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Custom Account Scoring in Propensity

Updated

What this is

Custom Account Scoring allows you to customize how different engagement and intent signals contribute to the overall Propensity Score for accounts.

Using scoring rules, you can assign weighted point values to different account signals and define how those signals influence account scoring within your workspace.

Propensity Scores range from 0–100 and are used throughout the platform to help identify account engagement and buying intent.

Propensity Scores appear in areas such as:

  • Audiences
  • Leads Manager

Traditionally, Propensity Scores are calculated using a combination of:

  • First-party engagement signals
  • Third-party intent signals

Custom Account Scoring allows you to customize how those signals contribute to the overall Propensity Score.

Custom Account Scoring is managed at the workspace level.

When to use this

Use Custom Account Scoring when you want to:

  • Create custom account qualification models
  • Prioritize accounts based on engagement activity
  • Assign different weights to different scoring areas
  • Score accounts based on:
    • Intent activity
    • Account website visits
    • Contact website visits
  • Customize how account engagement contributes to account scoring

Accessing Custom Account Scoring

To access the feature:

  1. Go to Workspace Settings
  2. Click the More Actions ("...") button
  3. Select Custom Account Scoring

This opens the scoring model management area.

Creating a scoring model

To create a new scoring model:

  1. Click New Rule
  2. Enter a Model Name
  3. Select a Scoring Area
  4. Configure the Weight %
  5. Add one or more scoring rules
  6. Save the model

Scoring Areas

Custom Account Scoring currently supports the following scoring areas:

  • Intent Data
  • Account Website Visits
  • Contact Website Visits

Each scoring area supports its own rule configuration.

Weight Percentage

The Weight % determines how much a scoring area contributes to the overall Propensity Score.

For example:

  • A scoring area with a higher weight contributes more heavily to the final score
  • A scoring area with a lower weight contributes less heavily to the final score

Scoring models can also be marked as Active or not.

Points and rule weighting

Points help determine the relative influence of scoring rules within a scoring area.

When multiple rules exist within the same scoring area:

  • Rules with higher point values contribute more heavily
  • Rules with lower point values contribute less heavily

Weight % and points work together to determine how much each scoring area contributes to the overall Propensity Score.

For example:

  • A scoring rule with 20 points and a Weight % of 50% contributes 10 points toward the final score
  • If multiple rules exist within the same scoring area, the points are combined before the Weight % is applied

Example:

  • Rule A = 20 points
  • Rule B = 50 points
  • Weight % = 50%

Combined score:

(20 + 50) × 0.5 = 35

If multiple scoring areas are active, the weighted totals from each scoring area are combined into the final Propensity Score.

Points become more meaningful when multiple scoring rules exist within the same scoring area.

Important: There is no restriction on the total number of points that can be assigned across scoring rules. However, your team may choose to align their point values to the platform's 0–100 scoring scale. When combined with Weight % values that total 100%, this can make scoring calculations easier to understand and maintain.

Weight % best practice

While the combined Weight % values do not need to total 100%, this is generally recommended, especially if you configure multiple active scoring areas.

Because account scores are calculated on a 0–100 scale, using weights that total 100% makes scoring behavior easier to understand and predict.

For example:

  • Intent Data → 50%
  • Account Website Visits → 25%
  • Contact Website Visits → 25%

Your team may intentionally use a lower combined weight total if you prefer account scores to be distributed across a smaller range.

Intent Data scoring rules

When using the Intent Data scoring area, you can configure rules using:

  • Intent Signal
  • Recency Days
  • Minimum Frequency
  • Maximum Frequency
  • Points

Example use cases may include:

  • Assigning points when accounts show activity around specific intent topics
  • Increasing scores for more recent or frequent intent activity

When configuring Intent Signal rules, use the exact intent signal name whenever possible.

To help avoid matching issues, Propensity recommends copying the intent signal directly from the audience configuration or intent signal list.

Website Visit scoring rules

When using:

  • Account Website Visits
  • Contact Website Visits

You can configure rules using:

  • Page Keyword
  • Recency Days
  • Minimum Frequency
  • Maximum Frequency
  • Points

Page keywords can be entered as comma-separated values to track multiple important page types within a single rule.

For example:

  • pricing
  • demo
  • free-trial
  • overview

Page keywords can be used to identify important website pages or content categories.

Preview section

The Preview section displays a summary of how the scoring area contributes to the overall account score based on the configured rules and Weight %.

Score Explanation

When Custom Account Scoring models are configured, Propensity provides additional score explanation details within the platform.

You can hover over an account score to view information about how the score was calculated and which scoring models contributed to the final value.

This can help you better understand account prioritization and scoring outcomes.

Scoring Model Examples

Example 1: Account Website Visits
An account visits high-intent pages such as the pricing or demo page.

  • Model Name: High-Intent Page Visits
  • Scoring Area: Account Website Visits
  • Weight %: 50%
  • Scoring Rule:
    • Page Keyword: pricing, demo, free-trial
    • Recency Days: 90
    • Min Frequency: 1
    • Max Frequency: No max
    • Points: 80

Preview: Account Website Visits contributes 50.0% to the overall account score using 1 scoring rule.

Example 2: Intent Data
An account shows research activity around a specific intent topic.

  • Model Name: ABM Intent Signals
  • Scoring Area: Intent Data
  • Weight %: 30%
  • Scoring Rule:
    • Intent Signal: Account-Based Marketing (ABM)
    • Recency Days: 30
    • Min Frequency: 1
    • Max Frequency: 6
    • Points: 25

Preview: Intent Data contributes 30.0% to the overall account score using 1 scoring rule.

Example 3: Contact Website Visits
Contacts at an account visit key pages such as the demo or pricing page.

  • Model Name: Contact Demo and Pricing Visits
  • Scoring Area: Contact Website Visits
  • Weight %: 20%
  • Scoring Rule:
    • Page Keyword: demo, pricing
    • Recency Days: 60
    • Min Frequency: 1
    • Max Frequency: No max
    • Points: 40

Preview: Contact Website Visits contributes 20.0% to the overall account score using 1 scoring rule.

Important notes

  • Custom Account Scoring is configured at the workspace level
  • Creating or editing your signals will not automatically refresh all of the scores for your audiences. On the next refresh (manual or automatic) of each audience, the scores will be updated
  • Weight % values do not need to total 100%, but this is generally recommended
  • Point values are configurable and are not limited to a maximum combined score
  • Score explanations are available when Custom Account Scoring models are configured

Related Documentation

Using Intent Groups in Propensity

What is Custom Contact Scoring and how to use it

 

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