Core Features

Analytics & Reporting

Track customer interactions and optimize your workflows

Overview

Smobi provides comprehensive analytics and tracking capabilities for customer interactions with automated workflows. Our system captures every customer interaction in real-time and provides detailed insights into workflow performance, customer journeys, and optimization opportunities.

Real-Time Event Tracking

Captured Events

We track every customer interaction with your workflows in real-time:

Message Events

  • Message Sends: When messages are sent to customers
  • Message Deliveries: When messages are successfully delivered
  • Message Reads: When customers read your messages
  • Delivery Failures: When messages fail to deliver

Button Interactions

  • Suggestion Button Clicks: When customers click on suggestion buttons
  • Carousel Card Selections: When customers interact with carousel cards
  • Global vs Local Actions: Distinguish between global and local suggestion interactions
  • Button Response Tracking: Track which buttons customers prefer
  • Node Transitions: How customers move through different workflow nodes
  • Automated vs Manual: Distinguish between automatic workflow progression and customer-initiated actions
  • Path Tracking: Complete journey through workflow steps

User Responses

  • Text Replies: When customers reply with text messages
  • Response Matching: Whether responses match expected patterns
  • Unmatched Responses: Track unexpected customer responses
  • Response Timing: How quickly customers respond

System Events

  • Workflow Starts: When workflows begin execution
  • Workflow Completions: Successful workflow completions
  • Timeouts: When workflows timeout due to inactivity
  • Errors: System errors and workflow failures

Advanced Flow Analytics

Sankey Flow Diagrams

Visual representation showing the paths customers take through your workflows:

Node-to-Node Transitions

  • Transition Visualization: See which workflow steps customers move between
  • Flow Volume: Number of customers taking each path
  • Transition Types: Automated, button click, or carousel card selection
  • Drop-off Points: Identify where customers stop engaging

Interactive Elements Tracking

  • Suggestion Interactions: Track when customers click on suggestion buttons
  • Carousel Card Engagement: Monitor interactions with carousel message cards
  • Button Performance: Which interactive elements perform best
  • Engagement Patterns: Understand customer interaction preferences

Flow Metrics

For each transition path, we track comprehensive metrics:

Quantitative Metrics

  • Customer Count: Number of customers who took that path
  • Execution Count: Number of workflow runs through that path
  • Completion Rate: Percentage of customers who complete the path
  • Average Duration: Time spent on each path

Qualitative Analysis

  • Transition Types: Breakdown of automated vs manual transitions
  • Engagement Quality: Depth of customer interaction
  • Success Indicators: Which paths lead to successful outcomes
  • Optimization Opportunities: Areas for improvement

Customer Journey Analysis

Journey Timeline

Complete chronological view of a customer’s interaction with your workflows:

Event Chronology

  • All Events: Complete list of events in chronological order
  • Time Stamps: Precise timing of each interaction
  • Duration Tracking: Time spent at each workflow step
  • Gap Analysis: Identify periods of inactivity

Journey Metrics

  • Completion Rates: Percentage of customers who complete workflows
  • Drop-off Points: Where customers stop engaging
  • Engagement Depth: How deeply customers interact with workflows
  • Journey Duration: Total time from start to completion

Execution History

View multiple workflow executions for the same customer:

Historical Data

  • Multiple Executions: Track all workflow runs for each customer
  • Pagination Support: Handle customers with extensive history
  • Execution Filtering: Filter by specific executions or date ranges
  • Sorting Options: Sort by date (newest/oldest first)

Detailed Views

  • Expandable Details: Drill down into specific execution details
  • Variable Tracking: See how variables change across executions
  • Performance Comparison: Compare different execution attempts
  • Pattern Recognition: Identify recurring customer behaviors

Path Analysis

Understand customer behavior patterns and preferences:

Behavioral Insights

  • Node Sequence: Which workflow steps customers visit
  • Path Preferences: Common paths customers take
  • Alternative Paths: Different routes to the same outcome
  • Path Efficiency: Most efficient routes through workflows

Journey Optimization

  • Total Journey Duration: Time from start to completion
  • Completion Rates: Success rates for different paths
  • Drop-off Identification: Where customers abandon workflows
  • Optimization Opportunities: Areas for workflow improvement

Workflow Performance Analytics

Node-Level Analytics

For each workflow step, track comprehensive performance metrics:

Execution Metrics

  • Total Events: Number of events at each node
  • Unique Customers: Number of unique customers reaching each node
  • Average Execution Times: Time spent at each workflow step
  • Success Rates: Percentage of successful node completions

Engagement Metrics

  • Customer Engagement Rates: How actively customers interact
  • Response Rates: Percentage of customers who respond
  • Interaction Depth: Level of customer engagement
  • Engagement Quality: Quality of customer interactions

Action Type Analytics

Breakdown of different interaction types and their performance:

Message Analytics

  • Message Sends: Number of messages sent
  • Message Deliveries: Successful delivery rates
  • Message Reads: Read rates and engagement
  • Delivery Failures: Failure analysis and reasons

Interactive Element Analytics

  • Button Clicks: Global and local suggestion interactions
  • Carousel Engagements: Card selection and navigation
  • Suggestion Performance: Which suggestions work best
  • Interaction Patterns: How customers use interactive elements

Response Analytics

  • Reply Matching: Responses that match expected patterns
  • Unmatched Responses: Unexpected customer responses
  • Response Timing: How quickly customers respond
  • Response Quality: Assess response relevance and quality

