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Inorganic Activity Filters

Inorganic Activity Filters are specialized rules that help LeadVibe identify and flag potentially non-human or automated activity that could artificially inflate lead scores. These filters are crucial for maintaining the accuracy and reliability of your lead scoring system.

Understanding Inorganic Activity​

Inorganic activity refers to engagement events that don't represent genuine human interest or intent. This can include:

Automated Behavior

  • Scripts or bots generating repetitive events
  • Automated email opens without meaningful engagement
  • Programmatic page views or form submissions

Spam or Invalid Activity

  • Malicious attempts to manipulate scoring
  • Erroneous data from system errors
  • Test or placeholder data entries

System-Generated Events

  • Duplicate events from tracking system errors
  • Auto-generated activity from integration issues
  • Background processes creating false engagement signals

When LeadVibe detects inorganic activity, it flags these events and prevents them from contributing to lead scores, ensuring that your scoring system reflects genuine prospect interest.

How Inorganic Filters Work​

Inorganic filters operate by monitoring event patterns for specific thresholds and time windows. The Inorganic Activity Filter first normalizes machine fan-out (such as email security scans), then suppresses sustained automated activity. Raw events are still stored, but only the representative event is counted toward velocity and scoring.

  1. Normalization: Machine fan-out is collapsed into a single representative event per microburst
  2. Pattern Detection: Each filter monitors a specific event type for excessive occurrences
  3. Threshold Comparison: When events exceed defined thresholds within time windows, they're flagged
  4. Grouping Logic: Related events can be grouped together for easier identification and management
  5. Scoring Exclusion: Normalized child events and flagged events don't contribute to lead scores but are still logged for analysis

Filter Components​

Each inorganic filter consists of four key parameters:

Event Type

  • The specific type of engagement event to monitor (e.g., page_view, email_open)
  • Must match exactly how events are registered in your system
  • Can be any valid event type tracked by LeadVibe

Count Threshold

  • The number of events that triggers the filter
  • Lower thresholds catch more activity, higher thresholds are more permissive
  • Set based on what constitutes "normal" vs. "excessive" activity for your business

Time Window (Milliseconds)

  • The period during which event counts are monitored
  • Shorter windows detect rapid bursts, longer windows identify sustained patterns
  • Common values: 1000ms (1 second), 60000ms (1 minute), 3600000ms (1 hour)

Group Events

  • Whether to group related events together for easier management
  • When enabled, subsequent matching events are associated with the initial group
  • Helps identify sustained bot activity or systematic issues

Creating Inorganic Filters​

Basic Filter Setup​

  1. Navigate to Configure in the main navigation
  2. Select Inorganic Activity Filters from the submenu
  3. Click Add Inorganic Activity Filter
  4. Configure the filter parameters
  5. Save the filter to activate it

Configure Filters page showing the Inorganic Activity Filters tab with a filter list displaying event type, threshold, time window in milliseconds, group events toggle, last modified by, and an Add Inorganic Activity Filter button

Filter Configuration Options​

Each inorganic filter requires the following parameters:

Event Type Selection

  • Choose from existing event types or enter a new one
  • New event types are automatically registered when used
  • Use descriptive names that match how events are categorized in your system

Threshold Count

  • Integer value representing maximum allowed events
  • Consider typical human behavior patterns when setting values
  • Test and adjust based on actual system performance

Time Window (Milliseconds)

  • Integer value representing monitoring period in milliseconds
  • Common conversions:
    • 1000 ms = 1 second
    • 60000 ms = 1 minute
    • 3600000 ms = 1 hour
    • 86400000 ms = 1 day

Group Events Checkbox

  • Enable to group subsequent matching events together
  • Disable for individual event tracking
  • Recommended for most use cases to simplify management

Example Implementations​

Page View Bot Detection​

Event Type: page_view
Threshold: 20 events
Time Window: 60000 ms (1 minute)
Group Events: Yes

Flags leads who view more than 20 pages in a minute, suggesting automated browsing.

