Deal Scoring & Progression

Deal scoring in SalesOS uses artificial intelligence to continuously evaluate the health of every open opportunity in your pipeline. Rather than relying on gut instinct or manual stage updates, the scoring engine analyzes dozens of behavioral and contextual signals to produce a single health score for each deal. This score tells you at a glance which deals need attention, which are progressing well, and where to focus your time for maximum impact.

Combined with progression tracking, deal scoring gives you a data-driven view of how quickly deals move through your pipeline, where they stall, and what actions correlate with successful outcomes.

---

How Deal Scoring Works

The SalesOS AI scoring engine evaluates each deal on a 0-100 scale by analyzing four core dimensions. The score updates automatically as new data flows in -- emails exchanged, meetings held, deal fields updated, and engagement patterns observed. No manual input is required from reps beyond their normal selling activities.

The score reflects the likelihood that a deal will close successfully within its expected timeframe. Higher scores indicate stronger deal health; lower scores signal risk that requires intervention.

Score Components

Each deal's health score is a weighted combination of four component scores:

Engagement Score

The engagement component evaluates how actively both parties are communicating. It considers:

• Email volume and response times -- Are emails being exchanged regularly? Is the buyer responding promptly?
• Meeting frequency -- Are discovery calls, demos, and review meetings happening on schedule?
• Multi-threading -- Are multiple stakeholders engaged, or is the deal single-threaded to one contact?
• Recency -- When was the last meaningful interaction? Deals with no activity in 7+ days see engagement scores decline.

Completeness Score

Completeness measures how well-documented the deal is. Well-documented deals close at higher rates because they indicate thorough qualification. The engine checks:

• Required fields -- Amount, close date, stage, and owner are populated.
• Contact associations -- At least one contact is linked; bonus for multiple contacts with defined roles (decision maker, champion, evaluator).
• Account association -- The deal is linked to a qualified account with firmographic data.
• Next steps -- A clear next action is documented with a due date.
• Notes and context -- Discovery notes, competitor information, or pain points are recorded.

Velocity Score

Velocity measures whether the deal is moving through the pipeline at a healthy pace. The engine compares each deal's progression to historical patterns for similar deals (same pipeline, similar deal size, same segment). It evaluates:

• Time in current stage -- Is the deal lingering longer than average in its current stage?
• Stage progression rate -- How quickly has the deal moved from stage to stage compared to won deals?
• Close date proximity -- Is the expected close date approaching with insufficient stage progress?
• Stage regression -- Has the deal moved backward to an earlier stage?

Signals Score

The signals component uses natural language processing and pattern recognition to detect buying indicators in communications and deal behavior:

• Positive signals -- Budget discussions, timeline urgency, executive involvement, contract language, vendor comparison requests, technical evaluation activity.
• Negative signals -- Cancellation of meetings, mentions of budget freezes, competitor preference, stakeholder departures, extended silence, pushback on pricing.

---

Accessing Deal Scores

Deal scores are visible in multiple places throughout SalesOS to ensure you always have context on deal health without navigating away from your current workflow.

Pipeline View

In the Kanban board view, each deal card displays a color-coded health indicator:

• A small circular badge in the top-right corner of the card shows the score tier (color) and numeric score.
• Cards can be sorted by health score to surface at-risk deals at the top of each column.
• Use the Sort by dropdown above the Kanban board and select Health Score (Low to High) to prioritize struggling deals.

In the list view, the Health Score column displays the numeric score with a color-coded background. Click the column header to sort ascending or descending.

Deal Detail Page

On any deal's detail page, the health score appears in the header section alongside the deal amount and stage. Below the header, a Deal Health card provides:

• The overall score with tier label and color.
• A breakdown of all four component scores with individual progress bars.
• A trend sparkline showing score changes over the past 30 days.
• A list of the top contributing factors (both positive and negative) that explain the current score.

Dashboard Widgets

The Deals at Risk dashboard widget displays a summary of all deals with scores below 50, sorted by value. This gives managers a quick view of pipeline risk without navigating to individual deals.

