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MyDress

121

Customer acquisition costs
dropped by 26%, while
conversions went up by 121%

127

Revenue increased by 127%,
and ROAS by 30%

56

Cost per click went
down by 56%

MyDress engaged Appier to improve audience segmentation for more effective customer targeting, essentially to drive sales and increase revenue. Appier’s AI and machine learning technology coupled with its dynamic product recommendation tool identified the most valuable users and consistently targeted them with the most relevant product recommendations.

Brand Story

MyDress is one of the top fashion e-commerce brands in Hong Kong, with a focus on bringing its customers original designs and high-quality garments that blend comfort with fashion. Launched in 2013, MyDress is partnered with more than 200 fashion brands both within and outside Hong Kong, allowing it to offer customers a wide selection of clothing and accessories.

Goal

MyDress’ goal was to effectively implement AI technology that would increase sales conversions to drive revenue. The brand also wanted to improve its overall return on advertising spending (ROAS) by finding more valuable users using precise targeting and delivering dynamic product recommendations to trigger shopper interest.

Challenges

Challenges

Rising
CACs
MyDress’s customer acquisition costs (CAC) were rising in the crowded marketplace.
Fragmented
audiences
MyDress was facing both fierce competition and fragmented audiences.
Ineffective
segmentation
Creating audience segments based on its past experience led to spending inefficiencies.
Rising
CACs
MyDress’s customer acquisition costs (CAC) were rising in the crowded marketplace.
Fragmented
audiences
MyDress was facing both fierce competition and fragmented audiences.
Ineffective
segmentation
Creating audience segments based on its past experience led to spending inefficiencies.

Appier's Solutions

Appier's Solutions

Create precise segments
MyDress used Appier’s AI to crunch the massive amount of user data, and identify more than one million customer segments based on user behavior and interests.
Predict the most valuable segments
It then leveraged Appier’s predictive machine learning model to predict the CVR of each segment in order to identify the most valuable segments – the ones most likely to convert.
Target with dynamic ads
MyDress employed Appier’s dynamic product recommendation tool to personalize product feeds and ad formats for its dynamic ads both as display ads and on Facebook.
Create precise segments
MyDress used Appier’s AI to crunch the massive amount of user data, and identify more than one million customer segments based on user behavior and interests.
Predict the most valuable segments
It then leveraged Appier’s predictive machine learning model to predict the CVR of each segment in order to identify the most valuable segments – the ones most likely to convert.
Target with dynamic ads
MyDress employed Appier’s dynamic product recommendation tool to personalize product feeds and ad formats for its dynamic ads both as display ads and on Facebook.

Client Testimonials

“We were consistently impressed by Appier’s technology expertise, as well as the team’s deep understanding of the e-commerce landscape. Thanks to this, they were able to help us implement the most effective solutions quickly and easily and guided us throughout the campaign to ensure overall success. They were extremely responsive to us and always available with a helping hand. We look forward to future engagement with Appier.”
Edmund Wong, Director, MyDress
Testimonial

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