Time Series Data

Track performance over time to identify trends and patterns:

Temporal Analysis

  • Daily Event Counts: Number of events per day
  • Unique Customer Engagement: Daily unique customer counts
  • Performance Trends: How metrics change over time
  • Seasonal Patterns: Identify seasonal variations

Trend Analysis

  • Workflow Optimization: Use trends to optimize workflows
  • Performance Forecasting: Predict future performance
  • Capacity Planning: Plan for expected volume changes
  • A/B Testing: Compare performance across time periods

Multi-Channel Support

Channel-Specific Analytics

Track interactions across different messaging channels:

RCS Analytics

  • Rich Media Performance: How rich media messages perform
  • Carousel Card Engagement: Carousel-specific interaction tracking
  • Suggestion Button Usage: RCS-specific button interactions
  • Rich Content Impact: Performance of rich vs simple content

SMS Analytics

  • Traditional Text Performance: SMS message effectiveness
  • Fallback Analysis: When RCS falls back to SMS
  • SMS Engagement: How customers engage with SMS
  • Channel Comparison: RCS vs SMS performance

Cross-Channel Insights

  • Channel Preferences: Which channels customers prefer
  • Channel Effectiveness: Performance comparison across channels
  • Fallback Patterns: When and why fallbacks occur
  • Channel Optimization: Optimize content for each channel

Advanced Features

Specialized tracking for carousel messages and their components:

Individual Card Tracking

  • Card Engagement: Track engagement with individual cards
  • Card Performance: Which cards perform best
  • Card Sequence: Order of card interactions
  • Card Content Analysis: Impact of different card content

Local Suggestion Analytics

  • Local Suggestion Interactions: Button clicks within carousel cards
  • Card-to-Card Navigation: How customers move between cards
  • Local vs Global Actions: Compare local and global suggestion performance
  • Carousel Optimization: Optimize carousel design and content

Suggestion Button Tracking

Detailed analysis of customer responses to interactive elements:

Global Suggestion Analytics

  • Global Button Performance: Overall suggestion button effectiveness
  • Button Text Analysis: Impact of different button text
  • Button Type Performance: Different button types (reply, action, etc.)
  • Global Engagement Patterns: How customers use global suggestions

Local Suggestion Analytics

  • Local Button Performance: Suggestion buttons within carousel cards
  • Context-Specific Interactions: How context affects button usage
  • Local vs Global Comparison: Performance differences
  • Local Suggestion Optimization: Optimize local suggestion placement

Response Analysis

  • Response Matching: Track expected vs unexpected responses
  • Unmatched Reply Analysis: Understand unexpected customer responses
  • Response Patterns: Common response types and patterns
  • Response Quality: Assess response relevance and quality

Condition Evaluation Tracking

Monitor how workflow conditions perform and affect customer journeys:

Condition Performance

  • Condition Group Matching: Which condition groups are matched
  • Field-Level Results: Detailed condition evaluation results
  • Default Path Usage: When conditions aren’t met and defaults are used
  • Condition Optimization: Identify and optimize condition logic

Conditional Flow Analysis

  • Branch Performance: How different conditional branches perform
  • Condition Complexity: Impact of complex conditions on performance
  • Condition Accuracy: How well conditions predict customer behavior
  • Condition Refinement: Improve condition logic based on data

Real-World Applications

Workflow Optimization

Use analytics to identify and resolve workflow issues:

Bottleneck Identification

  • Drop-off Points: Identify where customers abandon workflows
  • Performance Bottlenecks: Find slow or problematic workflow steps
  • Engagement Issues: Identify low-engagement areas
  • Completion Barriers: Find obstacles to workflow completion

Optimization Strategies

  • Path Optimization: Optimize workflow paths based on data
  • Content Improvement: Improve message content and timing
  • Condition Refinement: Refine conditional logic
  • Interactive Element Optimization: Optimize buttons and carousels

Customer Experience Improvement

Understand and improve customer interactions:

Journey Mapping

  • Customer Journey Visualization: Visual representation of customer paths
  • Experience Optimization: Improve customer experience at each touchpoint
  • Personalization: Use data to personalize customer interactions
  • Engagement Enhancement: Increase customer engagement

Conversion Optimization

  • Conversion Tracking: Track which paths lead to successful outcomes
  • Conversion Optimization: Optimize workflows for better conversion
  • A/B Testing: Test different workflow variations
  • Performance Measurement: Measure impact of optimizations

Debugging and Troubleshooting

Quickly identify and resolve workflow issues:

Issue Identification

  • Error Tracking: Track and analyze workflow errors
  • Performance Issues: Identify performance problems
  • Customer Complaints: Track and analyze customer feedback
  • System Issues: Monitor system health and performance

Resolution Support

  • Root Cause Analysis: Identify root causes of issues
  • Quick Fixes: Implement quick fixes based on analytics
  • Preventive Measures: Prevent issues before they occur
  • Continuous Improvement: Continuously improve based on data

A/B Testing

Compare different workflow versions and customer paths:

Testing Framework

  • Version Comparison: Compare different workflow versions
  • Path Testing: Test different customer paths
  • Content Testing: Test different message content
  • Timing Testing: Test different send times and intervals

Analysis and Optimization

  • Statistical Analysis: Ensure test results are statistically significant
  • Performance Comparison: Compare performance across variations
  • Optimization Implementation: Implement winning variations
  • Continuous Testing: Continuously test and Optimize

Next Steps