The next step to launch a scoring model is to assign point levels and values to each category. You can assign point levels for these score sections: Demographic score, Behavioral score, and BANT Score.

Demographic scoring

Use Demographic score for contact information such as job title, location, or annual revenue.

Example:

A contact's job title is scoring.

Select the Job title database.

Next, add Point level, Point value, and Criteria:

1. Point level: Job title
2. Point value: Assign 10 points
3. Criteria: Equals 'Senior' or 'Director'

If the value in contacts' Job title database field meets one of the criteria, then the contact is assigned the specified points. In this case, each contact receives 10 points if their job title includes the keywords 'Senior' or 'Director'.

When the scoring model is saved, it only scores updated and new contacts in the database. To retroactively calculate all the contacts in your database based on the current scoring model, click the Recalculate scores link at the top of the Scoring page.

Behavioral activity scoring events

The behavior score section includes activity scoring, recency scoring, and frequency scoring:

• Activity refers to specific behaviors.
• Recency refers to the last time the contact performed the behavior.
• Frequency refers to how often the contact performed the behavior over time.

Recency scoring

Measure the interest level that a contact has with your brand to better understand your lead.

• The more recent a contact engages with your brand, the more points you can choose to assign in your scoring model.
• Although recency scores are set up separately from behavioral activity scores, you can use a mix of recency and activity scores in any order. Scoring supports unlimited time frames.  

To create scoring for a web form, make sure the web form is published and is not an opt-out web form.

Recency scoring setup example

As a marketer, you want to reduce a contact's score over time, based on some of their behaviors to improve the targeting of your email campaigns.

In the example below, you assigned different point levels to contacts who visited a website in the last 30, 31-60 days, and more than 61 days. The expected results are:

• Contacts who visited the website in the last 30 days are assigned 50 points.
• Contacts who visited the website after 31 days were assigned fewer points (15 points or 5 points). Their interest in the cruise is not as strong as those who recently visited the page.

Database behavior for recency scores

Recency scores recalculates and updates scoring records daily. The behavior is the sum of activity score, recency score, and frequency score.

Example:

A contact submits a web form (scored), which redirects them to a tracked URL.

The contact is scored twice – one time for submitting the web form and again for visiting the tracked web page.

Set up your scoring rule as 'Submitted a form' OR 'Visited a Web page' to ensure your model calculates an accurate score.

About frequency scoring

Frequency scoring measures the number of times a contact performs an event over a specified time. It helps answer the questions "How often did my contacts engage with my brand?" and "Are my contacts highly engaged?"

Example:

As a marketer, you want to discover how often contacts open your emails.

In your scoring model, you create the following frequency rule:

Assign 2 points when a contact opens an Email at least 5 times in the last 30 days.

Frequency scoring calculations are based on rolling days. Because of this, scores change (dropped or added) based on the number of events a contact performs during this time. Another point to keep in mind is if a contact performs an event twice in one day, (e.g. opens two emails on the same day), this counts as two events.

Note: You can only add one behavior type and one time frame per Frequency Scoring rule.

Adding data values to a scoring model

Include numeric field values in the contact's overall score. This can be a scoring field from another score model or the number of purchases a contact made.

1. Click Enable scores from data fields.
2. Scroll down to view a new section called Include scores from data fields.
3. From the drop-down menu, choose from any of the numeric fields in the database.

   Note: The system does not show fields that can create circular references. 

4. Complete steps 1-3 to add more fields.

To delete a data value, scroll to the top and click Disable scores from data fields, and click OK to confirm your choice.

Scoring records that meet multiple criteria

When a contact matches multiple point levels in the same score section, the model honours only the highest point levels.

In some cases, you may want the model to work differently.

Here's an example: you set up a scoring model rule related to the behavior 'Newsletter performance'. There are two elements to this behavior: visiting a sign-up landing page and submitting a web form, but you want the web form to be the only factor in your scoring model.

In the current model, any contact who only visits a landing page gets +2 points, just like for submitting a web form. If the contact does not perform any action related to 'Newsletter performance' behavior, i.e. any value equal to '0', gets -2 points. However, it is not possible for the contact to submit a sign-up form without visiting the landing page. As a result, each contact that hasn't visited the landing gets -2 points, even though it's only one part of the behavior.

Changing the value from blank to '0' in landing page visits should have no effect on the score. However, the score increased by 2, which interferes with the accuracy of the score.

In this model, both point levels, +2 for 'landing page visited' and '-2 for XYZ equals zero', are under the same score section of 'Newsletter performance'. The scoring model will honor both point levels if you separate them into two different score sections, such as 'Landing page visit' and 'Web form submission'.