Lead Scoring for Plaintiff Firms

Machine Learning Lead Scoring for Plaintiff Firms: How It Works

This release introduces Machine Learning Lead Scoring to Case Compass, focused on plaintiff, personal injury, and mass tort practices, including Roundup opportunities. Below is a feature level overview that explains how it works in practice.

What Machine Learning Lead Scoring Does

Machine Learning Lead Scoring analyzes new and existing intakes in your Case Compass environment and assigns each lead a score and category, based on factors that matter to plaintiff firms, such as:

• Case type: motor vehicle, premises, med mal, product liability, mass tort, and more

• Liability indicators: fault, comparative negligence, documentation

• Damages: injury severity, treatment, wage loss, long term impact

• Coverage and collectability: policy hints, available coverage, defendant profile

• Venue and deadlines: jurisdiction, statute related concerns

The result is a ranked list of leads that helps staff focus on high value opportunities first.

How It Works Inside Case Compass

1. Data collection at intake

Machine Learning Lead Scoring uses the information your team already captures in Case Compass:

• Web forms and chat intake

• Phone intake entered by staff

• Structured fields such as incident details, injury information, employment, and exposure history

No separate data entry is required. As soon as the intake is saved, the lead becomes eligible for scoring.

2. Secure machine learning evaluation

Behind the scenes, the machine learning service securely evaluates each lead and generates:

• A numeric score that reflects the overall strength and potential value of the case

• A case category, for example:

  • High priority PI

  • Standard PI

  • Possible mass tort

  • Low probability or decline candidate

The scoring logic is tuned for plaintiff work and personal injury patterns, not generic sales leads.

All analysis happens through encrypted, secure channels. Your intake data is never shared with third parties, never used to train external models, and remains fully within your control.

3. Special handling for Roundup and other mass torts

For mass torts, including Roundup, the system looks for specific combinations of:

• Work history and occupation

• Product or chemical use patterns

• Medical conditions that align with known tort criteria

When these signals are present, the lead is tagged as a possible mass tort candidate. Case Compass can then:

• Add a Roundup or mass tort flag directly on the lead

• Prompt intake staff with additional qualifying questions

• Route the lead to a designated mass tort team or attorney queue

This helps your firm avoid missing high value Roundup type opportunities that begin as routine sounding inquiries.

4. Prioritization in your workflows

Once scored, leads can be used throughout Case Compass:

• Work queues and call lists: sort by lead score so staff call the best cases first

• Attorney review queues: filter to high priority or mass tort flagged leads

• Reporting and analytics: compare marketing channels based on average lead score, not only volume

The scoring is visible inside the same Case Compass screens your team already uses, so there is minimal disruption to existing workflows.

Configuration and Controls

You retain control over how Machine Learning Lead Scoring is used in your firm:

• Case types: limit scoring to specific case types at first, such as motor vehicle or Roundup related matters

• Visibility: choose who can see scores and flags, for example intake only, or intake and attorneys

• Workflow rules: decide which scores trigger alerts, escalations, or specific routing rules

Over time, you can expand or refine these settings as your team gains confidence with the scoring output.

Security and Data Handling

Your data security is our top priority:

• All scoring requests are transmitted through secure, encrypted channels using industry standard TLS encryption

• Only intake data from your Case Compass environment is used for scoring - no external data sources are accessed

• Your data is never used to train external models or shared with third parties

• Scores and flags are stored securely inside Case Compass and respect your existing user permissions and role based access controls

• You bring your own API key (BYOK) - you maintain direct control over the machine learning service and can revoke access at any time

• Full audit trails - all scoring activities are logged for compliance and review

No external parties can see your firm specific lead data or results. Your client information stays private and secure.

How To Start Using Machine Learning Lead Scoring

To enable Machine Learning Lead Scoring in your Case Compass account:

1. Contact your Case Compass representative or support channel to have the feature enabled.

2. Configure your secure API key for the machine learning service (we will walk you through this).

3. Select which practice areas and mass torts you want to include initially, such as personal injury and Roundup.

4. Configure basic queue sorting and visibility options.

5. Monitor results over the first few weeks, then adjust thresholds, routing, or additional case types as needed.

Once configured, Machine Learning Lead Scoring runs automatically in the background, giving your intake and attorney teams a clearer picture of which leads deserve attention first.