The big picture
This Middle Eastern marketplace is seeing tremendous growth from a new generation of shoppers looking at online and omnichannel shopping as the future. Shopping from the convenience of an online medium, however, does not translate to expecting a less than stellar shopping experience.
The marketplace is a leading online retailer of brands worldwide and caters to a diverse, experienced, savvy shopping community. They wanted their shoppers to engage with, discover, and be excited by the choices and recommendations they see on the site.
To help them build trust and deliver incredible shopper experiences for every individual on the site, the customer turned to Vue.ai. Vue.ai’s AI-powered solutions helped the customer create an end-to-end personalized shopping experience.
Through this sustained partnership, data-backed recommendation strategies have been tested and implemented to understand what works for this business. The customer has seen a 21% improvement in user engagement QnQ with Vue.ai’s personalized recommendation solution.
1:1 personalized recommendations across the site to improve user engagement
Shoppers want variety while shopping, but the variety also needs to be in line with their intent, preferences, and Style Profile. When there are many irrelevant product selections offered as recommendations, shoppers are more likely to abandon the site without a purchase. To avoid this scenario, the customer implemented Vue.ai personalized recommendations across the site.
Vue.ai’s personalized recommendations across the site helped shoppers see products that match their preferences - and, more importantly, showed products that had a higher likelihood of reaching their needs. Recommendations were added keeping in mind the page’s intent; for example, Trending Product recommendations on the category page kept shoppers engaged.
Within a month of implementing these Vue.ai strategies, the customer saw a 21% increase in user engagement across the site.
Personalization with a 360° view of product and shopper data to understand shopper preferences and improve retention.
Shoppers want familiarity and a sense of belonging when they shop. Loyalty to a site and regular logins happen when they log in to a site and are greeted by products they would gravitate towards immediately. To provide shoppers with an efficient start and personalization that recognizes shopper intent and needs, the customer worked with Vue.ai to experiment with and implement solutions across the site.
Vue.ai’s 360° view of both product and shopper data helped the customer understand shopper intent and preferences more accurately and with nuance. Shoppers who can consistently discover and purchase products that align with their preferred means earning shopper loyalty and improving retention.
Shopper intelligence built on this system ensures 1:1 personalization for every touchpoint of the shopper journey. Designing specific parts of the shopper’s journey prioritizes their preferred brands. Real-time personalization provides maximum engagement opportunities.
For this category of products, improvements made based on shopper data and shopper journey on the site helped the customer see a significant uplift in CTR QoQ from 2019.
Users who engage with Vue.ai recommendations in their first visit to the website revisit 3x more than the users who do not engage
Product page personalization to boost product discovery and conversion
Recommendations on any page need to be positioned to derive the highest conversion. Recommendations that help shoppers visualize trending products or items they recently viewed or similar products to their choice of the product ensure they remain engaged and convert.
Vue.ai recommendations help in enabling shoppers to explore a variety of products in line with their style preferences. The recommendations have also been observed to lead to a potential increase in cart size because of greater product visibility and the ability to visualize ensembles.
Vue.ai recommendations have resulted in a 3x uplift in add to cart rate and 4.5x increase in product viewed.