Success Story
EF Shop
Appier’s deep learning algorithms achieved a sales performance 3X better than conventional models
"Appier has been a trusted, long-term partner for EF Shop. Its AIQUA solution has transformed how we engage with our customers and the level of personalization we are able to provide. From automation to advanced hybrid algorithm recommendation, Appier's solution empowered us to offer more precise product recommendations for onsite visitors and boost revenue growth. We look forward to continuing to work with Appier to continue to provide an outstanding experience for our customers."
Grace Yang
Brand Story
EF Shop is a Taiwanese fashion e-commerce platform that offers high-quality yet affordable apparel for women, men and children. The online shop currently has over 10,000 items for its 1.5 million+ loyal shoppers to browse through. Committed to the best shopping experience for its visitors, EF Shop is constantly looking for new ways to facilitate customer engagement and provide personalized recommendations for each visitor. To this end, the company has teamed up with Appier for many years in a successful partnership that uses AI to meet and exceed what shoppers may need and want from an online shopping destination.
Goals
The fashion e-commerce market is extremely competitive and fast-paced. To stand out, EF Shop employed Appier’s AI personalization cloud solution, AIQUA, in the hopes of optimizing customer engagement on multiple channels and converting more visits into sales. The goal has been to undergo a digital transformation over the longstanding partnership and implement more and more AI elements into the website to make it more customer centric.
Challenges
Phase 1: Lacking effective multichannel engagement approach
The client, like most e-commerce stores, had multiple channels to reach potential customers but lacked an easy way to manage engagement on all channels, including the website, social media, and emails. This inability to juggle all marketing channels made it difficult for the company to capture sales opportunities from all touchpoints.
Phase 2: Need for a recommendation engine
As the client grew larger and stocked its platform with more items, it needed a way to better promote its products to shoppers. The recommendation section has always been a great place for shoppers to find relevant products that they may not have thought to look for. At this stage in their business, the client needed a recommendation engine for shoppers to better explore their site.
Phase 3: Time for more refined, personalized recommendations
In about a year’s time, the client saw tremendous growth in its business from the basic recommendation feature it adopted in Phase 2. To continue to cater to its shoppers and their evolving need for a diverse range of products and personalization in online shopping, the client needed more advanced recommendations for both products and content.
