Section 6: Analytics
Analytics dashboards help you understand performance, measure impact, and make data-driven decisions. Auxia Console provides two main analytics views: Goal Analytics and Journey Analytics.
6.1 Analytics Overview
What Analytics Shows
Analytics in Auxia Console helps you answer:
- Are we achieving our goals? (Goal Analytics)
- How are journeys performing? (Journey Analytics)
- What's the real impact? (Uplift measurement)
- Which treatments work best? (Treatment comparison)
Analytics Navigation
- Click Analytics in the sidebar
- Choose:
- Goal Analytics - Goal-level performance
- Journey Analytics - Journey-level performance
6.2 Goal Analytics
Goal Analytics shows performance toward your business goals.
Accessing Goal Analytics
- Click Analytics > Goal Analytics
- Select an goal from the dropdown
What is an Goal?
An goal is a measurable business goal:
- Increase purchases
- Boost app engagement
- Reduce churn
- Drive signups
Key Metrics
| Metric | Description | Calculation |
|---|---|---|
| Conversions | Number of goal completions | Count of goal events |
| Treatment Rate | Conversion rate for treated users | Treatment conversions / Treatment users |
| Control Rate | Conversion rate for control group | Control conversions / Control users |
| Uplift | Impact of treatments | (Treatment Rate - Control Rate) / Control Rate |
Understanding Uplift
Uplift measures the incremental impact of your treatments.
Uplift = (Treatment Rate - Control Rate) / Control Rate × 100%
Example:
- Treatment conversion rate: 5.0%
- Control conversion rate: 4.0%
- Uplift = (5.0 - 4.0) / 4.0 = 25%
This means your treatments drove a 25% improvement in conversions.
Goal Analytics Dashboard
The dashboard shows:
| Section | Content |
|---|---|
| Summary KPIs | Total conversions, conversion rate, uplift |
| Trend Chart | Performance over time |
| Journey Breakdown | Which journeys contribute to this goal |
| Treatment Performance | Individual treatment metrics |
Date Range Selection
Filter analytics by time period:
- Today
- Yesterday
- Last 7 Days
- Last 30 Days
- Last 90 Days
- Custom range
Interpreting Results
Positive Uplift (Good):
- Treatments are driving incremental conversions
- Your personalization strategy is working
Zero/Negative Uplift (Investigate):
- Treatments may not be effective
- Check content, targeting, or timing
- Consider A/B testing alternatives
6.3 Journey Analytics
Journey Analytics shows journey-level performance.
Accessing Journey Analytics
- Click Analytics > Journey Analytics
- Select a journey from the dropdown
Journey-Level Metrics
| Metric | Description |
|---|---|
| Impressions | Total treatment views |
| Clicks | Total treatment interactions |
| CTR | Click-through rate |
| Conversions | Goal completions |
| Uplift | Journey-level impact |
Journey Analytics Dashboard
The dashboard includes:
| Section | Content |
|---|---|
| Journey Summary | Overall journey KPIs |
| Treatment Comparison | Side-by-side treatment metrics |
| Surface Analysis | Performance by surface |
| Time Trends | Daily/weekly performance |
Treatment Comparison
Compare treatments within a journey:
| Treatment | Impressions | Clicks | CTR | Conversions |
|---|---|---|---|---|
| Welcome Banner v1 | 10,000 | 500 | 5.0% | 50 |
| Welcome Banner v2 | 10,000 | 600 | 6.0% | 55 |
| Welcome Modal | 8,000 | 400 | 5.0% | 48 |
Use this to identify top performers and optimize.
Surface Analysis
See how different surfaces perform:
| Surface | Impressions | CTR |
|---|---|---|
| Home Screen | 15,000 | 5.5% |
| Product Page | 8,000 | 4.2% |
| Checkout | 5,000 | 6.8% |
Filtering Options
Filter journey analytics by:
- Date range
- Treatment type
- Surface
- Status
6.4 Key Metrics Explained
Engagement Metrics
Impressions
- Count of times treatments were shown to users
- Each view = one impression
- Same user can have multiple impressions
Clicks
- Count of user interactions with treatments
- Clicking CTA button
- Engaging with treatment content
Click-Through Rate (CTR)
CTR = Clicks / Impressions × 100%
Typical CTR benchmarks:
| Treatment Type | Good CTR |
|---|---|
| Push notification | 3-5% |
| In-app message | 5-10% |
| Banner | 2-4% |
| Modal | 8-15% |
Conversion Metrics
Conversions
- Users who completed the goal action
- E.g., made a purchase, signed up, completed profile
Conversion Rate
Conversion Rate = Conversions / Users × 100%
Impact Metrics
Uplift
- The incremental impact of treatments
- Compares treated users vs control group
- Positive uplift = treatments are working
Statistical Significance
- Whether uplift is reliable or due to chance
- Look for confidence indicators
- Generally need 95%+ confidence
6.5 Control Groups
What is a Control Group?
