Re-engagement
Definition
Re-engagement in chatbots involves proactively reaching out to users who have previously interacted with the bot but not returned — or who abandoned a conversation before completing a task. Re-engagement messages are sent via a channel the user has opted into: WhatsApp notifications, push notifications, email, or SMS. They may reference the previous interaction ('You were asking about our enterprise plan — still have questions?') or highlight something new (a new feature, a promotional offer, or an update relevant to the user). Re-engagement is only possible on channels that support outbound messaging and with proper user consent.
Why It Matters
Most chatbot conversations end without complete resolution — users get distracted, leave the page, or decide to think about it. Re-engagement messages give businesses a second chance to help these users, recover abandoned flows, and convert interested prospects who didn't quite reach their goal. For customer support, re-engagement can proactively resolve issues before a user escalates to another channel.
How It Works
Re-engagement campaigns are configured with trigger conditions (e.g., user abandoned a conversation in the middle of a pricing inquiry more than 24 hours ago) and message templates. The platform checks these conditions against the conversation log database and sends messages to qualifying users via their opted-in channels. Response rates and conversation re-openings are tracked as campaign metrics.
Real-World Example
A user started a free trial sign-up flow, got halfway through, and left. 48 hours later, a WhatsApp re-engagement message arrives: 'Hi! You were signing up for a free trial with 99helpers. Your spot is still waiting — would you like to complete your setup?' The user taps 'Yes' and is taken directly back to where they left off in the flow.
Common Mistakes
- ✕Sending re-engagement messages without explicit user consent — unsolicited outreach is not only annoying but may violate GDPR/CCPA.
- ✕Re-engaging too aggressively or too frequently, training users to ignore messages from the channel.
- ✕Sending generic re-engagement messages instead of contextual ones that reference the specific interaction the user had.
Related Terms
Proactive Messaging
Proactive messaging is when a chatbot initiates a conversation with a user rather than waiting for the user to speak first. Triggered by user behavior, time-based rules, or business events, proactive messages can offer help, share relevant information, or guide users toward key actions at the right moment.
Proactive Chat Trigger
A proactive chat trigger is a rule or event that automatically opens the chat widget and initiates a conversation — without the user clicking the chat icon. Triggered by page behavior, time on site, exit intent, or user attributes, proactive triggers increase engagement by reaching users at the right moment.
Chatbot Analytics
Chatbot analytics is the measurement and analysis of chatbot performance — tracking metrics like conversation volume, resolution rate, fallback rate, escalation rate, and user satisfaction. These insights reveal how well the bot is performing and where to focus improvement efforts.
Session Management
Session management in chatbots refers to how the system tracks and manages individual conversation sessions — defining when a session starts and ends, maintaining session-scoped state, and handling session expiry. Proper session management ensures context is preserved within a conversation and cleanly reset between separate interactions.
Chatbot Feedback
Chatbot feedback is the collection and analysis of user opinions about their chatbot experience — typically through thumbs up/down ratings, star ratings, or short surveys. It provides direct user signal on response quality, helping teams identify failures and prioritize improvements.
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