Berrybenka's Success: Boosting Engagement and Conversions with Machine Learning and Personalisation

Berrybenka is a leading online fashion and beauty store based in Indonesia. The company sells more than 1000 local and international brands, including its own-label products. Berrybenka aims to provide a seamless shopping experience to its users across multiple channels. The company is committed to delivering personalized and targeted engagement experiences to its users to maximize conversions. Berrybenka's customer base includes users who explore specific product collections and those who have completed a purchase recently.

Berrybenka, a leading online fashion and beauty store in Indonesia, faced the challenge of maximizing conversions and creating a unified customer experience across channels. The company wanted to identify opportunities to provide a personalized and targeted engagement experience to its users. The challenge was to effectively segment their customer base and deliver targeted communication based on users' activity. This included users who explored a specific product collection or those who had completed a purchase recently. The company also needed to optimize their push notification campaigns to achieve the desired engagement.

Berrybenka leveraged MoEngage’s deep-dive analytics to deliver segmented campaigns based on users’ activity. This allowed them to deliver targeted, personalized communication, resulting in a significant increase in engagement. The company also used MoEngage Smart Triggers powered by Sherpa, a set of machine-learning algorithms, to optimize the timing, content, and delivery of push notifications. This resulted in a significant increase in engagement for push notification campaigns. Additionally, Berrybenka used MoEngage's superior Web push notifications to engage, retain, and convert visitors on their website. They targeted cart abandoners, resulting in a high click-through rate (CTR) and a significant percentage of users completing a purchase on the website. Finally, Berrybenka used segmented, targeted in-app messages to drive first-time purchases and boost revenues during holiday sales and other ‘sale occasions.’

• The implementation of machine learning, segmentation, and personalisation significantly improved Berrybenka's operational efficiency. The company was able to deliver a unified customer experience across channels, which was one of their primary objectives. The use of deep-dive analytics for segmentation allowed Berrybenka to deliver targeted and personalized communication to its users, enhancing the overall user experience. The optimization of push notification campaigns using machine learning algorithms resulted in a significant increase in engagement. The use of web push notifications helped Berrybenka engage, retain, and convert visitors on their website, particularly targeting cart abandoners. The use of in-app messages in conjunction with push notifications provided a seamless brand experience to app users, driving first-time purchases and boosting revenues during sales occasions.

• 14X Increase in engagement for segmented, personalized and targeted campaigns
• 2.8X Increase in engagement for push campaigns that were auto-optimized using machine-learning algorithms
• 17% of users coming through in-app messages completed a purchase on the app