SalesOS Rank

Overview

SalesOS Rank is the proprietary AI-powered scoring algorithm at the heart of SalesOS intelligence. It continuously evaluates every lead, contact, and account in your CRM, assigning a dynamic score from 0 to 100 that represents the record's engagement level, buying readiness, and relationship strength.

Unlike traditional lead scoring that relies on static rules and manual thresholds, SalesOS Rank combines five weighted signal categories with machine learning to produce scores that adapt to your organization's unique patterns. Records with higher SalesOS Rank scores consistently convert at higher rates, close faster, and generate larger deal values.

What SalesOS Rank Measures

SalesOS Rank evaluates five core dimensions of relationship and engagement quality. Each dimension contributes a weighted portion to the final score.

Score Components

Network Strength (30%)

Network Strength assesses how well-connected you are within the prospect's organization:

• Contact breadth — Number of contacts you have at the account across different departments
• Seniority coverage — Whether you have relationships at executive, management, and operational levels
• Champion identification — Presence of an internal advocate actively supporting your solution
• Multi-threading — Engagement with multiple stakeholders in the buying committee
• Org chart coverage — Percentage of the decision-making unit that you have relationships with

Higher Network Strength scores correlate with larger deal sizes and faster close times because multi-threaded relationships survive personnel changes and internal politics.

Activity (25%)

Activity measures the volume, frequency, and quality of interactions:

• Recency — How recently the last meaningful interaction occurred (exponential decay)
• Frequency — Cadence of touchpoints over the past 30, 60, and 90 days
• Bi-directionality — Whether engagement flows both ways (not just outbound)
• Channel diversity — Engagement across email, phone, meetings, and social
• Response time — How quickly the prospect responds to outreach
• Meeting attendance — Whether scheduled meetings are kept or cancelled

A lead who responded to your email yesterday and attended a demo last week scores higher than one who has not replied in three months.

Relevance (20%)

Relevance evaluates how closely the prospect matches your ideal customer profile (ICP):

• Firmographic fit — Company size, industry, revenue, and geography alignment
• Technographic fit — Technology stack compatibility and integration potential
• Use case alignment — Whether the prospect's stated needs match your solution capabilities
• Budget indicators — Signals suggesting appropriate budget authority and allocation
• Timing signals — Contract renewal dates, fiscal year timing, and growth indicators

Relevance is the most stable component — it changes only when new firmographic data is enriched or your ICP definition is updated.

Intent (15%)

Intent captures behavioral signals that indicate active buying interest:

• Website visits — Pages viewed, frequency, and depth of engagement on your site
• Content consumption — Downloads of case studies, pricing pages, ROI calculators
• Third-party intent — Signals from intent data providers showing research activity in your category
• Competitive research — Indicators that the prospect is evaluating alternatives
• Event engagement — Webinar registrations, conference interactions, demo requests
• Search behavior — Keywords and topics the account is actively researching

Intent is the most volatile component, spiking when a prospect enters an active buying cycle and decaying when research activity subsides.

Relationship Depth (10%)

Relationship Depth assesses the quality and history of the human connection:

• Relationship duration — How long you have been engaged with the contact
• Trust signals — Referrals made, introductions facilitated, personal rapport indicators
• Past business — Previous purchases, renewals, or expansions
• Advocacy — Public endorsements, references given, case study participation
• Sentiment — Tone and positivity in communications (AI-analyzed)

This component rewards long-term relationship investment and distinguishes genuine partnerships from transactional interactions.

How Scores Are Calculated

Real-Time vs. Batch Processing

SalesOS Rank uses a hybrid calculation approach:

Scoring Pipeline

1. Signal ingestion — Raw events are collected from all connected sources
2. Signal normalization — Events are standardized and weighted by significance
3. Component scoring — Each of the 5 components is scored independently (0-100)
4. Weight application — Component scores are multiplied by their configured weights
5. Final aggregation — Weighted scores are summed to produce the composite SalesOS Rank
6. Tier assignment — The numeric score is mapped to a qualitative tier
7. Trend calculation — The score is compared to historical values for trend direction

Machine Learning Layer

Beyond the weighted formula, a machine learning model trained on your organization's historical win/loss data adjusts scores based on patterns specific to your business:

• Deals that closed had certain activity patterns — the model recognizes these
• Deals that stalled shared common characteristics — the model penalizes these
• The model retrains weekly on new closed-deal data, continuously improving accuracy

Score Range and Tiers

Numeric Range

SalesOS Rank scores range from 0 to 100:

Tier Thresholds

Tier boundaries can be customized by administrators. For example, organizations with longer sales cycles may set the "Hot" threshold lower to account for slower progression patterns.

Score Distribution

A healthy pipeline typically shows:

• 40-50% Cold records (leads in nurture or early stage)
• 25-30% Warm records (actively engaged but not yet buying)
• 15-20% Hot records (in active evaluation)
• 5-10% On Fire records (ready to close)

If your distribution skews heavily toward Cold, it may indicate data decay or insufficient engagement. If skewed toward Hot, your scoring thresholds may need adjustment.

Accessing SalesOS Rank Scores

On Individual Records

Every lead, contact, and account record displays its SalesOS Rank score prominently:

• Score badge — Colored tier badge with numeric score in the record header
• Score breakdown — Expandable panel showing each component's contribution
• Score history — Sparkline chart showing score trend over the past 90 days
• Factor details — Specific signals driving the current score (see next section)

In List Views

Add the SalesOS Rank column to any list view to see scores at a glance:

• Color-coded by tier for quick visual scanning
• Sortable (highest first for prioritization)
• Filterable by tier or numeric range
• Trend arrow showing score direction (rising, stable, declining)

As a Filter

Use SalesOS Rank as a filter criterion anywhere filters are available:

• List views — Show only Hot and On Fire leads
• Reports — Segment by score tier in analytics
• Automations — Trigger workflows when a score crosses a threshold
• Sequences — Enroll only high-scoring leads in outreach cadences
• Assignment rules — Route high-score leads to senior reps

Score Factors Breakdown

Per-Record Explanation

Every scored record includes a human-readable explanation of why it received its score. This transparency helps reps understand and trust the algorithm.

