Intent Prediction & ICP Scoring

Discover how Sona analyzes visitor behavior to predict buying intent and evaluate account fit, helping you prioritize outreach and maximize conversion rates.

Why Intent and Fit Matter

Identifying website visitors is only the first step. To maximize conversion rates and sales efficiency, you need to answer two critical questions:

1. Is this a good-fit prospect? (ICP Fit Scoring)
2. Are they ready to buy? (Intent Prediction)

Not all visitors are created equal. A high-fit account showing strong buying signals deserves immediate attention, while a low-fit visitor casually browsing your blog can wait. Sona automatically evaluates both dimensions, transforming raw visitor data into prioritized pipeline opportunities.

ICP (Ideal Customer Profile) Fit Scoring

What Is ICP Scoring?

ICP scoring evaluates how closely an identified account matches your ideal customer profile. Rather than treating all visitors equally, this scoring helps you focus resources on prospects most likely to become successful, long-term customers. Think of ICP scoring as a filter that separates dream accounts from poor fits, allowing your sales and marketing teams to concentrate efforts where they'll have the highest impact.

How Sona Calculates ICP Fit

You build your ICP by selecting company attributes that align with your target customers. Sona then automatically scores each identified account based on how well they match your criteria.

In the Scoring settings, you can configure multiple attributes:

• # Employees - Target company size ranges (e.g., 5-200 employees)
• Annual Revenue (in millions) - Revenue ranges that match your deal size
• Job Title - Specific roles you want to target (with include/exclude options and custom weights)
• ChatGPT Prompt - Custom scoring logic using AI prompts for advanced criteria
• Intent Signals - Specific behavioral indicators (e.g., "Requested Demo")
• Tech Category - Technology stack and tools the company uses

Weighted Scoring System

Each attribute you add contributes a percentage weight to the overall ICP score. You can see the weight distribution on the right side of the ICP setup:

• Attributes show their weight percentage (e.g., "# Employees (15%)")
• The sum of all attribute weights must equal 100% to complete the ICP setup
• You can adjust weights based on which factors matter most for your business

Configuring Attribute Criteria

For each attribute, you can:

1. Set specific values or ranges - Define what "good fit" means (e.g., 5-200 employees, $5-200M revenue)
2. Include or Exclude - Toggle whether to include or exclude accounts matching the criteria
3. Add multiple values - Select multiple job titles, tech categories, or other options
4. Assign custom weights - For attributes like Job Title, set specific weight values per criterion
5. Use AI prompts - Create custom scoring logic with ChatGPT prompts for complex criteria

Active Attributes Tracking

The platform shows you how many active attributes you've configured (e.g., "-1 Active Attributes"), helping you understand your ICP setup completeness at a glance.

Real-Time Score Updates

As Sona enriches account profiles with new firmographic and behavioral data, ICP scores recalculate automatically. This ensures your prioritization always reflects the most current and complete information available.

ICP Fit Score Ranges

Rather than a fixed 0-100 scale, your ICP score is calculated based on the weighted attributes you configure. The score represents how well an account matches your defined criteria.

Understanding Your ICP Score:

• High Fit - Account matches most or all of your weighted criteria
• Moderate Fit - Account matches some criteria but may be missing key attributes
• Low Fit - Account doesn't align with your defined ICP

The platform shows your "Sum of Attribute Weights" with a completion percentage (e.g., "83% Complete"), indicating how fully you've configured your ICP scoring model. To finalize your ICP setup, the sum of all attribute weights must equal 100%.

You can customize how you tier and prioritize accounts based on their scores, defining what thresholds trigger different actions in your sales and marketing workflows.

Using ICP Scores Strategically

Different fit tiers warrant different engagement strategies:

A-Tier Accounts (90-100% fit)

• Immediate Slack alerts to sales leadership
• White-glove outreach from senior account executives
• Personalized demo experiences and custom content
• Premium nurture sequences with high-touch engagement
• Executive involvement and relationship building

B-Tier Accounts (70-89% fit)

• Standard sales follow-up within 24-48 hours
• Targeted email sequences highlighting relevant use cases
• Qualification calls from SDRs before passing to AEs
• Educational content and product tours
• Regular check-ins and relationship nurturing

C-Tier Accounts (50-69% fit)

• Automated nurture campaigns and self-service resources
• Marketing-qualified lead (MQL) workflows
• Lower-priority follow-up from SDRs
• Periodic re-evaluation as company circumstances change
• Focus on education rather than immediate sales

D-Tier Accounts (Below 50% fit)

• Minimal manual engagement
• Generic content and self-service options only
• Possible disqualification or redirection to partners
• Resources allocated to higher-fit opportunities instead

This tiered approach ensures you're investing time and effort where it will yield the highest returns.

Intent Prediction and Buying Signals

What Is Intent Prediction?

Intent prediction analyzes visitor behavior to estimate where prospects are in their buying journey and how likely they are to purchase. High intent signals indicate sales-readiness and urgency, while low intent suggests early-stage research or casual browsing.

Intent scoring transforms website analytics into a sales prioritization system, helping you strike while the iron is hot.

Behavioral Signals Sona Tracks

Sona monitors engagement patterns to build intent scores:

Page Visit Patterns

Different pages signal different levels of buying intent:

• High intent pages:
  • Pricing page - Indicates budget exploration and purchase consideration
  • Demo/trial request - Explicit interest in evaluating the product
  • Case studies - Seeking validation and social proof
  • Comparison pages - Active vendor evaluation
  • Implementation/onboarding docs - Technical evaluation and planning
• Medium intent pages:
  • Product features - Understanding specific capabilities
  • Integrations - Evaluating technical fit
  • Documentation - Deeper product research
  • About/team pages - Company vetting
  • Blog posts - Topic-specific education
• Low intent pages:
  • Homepage - Initial awareness and broad exploration
  • Resource center - General education
  • Careers page - May not be a buyer
  • Legal pages - Due diligence or research