Numeric Values Scoring – RevOS Documentation & Support

Scoring of numeric values works based on two parameters:

Metric thresholds - lower and upper bounds

Metric direction - wherever higher value is considered to be ‘better’ or lower value is considered to be ‘better’

Please note that low/red values include lower bound values and high/green values include higher bound. See examples below.

Examples

No Suppliers (higher is better)

Numner suppliers is a basic metric that count a number of unique suppliers inside one account. For this example we consider higher number of suppliers to trigger higher score (green) where low number of monthly active users to be lower score (red). Based configuration above:

A customer account with Number Suppliers = 10 or lower still be considered red (lower bound included)

A customer account with Number Suppliers = 11 will be considered yellow

A customer account with Number Suppliers = 49 will be considered yellow

A customer account with Number Suppliers = 50 or more will be considered green (upper bound included)

Number of issues last 30 days (lower is better)

Another good example is number of issues, e.g. issues s in the support and ticketing system of a customer account:

Here we want to score good/green when number of low and and score will decrease with increasing number of issues. In the example we will have:

A score of the customer account will be green if number of open tickets will be 1 or less

A score of the customer account will be yellow if number of open tickets will be 2

A score of the customer account will be yellow if number of open tickets will be 4

A score of the customer account will be red if number of open tickets will be 5 or more

Empty values scoring

In addition to thresholds and metric direction, you can now configure how empty / missing numeric values are scored.

Use Empty value score to choose what score should be assigned when a metric value is not available (e.g., NULL, empty, or not provided). Depending on the use case, you can treat empty values as:

No score (0 points) — exclude the metric from scoring when value is missing

Low (0 points) — consider missing value as bad

Medium (half points) — neutral/partial score for missing value

High (full points) — consider missing value as good

If the metric uses negative scoring (i.e., it assigns negative points), the Empty value score follows the same logic: selecting Low or Medium will apply a negative score, while High will result in 0 points (no penalty). For example, an empty value can be scored as -5 (Low) or -2.5 (Medium).

This allows you to adapt scoring to the metric meaning: sometimes missing data should not penalize an account, while in other cases missing data itself can be a negative signal.