history or planned purchasing requirements such as securing an outfit for a summer wedding. From a sales perspective, personal shoppers will also know which products have proved most popular and the top-selling product combinations or bundles. This kind of expert knowledge and shopper engagement drives trust and in turn sales. It’s no wonder personal shoppers have become a key selling tool in the high end retail sector but that they are also increasingly filtering down from designer outlets and department stores onto the high street.

But delivering a personalized shopping experience is not confined to physical bricks and mortar stores. Today, online retailers can provide a personalized shopper experience each time a user visits their e-commerce site. And, if they effectively and correctly harness the shopper data, online shops have an opportunity to curate more finely tuned offers and positive experiences than their physical retail counterparts.

Retail Rocket, a multi-channel big data platform for online stores’ personalization, is helping online stores to achieve that goal. It analyzes the behaviour of shoppers and adjusts retailer websites in real time so that each customer gets their own version of the webshop, highlighting the products that they are most likely to buy, based on their preferences and purchase history.

Founded six years ago, Retail Rocket’s solutions have a rich heritage in data science and are already used by more than 1,000 customers in 10 countries including leading retailer brands Otto Group, L’Occitane, Auchan, Vans, Yves Rocher and Decathlon. In total, Retail Rocket analyzes the behaviour of around 120 million user profiles.

Retail Rocket personalizes e-commerce websites in real time, throughout the shopper’s online journey – from the moment they first land on the homepage of the retailer’s website until the shopping cart page, through to their product category pages, product detail pages or internal search results page.

Retail Rocket personalizes e-commerce websites in real time

On product category pages, for instance, Retail Rocket’s solutions will showcase the most popular products within a category but segmented, according to the user profile plus new products for each category on the site. Retail Rocket also enables internal search results page personalization to feature products that are most relevant to the keywords a visitor used on a site search, based on what other people with similar searches were interested in.

On the shopping cart page, meanwhile, Retail Rocket will recommend related products, which other customers have bought and which the user may also like – a key up-selling tool, which boosts the average order value of each shop.

Put simply, Retail Rocket’s solutions draw on powerful algorithms and machine-learning expertise to create a virtuous shopping experience. Retail Rocket tracks and analyses users’ online behaviour against the retailers’ products database in order to provide personalized offers which, in turn, drive repeat business generation.

Website personalization case study

The Early Learning Centre’s online store in Russia – Elc-Russia.ru – has implemented Retail Rocket’s product recommendations and driven more than 10% revenue growth.

Launched in 2006, the online site reaches over 260,000 visitors per month. With customers’ increasingly high expectations from online shopping and a very large range of products, Elc-Russia.ru wanted to show shoppers personalised offers that matched their preferences in order to win their business and loyalty.

Retail Rocket introduced recommendations on both the category and product pages of the Elc-Russia.ru website and analyzed their efficiency with A/B testing.

Product recommendations were added to the category page and tested by randomly splitting visitors into two groups. The first group – the control group – was shown the category best sellers; while the second was shown personalized product recommendations from the current category based on their browsing history. The results showed that using Retail Rocket personalized product recommendations on the category page improved the conversion rate by 12.5% compared to the control group and boosted revenues by 10.1%.

To test the efficiency of product recommendations on Elc-Russia.ru’s product page, where the user is closer to making a purchase than on any other page and does not need distracting, Retail Rocket divided visitors randomly into four groups.

The first group was shown similar products, based on the product properties ie price, brand, category and text description etc. The second group was shown related products – complementary items based on the products’ database analysis and website visitors’ behaviour ie their shopping carts and orders. The third group was simultaneously shown two product recommendation blocks with similar products positioned above related products. The fourth segment was also simultaneously shown two blocks but this time related products were positioned above similar products.

The study found that using a product recommendation block displaying related products in a row above similar products (left) increased the conversion by 10.8%, with a statistical significance of 96%, and led to a revenue boost of 7.7%.

Saveliev Nikita, director of the ELC-Russia.ru online store, said: “By showing our customers the relevant products that may interest them the most, we try to make the process of choosing products as convenient as possible. Personal product recommendations that we implement on the different website pages cope with this task perfectly. This helps us to increase not only the loyalty of our customers but also the average order value and the revenue of the online store. The Retail Rocket team is always ready to support our ideas and actively offers testing of various algorithms to improve the conversion rate and the financial performance.”

Understanding what customers are looking for and presenting it to them clearly allows an online store to meet their customers’ expectations.

Retail Rocket’s solutions provide a personalized experience and means stores will be able to thrive in an increasingly competitive online shopping environment.

(A Retail Times’ sponsored article)