Fynd's Remarkable 129% Increase in Retention Through Predictive Segmentation

• Analytics & Modeling - Predictive Analytics
• Cybersecurity & Privacy - Identity & Authentication Management

• Consumer Goods
• Retail

• Procurement
• Sales & Marketing

• Inventory Management
• Retail Store Automation

Fynd, India's largest omnichannel platform for retail businesses, was facing a significant challenge with customer retention. Despite being a rapidly growing company, they found that only 2% of their customers were returning to the app within an 8-week period after signing up. This low retention rate was directly impacting their revenue metrics. Upon investigation, the growth team at Fynd discovered that customers were receiving irrelevant emails, leading to low open rates of just 3% from a customer base of 15,000. This situation was not only ineffective but also risked annoying customers and causing further churn. Fynd needed a solution that would allow them to identify customers who would respond positively to marketing communication and exclude those who would react negatively. They also needed to optimize their marketing efforts to ensure every communication was relevant to each customer without increasing campaign costs.

Fynd is India's largest omnichannel platform for retail businesses, enabling retailers to manage everything from a single dashboard through a centralized inventory, campaign, and order management solution. The company operates a store management portal for retailers and a marketplace for consumers, which runs on both an app and a website. The majority of their audience consists of consumers within the 18-35 age group, who are primarily deal hunters shopping due to discounts. A subsection of this group, composed of 18-25 year-olds, seeks even higher discounts. Despite the website seeing 3X more traffic, the app generates over 80% of the revenue.

Fynd turned to MoEngage Predictions, a tool that predicts customer behavior with up to 96% accuracy and 99% precision. The team at Fynd used this tool to identify the segment of their audience that would respond positively to their email messaging and exclude any customers who would react negatively. The Predictions algorithm created segments based on factors such as conversion, churn, dormancy, product addition, and campaign effectiveness. Using these segments, Fynd was able to identify their optimal target audience for their next campaign. They targeted customers with a medium to high propensity to add products and open emails, and a medium to low propensity to go dormant. They excluded customers with a high propensity to uninstall. As a result, their email base increased from 15,000 to 25,000 customers. However, this time, the target audience was more relevant and therefore more likely to respond positively. The open rates for this campaign doubled to 6-8% even as audience size increased by 66%.

• The use of MoEngage Predictions allowed Fynd to significantly improve their customer retention rates by optimizing their email marketing strategy. By segmenting their audience based on predicted behaviors, they were able to target their communications more effectively, resulting in a more engaged and responsive customer base. This approach not only increased the number of customers returning to the app but also improved the relevance of their communications, reducing the risk of customer churn due to irrelevant emails. The insights-led engagement strategy enabled Fynd to create more delightful experiences for their customers, standing out in a competitive market and driving growth.

• Retention from signups to app open within an 8-week period increased 129%, from 2.29% to 5.24%

• The email base increased from 15,000 to 25,000 customers, a 66% increase

• Email open rates doubled to 6-8%