Lead Scoring Methodology

A framework for prioritizing contacts in your pipeline based on fit and engagement signals, so reps focus on the leads most likely to convert.

What Is Lead Scoring?

Lead scoring assigns a numerical value (0-100) to each contact based on two dimensions:

1. Fit Score — How well does this lead match your ideal customer profile? (Company size, industry, title, budget)

2. Engagement Score — How actively is this lead interacting with your content and sales team? (Emails opened, meetings attended, demos requested)

Combined: Total Score = Fit Score + Engagement Score (each 0-50, total 0-100)

Fit Scoring Criteria

Assign points based on how closely the contact matches your best customers:

Maximum Fit Score: 50 (if top score on all 4 criteria + 5 bonus points for existing customer account)

Implementing in the Spreadsheet

Add a Fit_Score column to the Contacts tab:

=SUM(
  IF(OR(Title contains "VP", Title contains "Director", Title contains "C"), 15, IF(Title contains "Manager", 8, 3)),
  IF(Deal_Value > 50000, 15, IF(Deal_Value > 20000, 8, 3)),
  ... additional criteria
)

Or use a lookup approach with a scoring reference table.

Engagement Scoring Criteria

Points are accumulated based on interactions:

Maximum Engagement Score: 50 (capped)

Calculating in the Spreadsheet

The Activities tab drives engagement scoring:

=MIN(50,
  COUNTIFS(Activities!Contact_ID, A2, Activities!Type, "Demo") * 15 +
  COUNTIFS(Activities!Contact_ID, A2, Activities!Type, "Meeting") * 10 +
  COUNTIFS(Activities!Contact_ID, A2, Activities!Type, "Call") * 5 +
  COUNTIFS(Activities!Contact_ID, A2, Activities!Type, "Email", Activities!Outcome, "Positive") * 5 +
  IF(TODAY() - Last_Contact > 30, -20, 0)
)

Score Interpretation

Score-Based Routing

Use the score to determine next actions:

For Sales Reps

=IF(Score >= 80, "CALL TODAY",
  IF(Score >= 60, "Email within 48h",
    IF(Score >= 40, "Add to weekly cadence",
      "Leave in nurture")))

For Pipeline Stage Advancement

A lead shouldn't advance from Qualification to Discovery unless their score is at least 40. This prevents reps from pushing unqualified leads forward prematurely.

Recency Weighting

Not all engagement is equal. Recent activity matters more than activity from 3 months ago.

Time Decay Formula

Decayed Points = Original Points × 0.9^(weeks_since_activity)

After 4 weeks, a 10-point activity is worth: 10 × 0.9^4 = 6.6 points

After 8 weeks: 10 × 0.9^8 = 4.3 points

After 12 weeks: 10 × 0.9^12 = 2.8 points

Spreadsheet Implementation

=SUMPRODUCT(
  Activity_Points * POWER(0.9, (TODAY() - Activity_Dates) / 7)
)

Negative Scoring

Some signals should reduce a lead's score:

Calibration and Maintenance

Monthly Review

1. Look at all leads that scored 80+ in the past month

2. How many actually converted?

3. If conversion rate is < 30%, your thresholds are too generous

4. If conversion rate is > 70%, you're being too conservative (missing warm leads)

Target: 40-60% Conversion Rate for "Hot" Leads

This means your scoring accurately identifies high-probability prospects without being so restrictive that you miss opportunities.

Quarterly Recalibration

Analyze which scoring criteria actually predict conversion:

1. Export all closed-won deals from the last quarter

2. Look at their scores at the time they entered Negotiation stage

3. Which criteria were most predictive?

4. Increase weight for predictive criteria, decrease for non-predictive ones

Quick Reference: The Contacts Tab

The Engagement_Score column in the Contacts CSV uses a simplified version of this methodology. To implement the full model:

1. Add a Fit_Score column (calculated from company/title/budget)

2. Rename existing score to Engagement_Score (calculated from activities)

3. Add a Total_Score column: =Fit_Score + Engagement_Score

4. Add a Lead_Grade column: =IF(Total>=80,"A",IF(Total>=60,"B",IF(Total>=40,"C","D")))

5. Sort your contact list by Total_Score descending — that's your priority list