Guiding online beauty shoppers using Amazon Personalize with MonAmie

MonAmie is the second largest of three major players in Kazakhstan’s large beauty retail market. However, its website offered generic, nonpersonalized product recommendations using mechanical algorithm programs from the company’s enterprise resource planning system. Every visitor would be shown the same items regardless of their browsing history or preferences, resulting in suboptimal conversion rates and weak customer retention.

With a mobile app in development, MonAmie wanted to seize the opportunity to refine and personalize its online shopping environment, providing a similarly tailored experience to that offered in its brick-and-mortar stores. However, the company’s engineering team lacked the ML knowledge needed to internally create a solution. For that expertise and a vision to modernize its ecommerce experience, MonAmie turned to AWS.

MonAmie considered solutions from several major cloud service providers, but it chose AWS for its reputation and the simplicity of its technology. The company opted to adopt Amazon Personalize, which helps businesses elevate the customer experience with AI-powered personalization. Its recommendation engine is trained on Amazon.com services and helps household-name customers deliver hyper-personalized user experiences in near real time at scale, providing MonAmie with confidence in its effectiveness.

Meanwhile, AWS connected with Austria-based consultancy Softprom to serve as MonAmie’s trusted advisor during the adoption. Softprom would provide full support, including initial consulting, cost scoping, technical guidance during implementation, and on-the-ground field support in Kazakhstan.

To implement Amazon Personalize, MonAmie loaded customer profiles and purchase history from its online shop into Amazon Personalize datasets. It implemented two primary algorithms: User-Personalization-v2, which recommends items a user will interact with based on their preferences; and Item-Attribute-Affinity, which creates user segments for specific item attributes that further inform recommendations. For instance, if a customer purchases a perfume with a certain scent profile, Item-Attribute-Affinity helps guide the customer toward similar-smelling products across categories.

AWS sent instruction and conducted online meetings for technological clarifications and suggestions during the integration process, while Softprom served as the primary hands-on implementation partner. “AWS showed us great use cases that we could follow when implementing Amazon Personalize,” says Altay Kenzhebaev, head of CRM and mobile app development at MonAmie. “It put stepping stones on the path forward—showing the way we could go and what we can achieve.”

Using Amazon Personalize, MonAmie experienced 14 percent increases in ecommerce revenue and average order value, as well as a 200 percent increase in users who engage with the recommendation section. In addition to these business and customer engagement gains, the company established a foundation for multichannel expansion and positioned itself as a technology leader in the market.

MonAmie also boosted internal enthusiasm for modern technology adoption, overcoming initial team skepticism and unfamiliarity with ML tools. “When you start implementing something new, you get some resistance. But when we started using Amazon Personalize, our team understood the benefits and how easy it is. After that, they loved it,” says Kenzhebaev.

Building on momentum from this digital transformation, MonAmie plans to implement facial recognition technology in brick-and-mortar stores next year using Amazon Rekognition, which automates and lowers the cost of image recognition and video analysis with ML. The company envisions a solution that will recognize customers entering its stores and provide on-site consultants with personalized recommendations to help guide in-person shopping.

Working alongside AWS gives MonAmie confidence in this and other potential advances. “The AWS team is very friendly—great people with great ideas, making great things in a simple way,” says Kenzhebaev.