Email Open Spam Detection​

Event Type: email_open
Threshold: 5 events
Time Window: 1000 ms (1 second)
Group Events: Yes

Identifies leads with suspiciously rapid email opens that are unlikely to be human.

Form Submission Protection​

Event Type: form_submit
Threshold: 3 events
Time Window: 5000 ms (5 seconds)
Group Events: Yes

Catches automated form submissions that occur too quickly for human completion.

Best Practices​

Setting Appropriate Thresholds​

Choose thresholds based on understanding normal human behavior:

Research Baselines

  • Analyze typical engagement patterns in your system
  • Identify natural upper limits for different event types
  • Consider industry-specific patterns and behaviors

Start Conservative

  • Begin with higher thresholds to avoid false positives
  • Monitor flagged activity to understand typical patterns
  • Gradually decrease thresholds as you gain confidence

Account for Legitimate High Activity

  • Some prospects may genuinely engage rapidly
  • Track multiple related events as normal behavior
  • Allow for campaign-specific engagement spikes

Monitoring and Adjustment​

Regular maintenance ensures filters remain effective:

Monthly Reviews

  • Check flagged events for false positives
  • Validate that flagged activity is truly inorganic
  • Adjust thresholds based on changing patterns

Sales Team Feedback

  • Gather input on lead quality and scoring accuracy
  • Identify scenarios where filters may be too restrictive
  • Document legitimate edge cases that trigger filters

Integration with Other Features​

Inorganic filters work with other LeadVibe features:

With Scoring Rules

  • Ensure flagged events don't contribute to scores
  • Maintain score accuracy despite inorganic activity
  • Preserve legitimate engagement scoring

With Reporting

  • Track inorganic activity trends over time
  • Monitor filter effectiveness and false positive rates
  • Report on system health and data quality

Troubleshooting​

Common Issues​

Filters Not Triggering

  • Verify event type names match exactly (case-sensitive)
  • Confirm thresholds and time windows are appropriately set
  • Check that events are being properly tracked in the system

Too Many False Positives

  • Increase thresholds to reduce sensitivity
  • Extend time windows to allow for natural activity bursts
  • Add specific conditions to distinguish legitimate from inorganic activity

Performance Impact

  • Avoid overly complex filter configurations
  • Limit the number of active filters if experiencing performance issues
  • Optimize time windows for your specific use cases

Debugging Process​

When filters aren't working as expected:

  1. Check Event Tracking

    • Verify that events are being properly recorded
    • Confirm event type spelling and formatting
    • Validate timestamp accuracy and timezone handling

  2. Review Configuration

    • Examine threshold and time window settings
    • Check activation status and grouping options
    • Verify that the filter is properly saved and active

  3. Analyze Historical Data

    • Review previous instances of flagged activity
    • Compare expected vs. actual pattern matching
    • Identify configuration gaps or edge cases

Advanced Configuration​

Multi-Layer Filtering​

Combine multiple filters for comprehensive protection:

Hierarchical Approach

  • Create different thresholds for different severity levels
  • Implement progressive filtering for various event types
  • Build cascading rules for complex behavioral patterns

Time-Based Adjustments​

Adapt filters to business cycles:

Campaign-Specific Settings

  • Adjust thresholds during high-engagement periods
  • Implement temporary filters for special promotions
  • Create seasonal adjustments for predictable patterns

Custom Integration​

Extend filtering capabilities:

External Data Sources

  • Integrate with third-party bot detection services
  • Import known spam or malicious activity lists
  • Sync with CRM data quality tools

Custom Alerting

  • Implement webhook notifications for flagged activity
  • Create specialized dashboards for monitoring inorganic activity
  • Build automated reporting for filter performance

By configuring effective inorganic activity filters, you ensure that your lead scoring system accurately reflects genuine prospect engagement, helping your sales team focus on the leads most likely to convert.