Example factor breakdown for a "Hot" contact (score: 72):

Factor Categories

Factors are grouped into positive (boosting) and negative (suppressing) influences:

• Positive factors — Signals that increase the score
• Negative factors — Signals that decrease or suppress the score
• Neutral factors — Contextual information that neither boosts nor reduces

Using SalesOS Rank for Prioritization

Daily Workflow

Sales reps should organize their day around SalesOS Rank:

1. Morning review — Check "On Fire" records for immediate action
2. Follow-up queue — Address "Hot" records with pending tasks
3. Nurture cadence — Engage "Warm" records to progress them
4. Score changes — Review records that jumped tiers overnight (potential triggers)

Pipeline Prioritization

When choosing which deals to advance:

• Prioritize deals with rising SalesOS Rank (momentum)
• Investigate deals with declining scores (stalling indicators)
• Focus coaching on reps whose deals consistently plateau in "Warm"
• Escalate "On Fire" accounts to senior leadership for executive engagement

Territory and Capacity Planning

Use SalesOS Rank distribution to balance workloads:

• Reps with more "Hot" and "On Fire" accounts may need support
• Reps with mostly "Cold" records may need pipeline generation help
• Territory reassignment should consider score distribution, not just record count

SalesOS Rank in Routing

Predictive Lead Routing

When new leads enter the system, SalesOS Rank informs routing decisions:

• High-score leads (50+) are routed to top-performing reps or specialists
• Medium-score leads (26-49) follow standard round-robin distribution
• Low-score leads (0-25) enter automated nurture sequences before human engagement

Dynamic Re-Routing

As scores change over time, leads can be automatically re-routed:

• A "Warm" lead that spikes to "On Fire" can trigger immediate reassignment to a closer
• A "Hot" lead that decays to "Cold" after 60 days of silence can be returned to marketing for re-nurture

Routing Configuration

Configure SalesOS Rank-based routing in Settings > Lead Routing > Score-Based Rules:

Score Trends

Trend Indicators

Every record shows its score trajectory:

• Rising (up arrow) — Score increased 5+ points in the past 14 days
• Stable (neutral) — Score changed less than 5 points
• Declining (down arrow) — Score decreased 5+ points in the past 14 days

Trend Analysis

The score trend is often more actionable than the absolute score:

• A "Warm" lead with a rising trend is likely approaching readiness — prepare outreach
• A "Hot" lead with a declining trend may be losing interest — intervene immediately
• A "Cold" lead with a sudden spike may have just entered a buying cycle — act fast

Historical Score Chart

The record detail page shows a 90-day score chart with:

• Daily score values plotted as a line
• Tier boundaries shown as horizontal bands
• Key events annotated (emails, meetings, page visits) correlated with score changes

Team Benchmarks

Rep Performance Metrics

Managers can view SalesOS Rank benchmarks across their team:

Organization Benchmarks

Org-wide benchmarks help calibrate expectations:

• Average score at time of deal creation
• Average score at time of closed-won
• Score threshold that predicts 80% win probability
• Time-to-close correlation with SalesOS Rank tier

Configuring Weights (Admin)

Adjusting Component Weights

Administrators can adjust the weight each component contributes to the final score:

1. Go to Settings > SalesOS Rank > Score Configuration
2. Adjust the percentage weight for each component
3. Weights must total 100%
4. Preview the impact on a sample of records
5. Apply changes (full recalculation runs within 6 hours)

When to Adjust Weights

Custom Signal Configuration

Beyond weight adjustment, admins can configure which specific signals feed into each component:

• Add or remove activity types from the Activity component
• Define ICP criteria for the Relevance component
• Connect new intent data sources to the Intent component
• Specify which relationship indicators matter for your business

Testing Changes

Use the Simulation Mode to preview how weight changes would affect scores across your entire database before committing. The simulation shows:

• Number of records that would change tier
• Average score shift (positive or negative)
• Top records most affected by the change
• Impact on routing rules and automation triggers

Best Practices

• Trust the score but verify with context — SalesOS Rank is a powerful prioritization tool, but it does not replace human judgment. A low score might simply mean incomplete data rather than a bad prospect.
• Act on trends, not just absolutes — A rising score indicates momentum. A declining score signals that action is needed before the relationship cools further.
• Keep your data fresh — SalesOS Rank is only as good as the data feeding it. Log activities promptly, keep contact records current, and enrich firmographic data regularly.
• Review score factors before outreach — Before contacting a high-scoring lead, review the factor breakdown to understand why they scored high. This context informs your messaging and approach.
• Use scores for coaching — Compare score distributions between top performers and underperformers. The patterns reveal which behaviors drive higher engagement.
• Do not game the algorithm — Logging fake activities or inflating engagement metrics to boost scores undermines the system's value for everyone. The ML layer detects and discounts anomalous patterns.
• Calibrate quarterly — Review your weight configuration quarterly. As your business evolves, the relative importance of each component may shift.
• Set threshold-based alerts — Configure notifications when key accounts drop below a threshold or when dormant leads suddenly spike. These moments require immediate attention.
• Integrate with pipeline reviews — Make SalesOS Rank a standard element of pipeline review meetings. Discuss score changes alongside deal progress to identify at-risk opportunities early.
• Combine with deal scoring — SalesOS Rank scores records; deal scoring evaluates opportunity health. Use both together for a complete picture of where to invest your time.