AI Insights Advanced

Conversational Analytics Deep Dive

2 min read Updated February 11, 2026
Advanced techniques for getting the most out of clariBI's AI-powered conversational analytics.

Master the art of asking questions to your data.

Accessing Conversational Analytics

Entry Points

  • Chat Icon: Top navigation bar
  • Dashboard Chat: Within any dashboard
  • Analytics View: Dedicated analytics page
  • Quick Access: Keyboard shortcut Ctrl/Cmd + K

Query Techniques

Basic Queries

Simple metric requests:
- "Show total revenue"
- "How many customers do we have?"
- "What were sales yesterday?"

Comparative Queries

Period comparisons:
- "Compare this month vs last month"
- "Year-over-year growth rate"
- "How does Q4 compare to Q3?"

Trend Queries

Pattern analysis:
- "Show revenue trend for 2024"
- "Is customer churn increasing?"
- "Plot daily active users"

Ranking Queries

Top/bottom analysis:
- "Top 10 products by revenue"
- "Worst performing campaigns"
- "Highest value customers"

Filtering Queries

Segmented analysis:
- "Revenue from California customers"
- "Sales for product category Electronics"
- "Conversions from mobile devices"

Advanced Techniques

Multi-Dimensional Analysis

```
"Show revenue by product category and region"
"Customer acquisition cost by channel and quarter"
"Support tickets by priority and team"
```

Calculated Metrics

```
"What's our profit margin?"
"Calculate customer lifetime value"
"Show conversion rate trend"
```

Predictive Questions

```
"Forecast next month's revenue"
"Predict customer churn risk"
"What will sales be in Q1?"
```

Optimizing Responses

Be Specific

Instead of: "How are we doing?"
Try: "What's our month-over-month revenue growth for Q4 2024?"

Specify Time Periods

Include clear date references:
- "Last 30 days"
- "This quarter"
- "January 2024"
- "Year-to-date"

Name Your Metrics

Use exact metric names when known:
- "MRR" instead of "monthly revenue"
- "CAC" for customer acquisition cost
- "NPS" for net promoter score

Understanding Responses

Response Types

  1. Number Cards: Single metric answers
  2. Charts: Visual trend/comparison data
  3. Tables: Detailed breakdowns
  4. Insights: AI-generated observations

Follow-Up Questions

The AI remembers context:
- "Break that down by region"
- "Now show last year"
- "Exclude refunds"
- "Only enterprise customers"

Best Practices

Query Strategy

  1. Start broad, then narrow down
  2. Use follow-ups for deeper analysis
  3. Save useful queries for reuse
  4. Share insights with team

Credit Efficiency

  • Be specific to avoid multiple queries
  • Use filters in initial query
  • Combine related questions

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