Technology Category
- Analytics & Modeling - Big Data Analytics
- Analytics & Modeling - Data-as-a-Service
Applicable Industries
- Apparel
- Equipment & Machinery
Applicable Functions
- Procurement
- Sales & Marketing
About The Customer
Cocomelody is a renowned bridal brand offering haute couture for bridal and wedding parties at affordable rates. The brand is known for its omnichannel retailing across offline and online stores, ensuring shoppers get a unique, hassle-free buying experience. Cocomelody has catered to more than 6,000 brides and 18,000 bridesmaids across the U.S. and China. The brand’s unique categories such as Material Swatches (look, feel and see color and fabrics for customized dresses) and Try at Home (try bridal dresses at $25 and buy only if you like it) has provided them an edge with their customers.
The Challenge
Cocomelody, a popular bridal brand, was facing challenges in maintaining customer engagement and increasing conversion rates. Despite using multiple tools for cross-channel customer engagement and online ads with Google and Facebook, the brand was experiencing a significant drop in users at various stages of the purchasing journey. The conversion rates of their ads were not growing, negatively impacting their overall return on online ad spend (ROAS). The brand also identified a lack of dynamic messaging and intuitiveness on their website and app, and they were unable to pinpoint the exact drop-off points. Overall, they lacked crucial data analytics and the ability to personalize engagement campaigns. The brand's team decided to opt for a more dynamic and centralized engagement tool that would enhance customer interaction.
The Solution
Cocomelody's marketing team decided to partner with MoEngage and deploy its customer engagement platform to address their challenges. The team aimed to centralize data from physical boutiques and its website to understand exactly where and why customers were dropping off. They also wanted to provide relevant messaging on the website to ensure users coming in from ads don’t abandon the site. The team created new economical categories such as 'Try at Home' and 'Fabric Swatches' to attract user attention and drive them to make more purchases. By analyzing user data more deeply, they were able to understand user shopping preferences and run targeted campaigns catering to these new categories. Personalized messaging helped showcase their economical haute couture fashion while engaging customers at the right moment to drive users to complete a purchase.
Operational Impact
Quantitative Benefit
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