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Shiprocket Cuts Campaign Setup Time by 70% with Merlin AI

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22%

Improvement in Open Rates using AI-optimized content

70%

Reduction in Manual Work

Shiprocket
About Shiprocket

Shiprocket, India’s leading e-commerce enablement platform, empowers over 400,000 sellers nationwide. Catering to everyone from home-grown brands to large enterprises, Shiprocket streamlines shipping, marketing, and payments. By leveraging data-driven insights, the platform simplifies supply chains and drives smarter business decisions.

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Helping Sellers Before They Ask

For Shiprocket, staying in touch with sellers is about support throughout their business life. The team adopted a way of working that aims to predict what a seller needs before a problem occurs. By reviewing a seller's history, they can determine the right time to send a shipment update or to suggest a new service. They use AI to help turn logistics data into helpful notes that go out at the right time.

Helping Sellers Before They Ask

Transitioning to a predictive engagement model was a critical step for our B2B e-commerce ecosystem. By leveraging Merlin AI, we are moving toward a future where we don't just react to seller actions, we anticipate them. Mapping our in-house seller profiles into predictive journeys has allowed us to support our sellers with a level of precision that was previously impossible.

Dhyani Doshi

Director - Growth and Marketing

Shiprocket is an e-commerce enabler, and our communication needs to reflect that. Consolidating our web and mobile engagement into a single, AI-powered stack has allowed us to automate critical journeys and identify drop-offs in real-time using predictive signals.

Aditya Biswas

Associate Manager - Growth and Marketing

Strategic Opportunities for Growth

As Shiprocket grew, the team found a few areas where they could work better to support their sellers:

Connecting the seller experience: The team wanted to move away from using different tools for their website and app. They needed one place to see everything a seller was doing, so the communication stayed the same across every channel.

Predicting what comes next: Instead of just reacting to problems, they wanted to know which sellers might stop using the service or who might need cargo shipping in the next 30 days.

Managing data at scale: With so many sellers, sorting through information like shipment weight and frequency by hand was becoming too much work. They needed a way to automate how they grouped sellers and shared advice.

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Building the Predictive Ecosystem

Shiprocket moved all its seller data and communication into one place. This change happened in about 40 days, giving them a clean starting point for using predictive tools.

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Phase 1: Tech Stack Consolidation for AI Readiness

Shiprocket executed a strategic consolidation, replacing multiple legacy tools with a unified MoEngage implementation. This migration, completed in just 30-40 days, established the clean data foundation necessary for Predictive Analytics to process seller attributes and event mappings at scale, ensuring the brand was ready for predictive execution. Before this execution, the marketing and operations teams spent 8 to 10 hours every week just sorting through data and setting up campaigns. Now, that same work takes them only 1 to 2 hours.

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Phase 2: Predictive Intelligence and Segment Forecasting

The team is leveraging predictive features to gain a future propensity view of its seller base. By analyzing complex variables such as shipment frequency and wallet activity using Merlin’s predictive features, Shiprocket’s team can now forecast what a seller might do over the next 7, 10, or 30 days. This allows the team to identify high-potential seller profiles and proactively address those at risk of churn before they exit the ecosystem.

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Phase 3: Proactive Automation and Best-Time Configuration

Building on these predictive insights, Shiprocket configured automated Flows and Journeys designed to intervene at critical milestones.

Predictive Best-Time-to-Send: Leveraging AI-driven timing, Shiprocket ensures critical business updates reach sellers at the times they are most likely to interact with their dashboards.

Reactivation Strategies: Shiprocket uses custom dashboards to monitor experiments aimed at reactivating "dormant" sellers, leveraging predictive signals to offer personalized incentives and wallet updates.

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Phase 4: High-Performance Omnichannel Execution

The predictive foundation has significantly amplified the performance of Shiprocket’s priority channels, SMS and Email.

Personalized SMS: In B2B logistics, SMS is still a very effective way to reach people. By personalizing SMS with variables like company name and specific transaction info, Shiprocket achieved a 1% CTR, an exceptional benchmark for the industry.

Dynamic Email Engagement: Utilizing dynamic variables like wallet activity and last transaction details, email campaigns consistently drive 18% to 22% open rates, ensuring sellers stay proactive in managing their business health.

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Products Used

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Custom Segments

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Customer Journey Orchestration

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Merlin AI

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MoEngage Analytics

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Omnichannel Flows

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Smart Recommendations

Impact and Value

The transition to a unified, predictive engagement model has allowed Shiprocket to support its sellers with greater precision and operational agility:

  • 18%-22% Improvement in Open Rates driven by AI-optimized content and timing.
  • Reduced manual work from 10 hours a week to 1-2 hours.
  • 1% CTR increase, which is significant, outperforming industry averages through predictive targeting.
  • 30-40 Day Migration to a fully unified production environment across web and app.
  • 7, 10, and 30-Day Predictions enabling early intervention in seller lifecycles via Merlin AI.

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