---

Score Tiers

SalesOS groups deal scores into four tiers for quick visual identification and action prioritization:

Tier Distribution

A healthy pipeline typically shows the following distribution:

• Critical: Less than 10% of deals by count.
• At Risk: 15-25% of deals.
• On Track: 40-50% of deals.
• Strong: 20-30% of deals.

If your pipeline skews heavily toward Critical and At Risk, it may indicate systemic issues with lead qualification, follow-up cadence, or competitive positioning. Use the distribution as a leading indicator of pipeline health before revenue impact becomes visible.

---

Progression Tracking

Beyond the point-in-time health score, SalesOS tracks how deals progress through your pipeline over time. Progression tracking answers questions like: How long do deals typically spend in each stage? Are certain stages bottlenecks? Is this specific deal moving faster or slower than expected?

Stage Velocity

Stage velocity measures the average number of days deals spend in each pipeline stage before advancing. SalesOS calculates velocity by analyzing your historical won deals and presents benchmarks for each stage.

Navigate to Pipeline > Analytics to view stage velocity metrics:

• Average days per stage -- A bar chart showing the mean time spent in each stage for won deals.
• Current deal velocity -- For any individual deal, you can see how its time in the current stage compares to the historical average. A deal that has been in Proposal for 12 days when the average is 7 days will be flagged as slow.
• Velocity by deal size -- Larger deals naturally take longer. SalesOS segments velocity benchmarks by deal size (small, mid-market, enterprise) so comparisons are fair.

Expected vs Actual Progression

For each deal, SalesOS projects an expected progression timeline based on:

• The deal's creation date and expected close date.
• Historical stage duration patterns for similar deals.
• The number of remaining stages before close.

On the deal detail page, a Progression Timeline visualization shows:

• Expected path (dashed line) -- Where the deal should be based on historical patterns.
• Actual path (solid line) -- Where the deal has actually progressed.
• Gap indicators -- Visual markers where the deal has fallen behind or pulled ahead of expectations.

When a deal's actual progression falls significantly behind expected progression, the velocity component of the health score decreases, and the deal may shift from On Track to At Risk.

Stalled Deal Detection

A deal is considered stalled when it meets any of the following criteria:

• No stage change in more than 2x the average time for the current stage.
• No activity (emails, calls, meetings, or notes) in the past 10 business days.
• Close date has passed without advancement or date update.

Stalled deals are automatically flagged in the pipeline view with a pause icon and appear in the Stalled Deals section of the forecasting page.

---

Score Trends Over Time

Deal scores are not static -- they fluctuate as circumstances change. SalesOS records the health score for every deal daily, creating a historical trend that reveals momentum.

Viewing Trends

On the deal detail page, the Score History chart shows:

• A line graph of the deal's health score over the past 90 days (or since creation, whichever is shorter).
• Annotations marking significant events: stage changes, meetings, score tier transitions.
• A moving average line to smooth out daily noise and reveal the true trajectory.

Trend Indicators

In list views and pipeline boards, a small arrow next to the score indicates recent trajectory:

• Up arrow -- Score has increased by 5+ points in the past 7 days.
• Down arrow -- Score has decreased by 5+ points in the past 7 days.
• No arrow -- Score is stable (within 5 points of its 7-day average).

Trend direction is often more actionable than the absolute score. A deal at 55 (On Track) with a downward trend may need attention sooner than a deal at 45 (At Risk) with an upward trend.

---

Recommended Actions by Score Tier

SalesOS does not just score deals -- it provides specific, actionable recommendations based on the score tier and the specific factors dragging the score down.

Critical Tier (0-25) Actions

• Escalate immediately -- Involve a manager or executive sponsor to rescue the deal.
• Re-engage the champion -- If the primary contact has gone silent, attempt re-engagement through a different channel (phone instead of email, LinkedIn message, or mutual connection introduction).
• Offer concessions -- Consider pricing flexibility, extended trials, or custom terms to reignite interest.
• Qualify out -- If recovery is unlikely, mark the deal as lost and reallocate effort to healthier opportunities.

