Popular U.S. Bridalwear Brand Cocomelody Boosts Repurchase Rates by 27%
Cocomelody is a bridal brand focused on 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 experience throughout.
Cocomelody has been catering to more than 6000 brides and 18000 bridesmaids across the US 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.
Cocomelody’s marketing team has been driving customer engagement across channels using multiple tools. Additionally, the team was using online ads (Google and Facebook) driving users to their website and app. However, over a period of time, the brand observed user drop-offs at various stages during a purchase journey. Similarly, their ads’ conversion was not growing, thereby affecting the overall ROAS (return on online ads). The brand team realized a lack of dynamic messaging on the website and the app needed quick attention. Also, the current tools were not assisting the team in understanding the exact drop-off points. This caused the team to recognize the missing intuitiveness of the tools along with the lack of data analytics and personalized engagement campaigns.
Cocomelody’s team decided to opt for a more dynamic and centralized engagement tool that will help them do more and engage better.
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.
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.Cocomelody’s marketing team had a clear vision of what they need from an automated engagement tool:
- Centralize data from physical boutiques and website to know exact drop-offs points by analyzing this data.
- Provide relevant messaging on the website to ensure users coming in from ads don’t drop-off.
- Offer personalized engagement across channels (emails, website) based on this data.
The brand decided to partner and employ MoEngage’s customer engagement platform as it offered a dynamic approach to user engagement.
Reducing Drop-offs by Promoting Cost-effective Categories
The brand’s marketing team devised a smart approach i.e., promote economical categories to reduce the user drop-offs. These economical categories such as Try-at Home and Fabric Swatches will attract users’ attention thereby driving them to make more purchases.
To do this, the team wanted to analyze user data, understand their preferences, and run two campaigns catering to two categories. Similarly, use personalized messaging to showcase their economical haute couture fashion while engaging at the right moment. Eventually, the whole approach will drive users to complete a purchase.
As a bridal fashion site with the intent to encourage users to purchase dresses from an online store, it was imperative for the brand to create trust within its userbase. The best way to go about this was to allow the users to look, feel, and try-out bridal dresses before purchasing. The team knew that many users abandoned their carts during their purchase and some others explored product catalogs but never purchased. So the brand team decided to run category-based campaigns for their exclusive ‘Try-at Home’ category specifically for these abandoned users. This category allowed users to try any wedding dresses at $25 straight and nudge them to purchase the final bridal dress.
The team utilized MoEngage Analytics to analyze the user traffic data to understand who are these abandoned users and what products they abandoned or searched. Once the team established the users’ intent on dresses, they segmented based on LTV and behavior actions (checkout success, last known city, and active in last 30 days). Using this data, the team started engaging users on the website. The team used MoEngage Flows along with channels such as Email, SMS, and Web Push. The team then personalized these campaigns using MoEngage DPM (Dynamic Product Messaging) that allowed the team to trigger messages based on users’ dress preferences.
Campaign 2: Fabric Swatches
Apart from ‘try-at home’ category, the brand also offered fabric swatches allowing users’ to look at a variety of fabrics and order their preferences at $2 to $5. The idea behind promoting this category was to give users the option to see and feel the fabric based on their liking, then order a customized dress using that fabric.
The team again utilized Analytics to know users’ wishlist items and other product searches and understand the fabric and color preferences. This is because the team knew that 95% dropoff in users who add a product to the wishlist has the intent of purchasing the product. The team saw potential here and created a smart-triggered Flow campaign to target the users dropping off. The team utilized Flows campaign to promote various fabrics by sending smart-triggered push and Web Push notifications.
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.
