Scores

Ortto’s scores enable you to create a customized scoring system to measure your contact’s activity and characteristics against the metrics that are most important to you.

When creating a score, you choose the criteria and a relevant half life period over which the lead score is reduced. Similar to how a contact’s engagement score is calculated, the score is reduced by a half life period (for activities only, filter criteria do not depreciate). That is, activities that are in the older half of your half life period only contribute half the points, and activities in the more recent half contribute full points. Learn more about how the score is calculated.

Each criteria that you add to the score can contain a filter condition with multiple Where clauses, or an activity. The filter condition or activity will become the criteria, for example, User session has occurred where page paths contain 'pricing'. You’ll also assign positive or negative points to the criteria to determine its value. For example, you might consider an undesirable customer action to be Subscription cancelled has occurred and assign it -50 points.

Create a score

To create a score:

1. In your account Settings > Customer data > Scores, click New score.
2. Give the score a name, such as "Product score". This name will be populated as the field name for viewing a contact’s score in your customer data platform (CDP).
3. Choose a Score format:
   • Normalized — this creates a relative score to calculate a person’s score against the 95th percentile. Normalized scores are represented by emojis.
   • Whole number — this is an absolute score calculated as points per activity times the number of activity occurrences.
4. Select your Score half life period.
5. Add the Scoring criteria.
6. Toggle the score ON to begin scoring your contacts.

Once created, you can add scores to your CDP view using by clicking the cog icon, then searching for and selecting the scores.

You can filter by scores, such as to find contacts with high lead scores so your sales team can reach out to qualified leads in a timely manner. You could also use scores as entry criteria for playbooks and journeys.

You’ll also be able to see scores in an audience’s overview, and in a contact’s or organization’s view. (Scores that are OFF or have no calculation (no contacts have met the criteria) will not be visible in the audience’s, contact’s or organization’s view.)

Audience

The audience tab shows you, for the contacts who meet the normalized score criteria, the number and percentage of contacts who have a particular score value (1 to 5 icons).

Whole number scores cannot be represented in the audience tab, so you may wish to create a report to visualize the score values.

How are scores calculated?

Scores are calculated differently depending on the calculation type you chose during the score setup.

Scores can be normalized (an individual contact’s score is calculated against another contact’s 95th percentile score) or whole number (an individual contact’s score is the result of their actions according to the criteria you set, and not measured against other contacts).

A normalized score for any given person in your CDP is a 5-point score, where 5 emojis represent the highest score and 1 emoji represents the lowest score. The whole number score is represented by a number value. Both score types are calculated over the specified half life period.

Activities that are in the older half of your half life period only contribute half the points, and activities in the more recent half contribute full points. So, if a half life period is 30 days, a Clicked email 3 weeks ago might be worth 125 points, but a Clicked email 2 days ago is worth 250 points.

Filters, however, do not depreciate, so filter criteria will contribute the whole amount of points for the half life period. To use the same example as before, if a half life period is 30 days, a filter criteria Clicked email has occurred that occurs 3 weeks ago or 2 days ago will each be worth 250 points.

Activity criteria accrue points each time the activity occurs (it counts the number of times the activity is performed), but filter criteria only accrue points once, when met (because the filter is only assessing whether filter criteria = true, not how many times it is true). If filter criteria is no longer met (becomes false after being true), the points added for the filter criteria will be subtracted in the subsequent calculation cycle. See the normalized and whole number score calculations for an illustrated example.

Normalized score calculation

A normalized score is calculated based on the maximum person value, rather than the maximum available points value. The outliers are then removed (only the 95th percentile is kept), and then the score is calculated based on points/max value. This means that an individual contact’s score is calculated against the highest (95th percentile) of any existing contact (to result in a relative score).

The calculation for normalized scores is as follows:

total points amassed by the user (points per activity x number of activity occurrences, for each activity) / total possible points (95th percentile score)

The result of this calculation is a percentage, which corresponds to the 1 to 5 icon score, where:

• 0% (no score) gets 0 icons,
• 1—​19% gets 1 icon,
• 20—​39% gets 2 icons,
• 40—​59% gets 3 icons,
• 60—​79% gets 4 icons, and
• 80%+ gets 5 icons.

Example 1. A contact’s normalized score calculation

Say your scoring activities are configured like this:

And a contact has the field values and has performed the following activities within the recent half of your half life period:

• Industry is Retail
• Country is United States
• Clicked email has occurred where email name is New products: July
• Clicked email has occurred where email name is New products: July
• Trial expired has ocurred

The contact’s score is calculated as follows:

1. 1 field value at +50 points = 50
2. 1 field value at +30 points = 80
3. 2 clicks at +20 points each = 120
   (This Clicked email activity gets points added twice because it is an activity criteria. If Clicked email had been created as a filter criteria, it would only count once, when met.)
4. 1 activity at -50 points = 70 (this contact’s total score)
5. All contacts who meet the score criteria have their scores calculated, and we find the 95th percentile score. In this example, the 95th percentile score is 200.
6. We then calculate this contact against the highest contact score: 70 (total individual contact points) / 200 (95th percentile score) = 0.35
7. The contact’s score is 35% which gets 2 icons.

Whole number score calculation

A whole number score is calculated based on the maximum available points value, rather than the maximum person value. This means that an individual contact’s score is calculated against the scoring criteria you set and results in a whole number score.

The calculation for a whole number scores is as follows:

points per activity x number of activity occurrences

The result of this calculation is a whole number value.

Example 2. A contact’s whole number score calculation

Say your scoring activities are configured like this:

And a contact has the field values and has performed the following activities within the recent half of your half life period:

• Industry is Retail
• Country is United States
• Clicked email has occurred where email name is New products: July
• Clicked email has occurred where email name is New products: July
• Trial expired has ocurred

The contact’s score is calculated as follows:

1. 1 field value at +50 points = 50
2. 1 field value at +30 points = 80
3. 2 clicks at +20 points each = 120
   (This Clicked email activity gets points added twice because it is an activity criteria. If Clicked email had been created as a filter criteria, it would only count once, when met.)
4. 1 activity at -50 points = 70
5. The contact’s score is 70.