Popular U.S. Bridalwear Brand Cocomelody Boosts Repurchase Rates by 27%
Discover how Cocomelody used MoEngage’s Dynamic Messaging and Omnichannel Flows to increase their repurchase rate by 27%, leading to a 30% increase in overall sales.
About Cocomelody
Cocomelody is a brand offering haute couture for bridal and wedding parties at affordable rates. Known for its omnichannel retailing, the brand caters to more than 6,000 brides and 18,000 bridesmaids across the U.S. and China.
MoEngage is the best data-centralized CRM system and the best multi-channel marketing tool we’ve found. Using MoEngage, we can add as many attributes and custom events as we like to profiles, then filter customers for various campaigns and offers. It is very easy to unify data, engage and analyze our results.
Over a period of time, Cocomelody observed steep user drop-offs at various stages of the purchasing journey. Similarly, their ads’ conversion rates were not growing, which impacted their overall ROAS (return on online ad spend).
Cocomelody’s team decided to employ MoEngage platform to centralize data from physical boutiques and its website to understand where and why customers are dropping off. Also, strategized to offer personalized engagement across channels based on the aggregated analysis.
The Cocomelody team created two new economical categories to reduce customer drop-offs. Using MoEngage Analytics, they understood shopping preferences and ran focused campaigns on these categories along with personalized messaging, to drive better conversions.
• 30% more sales under the ‘Try at Home’ category
• 27% increase in repurchase rate
• 69% boost in return on online ad spend
• 5% higher cost value reconciliation
Using MoEngage, the team identified abandoned customers and what products they abandoned. On establishing customer intent, they segmented them based on LTV and behavioral actions. The team then engaged customers across email, SMS and Web Push using Flows, along with personalization using DPM.
The team further utilized MoEngage Analytics to see customers’ wishlist items, product searches, and understand fabric preferences. On identifying that 95% of drop-offs who had wishlisted a product actually had the intent of buying it, the team created smart-triggered Flow campaigns to target them.
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