Data Discrepancies

Understand why analytics numbers differ between platforms and how to reconcile discrepancies.

Why Numbers Differ

No two analytics tools show exactly the same numbers. This is normal and expected due to:

1. Different methodologies
2. Different tracking mechanisms
3. Different definitions of metrics
4. Different filtering and processing

Zenovay vs Google Analytics

Common Differences

Metric	Zenovay	Google Analytics
Unique visitors	Fingerprint + cookies	Client ID cookie
Sessions	30-min inactivity	30-min + midnight
Bounce rate	Single page + <5s	Single pageview
Page views	All loads	Sampled (free)

Why Zenovay Shows Fewer Visitors

1. Bot filtering:

• Zenovay aggressively filters bots
• GA may count some bot traffic
• Our bot detection catches 15-20% more bots

2. Privacy tools:

• Different script blocking rates
• Zenovay's lightweight script loads more often
• But some blockers target all analytics

3. Single-page apps:

• Virtual pageviews may be configured differently
• Check SPA tracking setup on both

Why Zenovay Shows More Visitors

1. Ad blockers:

• Zenovay's first-party tracking avoids many blockers
• GA blocked by default in some browsers

2. Cookie consent:

• GA requires cookies in strict mode
• Zenovay can track without cookies

3. Sampling:

• GA Free samples data at high volumes
• Zenovay counts every visit

Reconciling Differences

Expect 10-30% variance as normal. To minimize:

1. Match date ranges exactly

   • Include timezone considerations
   • Use same start/end dates

2. Compare same metrics

   • "Users" vs "Unique Visitors"
   • "Sessions" definitions differ

3. Check for filters

   • Both excluding internal traffic?
   • Same geographic filters?

Session Count Differences

What's a Session?

Zenovay:

• Starts: First pageview
• Ends: 30 minutes inactive OR browser close
• No midnight split

Google Analytics:

• Starts: First interaction
• Ends: 30 minutes inactive OR midnight OR campaign change
• Splits at midnight

Why Sessions Differ

Example scenario:

• User visits at 11:45 PM
• Stays until 12:15 AM
• Single continuous activity

Zenovay: 1 session GA: 2 sessions (split at midnight)

Aligning Sessions

If comparing:

1. Compare full days, not partial
2. Account for midnight splits
3. Compare 7-day averages, not single days

Bounce Rate Differences

Definitions

Zenovay:

• Single page visit
• Less than 5 seconds
• No clicks or scrolls

Google Analytics:

• Single pageview session
• No time requirement
• No interaction requirement

Why Zenovay Often Shows Lower Bounce

Zenovay's definition is stricter:

• Reading content = not a bounce
• Scrolling = not a bounce
• Clicking anywhere = not a bounce

Example:

• User lands, reads for 2 minutes, leaves
• Zenovay: Not a bounce (engaged)
• GA: Bounce (single pageview)

Pageview Differences

Counting Methods

Zenovay:

• Every page load counted
• Client-side + server-side deduplication
• Real-time processing

Google Analytics (Free):

• Sampled at high volume
• Session-based processing
• May have delayed counts

SPA Considerations

For single-page apps:

// Ensure both track virtual pageviews
// Zenovay
zenovay('page');

// GA
gtag('config', 'GA_ID', {'page_path': '/new-page'});

Geographic Data Differences

IP Geolocation

Different providers yield different results:

• MaxMind vs IP2Location vs custom
• Database update frequency
• VPN/proxy detection

Common issues:

• Country usually accurate
• City can vary 10-20%
• Mobile IPs often wrong location

Compare at Country Level

For valid comparison:

• Use country-level data
• Expect city data to vary
• Don't compare exact numbers

Real-Time vs Processed Data

Data Processing

Zenovay:

• Real-time display
• Immediate availability
• Live counts

Google Analytics:

• Processing delay (4-24 hours)
• Real-time view is separate
• Final numbers may change

When to Compare

Compare after both have finalized:

• Wait 24-48 hours after period ends
• Don't compare real-time to processed
• GA numbers may adjust over time

Conversion/Goal Differences

Goal Matching

Goals may differ due to:

• URL matching rules
• Event definitions
• Attribution windows

Check:

Zenovay: Exact match "/thank-you"
GA:      Contains "thank-you"

Attribution Models

Conversion attribution:

Model	Zenovay	GA
Default	Last click	Data-driven
Window	30 days	90 days

Traffic Source Differences

UTM Handling

Both use UTM parameters but may:

• Parse differently
• Store case differently
• Handle missing data differently

Standardize UTMs:

Use: utm_source=google
Not: utm_source=Google, GOOGLE, google.com

Referrer Detection

Differences in:

• Direct traffic definition
• Referrer header availability
• SSL/non-SSL referral

How to Investigate

Step-by-Step Comparison

1. Export both datasets

   • Same date range
   • Same timezone
   • Raw data if possible

2. Compare totals first

   • Calculate percentage difference
   • 10-30% is normal

3. Drill into specifics

   • Which days differ most?
   • Which pages differ?
   • Which sources differ?

4. Check configurations

   • Both excluding same traffic?
   • Both tracking same pages?
   • Both using same events?

Using Debug Mode

Enable debug on both:

Zenovay:

<script data-debug="true" ...></script>

Check browser console:

• Both firing on same actions?
• Both receiving same data?
• Any errors on either?

Expected Variance

Normal Ranges

Metric	Expected Variance
Pageviews	5-15%
Unique visitors	10-30%
Sessions	15-25%
Bounce rate	5-20% difference
Conversions	10-20%

When to Worry

Investigate if:

• Variance > 50%
• Sudden change in variance
• Trends go opposite directions
• One shows 0 data

Best Practices

Pick a Source of Truth

1. Choose one platform as primary
2. Use for business decisions
3. Keep other for validation

Document Differences

Track known differences:

• Bot filtering rates
• Consent rate differences
• Technical setup differences

Focus on Trends

More reliable than absolute numbers:

• Week over week change
• Month over month growth
• Seasonal patterns

Both should show similar trends even if absolute numbers differ.

Contacting Support

If variance seems wrong, provide:

1. Both platform screenshots
2. Date range compared
3. Specific metrics differing
4. Recent changes made

Next Steps

• Understanding Metrics
• Unique Visitors Explained
• Missing Data Issues