In early childhood, the first five years of a child’s life are critical for brain development. Yet, in many classrooms, children already lag behind before formal schooling even begins — struggling with basic numbers while the rest of the class moves ahead.
Recognizing the importance of these formative years, Rocket Learning has been working to bridge this gap by partnering with parents, teachers, and government systems to bring foundational learning into homes and classrooms. Their tool of choice? WhatsApp.
And recently, they’ve taken their WhatsApp strategy to the next level — introducing a chatbot powered by Glific, an open-source WhatsApp engagement platform.
Why WhatsApp?
Rocket Learning’s core model involves sending bite-sized learning activities via WhatsApp groups to both parents and teachers. These activities — like asking parents to find five colored objects with their child, or suggesting classroom games — build awareness and show adults how to engage children meaningfully.
Why WhatsApp and not an app? “Our audience uses basic smartphones,” explains Amit, from Rocket Learning. “An app wouldn’t work — it wouldn’t run well on their phones, and engagement would drop. WhatsApp is familiar. Even in rural settings, people already use it daily — checking statuses, chatting, and participating in groups.”
But the WhatsApp groups had a limitation: they were primarily one-way. Parents and teachers received content, but Rocket Learning had no way to learn what these users wanted or how they experienced the activities.
The Challenge: Moving Beyond One-Way Communication
To understand user preferences and improve engagement, Rocket Learning piloted Glific with around 1,000 users — a mix of parents and teachers.
Glific enabled a two-way dialogue, letting users ask questions, choose the content they wanted, and respond in real-time.
“Through Glific we started seeing what kinds of questions users actually asked,” Amit says. “It helped us understand their behavior patterns too — like what time they read and responded to messages.”
Insights from the Pilot
The pilot, which ran between October and November 2024, revealed several key insights:
📊 Behavior Patterns
- Most users responded to messages within two hours of receiving them — a critical insight for scheduling nudges.
- Engagement peaked at certain times of day, depending on the audience — teachers during work hours, parents at night.
🎯 User Preferences
- Parents were eager to share their needs — preferring stories, poems, or specific activities for their children.
- The chatbot provided real-time data that previously required costly on-ground surveys.
🤔 Unexpected Challenges
- Many users struggled with the chatbot flow, showing low tech savviness.
- Parents often sent very short prompts like just a child’s name (“Aryan”) or an age (“3 years”), expecting a full story or activity in response.
- Rocket Learning adapted the chatbot to accept these short prompts and guide users with more examples.
Re-Engaging Users
One notable benefit of Glific was its ability to bring back inactive users.
Through well-timed nudges — such as reminders about activities or invitations to request a bedtime story — Rocket Learning re-engaged around 30% of users who had become inactive.
However, Amit notes: “Habit-building takes time. We realized that nudging has to be consistent — you have to keep reaching out at the right moments to make it a habit.”
What’s Next?
Rocket Learning plans to deepen the integration of Glific into their main WhatsApp workflows.
- The chatbot will soon help users with FAQs — about certificates, medals, and other rewards distributed through Rocket Learning’s programs.
- Nudges will be tailored more precisely — for example, reminding teachers when a classroom is about to open or asking if they completed the day’s activity.
- The team aims to scale this engagement to reach over 150,000 anganwadi workers and teachers — while maintaining personalization.
Why Glific?
Rocket Learning chose Glific over alternatives because it offers:
- An easy-to-build flow-based interface for designing conversations.
- Integration with GPT, enabling context-aware replies.
- Analytics that provided actionable insights into user behavior.
- Flexibility as an open-source tool to customize for their unique needs.
Key Learnings
From the pilot, Rocket Learning learned that:
- Familiar platforms like WhatsApp are crucial for engaging low-tech users.
- Short, simple prompts should be expected — chatbots must be designed accordingly.
- Regular, well-timed nudges are critical to sustain engagement.
- Behavioral insights — like peak response times — can make communication more effective.
Conclusion
For Rocket Learning, the Glific-powered chatbot has opened a new chapter in their mission — transforming early childhood education by listening, learning, and engaging at scale.
By combining Glific’s technology with their existing WhatsApp outreach, Rocket Learning is creating a more responsive, user-centered ecosystem. One that meets users where they are — and ensures that every child has a fair chance to thrive, one conversation at a time.