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Success Story


Personalized recommendations increased CVR by 4.4X

“The Appier team demonstrated strong performance from the initial stages of our work together. Their AI recommendations worked great by considering various and crucial purchase factors for our commerce business. We enjoyed working with Appier and will continue to build delightful personalized experiences for our customers.”

Co-Founder of Doublewoot




Disjointed approach to marketing that failed to sync up all available channels

With various digital and social channels, the client did not fully integrate them cohesively into its marketing strategy to target its potential customers. Social media posts, email campaigns and the website felt separate, instead of complementary marketing components that drove traffic and sales.

Lackluster user experience without recommendations or other engagement

The e-commerce platform itself lacked advanced, personalized recommendations that would match shoppers with products and prompt shoppers to stay engaged with the site.


A multichannel solution for engaging users at different stages of the customer journey

The client leveraged AIQUA to automatically deliver custom campaigns to different segments of customers. The platform understands that each customer is at a different stage in their customer journey, and with varying degrees of familiarity and experience with the brand, their actions will vary. AIQUA uses different marketing collaterals with purposeful calls to action. Based on such user behavior, the client introduced a membership program and successfully registered 25% of the users targeted for the program using pop-ups within a 3-month period. The pop-ups for the membership program, which comes with exclusive discounts and other perks, also yielded an increase in average order value of 15 USD compared to that of shoppers who did not see or click on them.

Image and other AI-powered recommendations for a personalized browsing experience

AIQUA’s deep learning models allowed the client to showcase personalized content to visitors on their channels. These included more curated recommendations based not only on what similar shoppers have viewed but also on what each shopper has interacted with. With Appier’s deep image learning technology, the client could show shoppers items that are similar in color, style, look and feel to what they have expressed interest in. Having recommendations dramatically increased Doublewoot’s page views by 3.9 times and session duration by 4 times the previous amounts. Other personalized content, such as the trigger-based email campaigns, saw similar growths in open and conversion rates (5.2x and 4.4x, respectively).

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