At Risk Tier (26-50) Actions

• Schedule a meeting -- The most common recommendation for at-risk deals with declining engagement. Get face time (virtual or in-person) to re-establish momentum.
• Multi-thread -- If the deal is single-threaded, the system recommends identifying and engaging additional stakeholders.
• Update next steps -- Ensure a concrete, time-bound next action is documented and communicated to the buyer.
• Address objections -- Review recent communications for unresolved concerns and prepare targeted responses.

On Track Tier (51-75) Actions

• Maintain cadence -- Continue the current communication rhythm without over-contacting.
• Advance the stage -- If the deal meets the criteria for the next stage, update it promptly to keep velocity healthy.
• Strengthen multi-threading -- Add contacts and deepen relationships with buying committee members.
• Document progress -- Keep notes current so the AI has complete context for scoring.

Strong Tier (76-100) Actions

• Prepare for close -- Begin drafting contracts, confirming terms, and aligning on implementation timelines.
• Upsell opportunity -- Healthy deals with engaged buyers may be receptive to expanded scope or additional products.
• Reduce risk -- Even strong deals can slip. Confirm the close date, verify budget availability, and ensure no late-stage surprises.

---

Configuring Score Weights (Admin)

Administrators can customize how the four score components are weighted to reflect your organization's selling motion and priorities. For example, a high-velocity transactional sales team might weight engagement more heavily, while an enterprise team might prioritize completeness and signals.

Accessing Score Configuration

1. Navigate to Settings > Pipeline > Deal Scoring.
2. You will see sliders for each of the four component weights.
3. Adjust the sliders so the total equals 100%.
4. Click Save to apply changes.

Weight changes take effect on the next scoring cycle (scores refresh every 4 hours). Historical scores are not retroactively recalculated.

Additional Configuration Options

• Stale deal threshold -- Define how many days of inactivity constitute a stalled deal (default: 10 business days).
• Velocity baseline period -- Choose the lookback window for calculating stage velocity benchmarks (default: 6 months of closed-won deals).
• Score refresh frequency -- Standard is every 4 hours; enterprise plans can configure hourly updates.
• Excluded stages -- Optionally exclude certain stages (such as Closed Lost or Parking Lot) from scoring entirely.

---

Best Practices

• Trust the trend, not a single score. A deal dropping from 72 to 58 over two weeks is more concerning than a deal sitting steadily at 48. Focus on trajectory and intervene when scores are declining, regardless of the current tier.

• Act on Critical deals within 24 hours. Deals in the Critical tier have a low probability of recovery without immediate intervention. Make it a daily habit to review Critical deals and take action or qualify them out.

• Keep deal fields current. The completeness component rewards well-documented deals, and for good reason: deals with complete data close at 2-3x the rate of sparsely documented ones. Encourage reps to update close dates, next steps, and contact roles regularly.

• Use score distribution as a pipeline health metric. If more than 35% of your pipeline by value is in Critical or At Risk, your forecasted revenue is unreliable. Address the root causes (poor qualification, inconsistent follow-up, missing stakeholders) rather than hoping deals recover on their own.

• Review score factors, not just the number. The score breakdown on the deal detail page tells you exactly why a deal scored the way it did. Use the specific negative factors to guide your next action rather than applying generic recovery tactics.

• Customize weights for your sales motion. The default weights work well for most B2B SaaS sales cycles, but they are not universal. If your historical data shows that engagement frequency is the strongest predictor of deal outcomes in your business, increase its weight accordingly.

• Combine scoring with progression tracking. A deal can score well on engagement and completeness but still be at risk if velocity is lagging. Use the expected-vs-actual progression view to catch deals that are healthy in every dimension except pace.

• Do not game the score. Adding empty notes or scheduling placeholder meetings to inflate engagement metrics undermines the system's value. The AI is designed to detect meaningful interactions, and artificial activity will be weighted accordingly in future model updates.