A control group is a subset of users who don't receive treatments, used to measure true impact.
How Control Groups Work
All Eligible Users
├── Treatment Group (e.g., 90%) → Receives treatments
└── Control Group (e.g., 10%) → No treatments
Why Control Groups Matter
Without a control group, you can't know if conversions would have happened anyway.
Example:
- 1,000 users converted after seeing treatment
- But how many would have converted without treatment?
- Control group answers this question
Control Group Size
Typical control group sizes:
- 5-10% of eligible users
- Must be large enough for statistical significance
- Balance: larger = better measurement, but fewer treated users
6.6 Reading Analytics Reports
Time Series Charts
What to look for:
- Overall trends (up, down, flat)
- Sudden changes (investigate causes)
- Day-of-week patterns
- Seasonal effects
Comparison Tables
Sorting:
- Click column headers to sort
- Identify top/bottom performers
Filtering:
- Use filters to focus analysis
- Compare similar treatments fairly
Export Options
Export data for further analysis:
- CSV download
- Date range selection
- Metric selection
6.7 Analytics Best Practices
Regular Review Cadence
| Frequency | Focus |
|---|---|
| Daily | Check for anomalies, monitor active journeys |
| Weekly | Review trends, identify optimization opportunities |
| Monthly | Full performance review, strategic planning |
| Quarterly | Long-term trends, goal reassessment |
What to Monitor Daily
- Sudden drops in impressions (delivery issues?)
- Unusual CTR changes (content problems?)
- Conversion rate shifts (external factors?)
What to Analyze Weekly
- Treatment comparison within journeys
- Surface performance patterns
- Uplift trends
Optimization Process
- Measure - Establish baseline metrics
- Analyze - Identify improvement opportunities
- Hypothesize - What change might improve results?
- Test - Create variant treatments
- Learn - Analyze results, apply learnings
- Repeat - Continuous improvement
Common Analysis Mistakes
| Mistake | Better Approach |
|---|---|
| Looking at metrics in isolation | Consider context and trends |
| Short time windows | Use sufficient data (7+ days) |
| Ignoring statistical significance | Wait for confident results |
| Comparing dissimilar treatments | Control for variables |
6.8 Attribution
What is Attribution?
Attribution determines which treatments get credit for conversions.
Attribution Window
The time period during which a conversion is attributed to a treatment.
Example: If attribution window is 7 days:
- User sees treatment on Day 1
- User converts on Day 5
- Conversion is attributed to the treatment
Multi-Touch Attribution
When users see multiple treatments:
- First touch: Credit to first treatment
- Last touch: Credit to last treatment
- Multi-touch: Credit distributed
Note: Attribution settings are configured by your admin. Contact them for details on your attribution model.
6.9 Analytics Troubleshooting
No Data Showing
Possible Causes:
- Date range doesn't include activity
- Journey/treatments are new
- Filters are too restrictive
- Data processing delay
Actions:
- Adjust date range
- Remove filters
- Wait for data processing (up to 24 hours)
Metrics Look Wrong
Check:
- Correct goal/journey selected
- Date range is appropriate
- No filters hiding data
- Compare to raw treatment counts
Uplift is Negative
Investigate:
- Treatment content issues
- Wrong audience targeting
- Timing problems
- External factors affecting control differently
CTR is Zero
Check:
- Treatments are actually delivering (impressions > 0)
- CTA is visible and clickable
- Tracking is configured correctly
6.10 Advanced Analytics Features
Cohort Analysis
Analyze performance by user cohorts:
- Sign-up date cohorts
- Behavioral cohorts
- Segment-based analysis
A/B Testing Analysis
Compare treatment variants:
- Statistical significance indicators
- Winner determination
- Confidence intervals
Custom Metrics
Some organizations configure custom metrics. Check with your admin for available custom metrics.
6.11 Analytics Permissions
Who Can Access Analytics
| Permission | Access Level |
|---|---|
| ANALYZE_OBJECTIVE_VIEW | View goal analytics |
| ANALYZE_PROGRAM_VIEW | View journey analytics |
| TREATMENT_VIEW | View treatment details |
Requesting Access
If you can't access analytics:
- Note the specific section you need
- Contact your admin
- Request appropriate permissions
Next Section
Continue to Section 7: Agent and AI Insights for AI-powered analytics documentation.