Conversation Types
1:1 Chat Analytics
Individual conversations between your team and customers:Group Chat Analytics
Team or broadcast group activity:Message Flow Analysis
Understanding where messages come from and go:Inbound vs Outbound
A healthy conversation has balanced back-and-forth. If you’re sending 5 messages for every 1 reply, your messaging may not be resonating.
Message Categories
Follow-up Analytics
Track your follow-up effectiveness:Follow-up Performance by Sequence Position
Conversation Quality Indicators
Signs of High-Quality Conversations
Red Flags to Monitor
Analyzing by Time Period
Best Times for Engagement
Track when your messages get the best response:Day of Week Analysis
Segment Analysis
Compare conversation metrics across customer segments:Using Insights for Improvement
Optimize Message Content
Use response rate data to identify which message types resonate best with your audience
Perfect Your Timing
Send messages when data shows recipients are most responsive
Refine Follow-up Cadence
Adjust follow-up frequency based on response rate by sequence position
Segment Your Approach
Customize messaging strategy based on segment-specific analytics
Best Practices
Monitor the 80/20
Monitor the 80/20
Focus on the 20% of conversations that drive 80% of results. Identify patterns in your most successful interactions and replicate them.
Act on red flags quickly
Act on red flags quickly
When you see warning signs like increasing non-response rates, investigate immediately. Small issues become big problems if ignored.
Compare apples to apples
Compare apples to apples
When analyzing, compare similar time periods (this Tuesday vs last Tuesday) rather than different conditions (weekday vs weekend).
Correlate with outcomes
Correlate with outcomes
Conversation metrics only matter if they lead to results. Always connect messaging data to business outcomes (sales, support resolution, etc.).