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Introduction of MishiPay’s Item Recommendations Feature
Share this with your colleagues Introduction At MishiPay we started because we hated waiting in a line. Now that shoppers never have to wait in
Learn how MUJI combines MishiPay Scan & Go and Product Recommendations, enabling them to benefit from Amazon Go levels of checkout efficiency whilst simultaneously increasing average basket value and sales growth.
MUJI, one of the world’s leading variety and homeware retailers, deployed MishiPay at the end of 2020 and have seen more than 100,000 users benefit from our enhanced shopping experience. Our Scan & Go technology enables in-store shoppers to scan the items they want to buy using their own phones, pay using a variety of convenient digital payment methods and then simply leave the store. Users do not have to download an app or register; they can scan products with their smartphone camera and pay using card or Apple Pay, Google Pay or AliPay making it a 1-click checkout journey.
In late Q4 2021 MishiPay deployed the first version of our in-store Product Recommendations technology:
18% of what customers purchased came from MishiPay Product Recommendations
Customers discovered and bought on average one new product via Product Recommendations
MishiPay took care of all the heavy lifting; zero involvement was required from the client to enable this feature
Challenges
The motivation was to improve the customer journey by enabling the shoppers to discover new products, , find great combinations for the items they want to buy and improve visibility of in-store promotions.
However, challenges exist on an operational and technical level. In-store product recommendations have not been deployed before on a Scan & Go application, making it a UX, engineering and operations challenge. Our engineering team had to experiment with different approaches and machine learning models while keeping in-store constraints in mind, like inventory availability, the user’s position in the store and product catalog updates (see more here).
Solution
Knowing that speed and efficiency are key to a deployment of a new feature during the pre-Christmas peak trading time, MishiPay deployed the feature without requiring time or resource from the customer’s side. No extra integration, UAT or data sharing was required in order for MishiPay to enable the feature.
Enabling Product Recommendations gave MUJI a better understanding about user preferences and analytics. When customers were presented with recommended products, MishiPay captured the data about which barcodes trigger recommendations and which products are successfully bought from the recommendation carousel.
MUJI saw an 18% increase in revenue (Sales Growth) from the deployment of Product Recommendations. Customers on average bought one new product directly from the recommendations.
To find out more about bringing the power of Product Recommendations to your store, please contact us to increase your retail sales growth.
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