I am about to take the MB2-719 certification, this certification covers the Dynamics 365 for Marketing Application. I plan to create a series of blog posts that collectively should help anyone else preparing for this exam. In this post I’ll look at the basic concepts around lead scoring.

The section of the skills measured statement that mentions leads is shown below. Up-to 15% of the exam could be focused on leads, so understanding their purpose in the context of marketing is a significant portion of the exam. I have already covered the leads life cycle, in this post I will focus on the concept of sales readiness. (aka lead scoring.)

In a previous post I covered the meaning of leads in context of Dynamics 365 for Marketing and their associated life cycle. You can view that post here. In the lead life cycle we saw that once sales ready the lead would be passed from the marketing team to your sales team.

Lead Scoring Concept

Marking a lead as sales ready can sometimes be a manual process. This might happen, for example, when a telesales person speaks to a contact and establishes a clear requirement.

Often marketers will be working with hundreds or even thousands of leads simultaneously. Flagging these as sales ready manually would be a massive or impossible task! But as only a small fraction will warrant the attention of a salesperson and we also don’t want to waste the efforts of our sales team chasing leads which aren’t sales ready. Therefore an automated lead scoring system is required to help focus the efforts of our sales teams whilst not creating a restrictive process for our marking team.

There could be many ways we’d want to score leads and these may vary from campaign to campaign. Initially you may want to score leads based on demographic or firmographic data. Demographic being personal information, such as a contacts age or gender. Firmographic would be a similar segmentation concept aimed at commercial aspects of the organisation leads work for, including attributes such as industry sector or company size. Importantly you’d also want to score leads based on contact interactions. (Someone who has repeated opened your emails might be indicating a greater level of interest than someone who has never opened one!)

Note:
Scoring could go up or down. For example, your product or service might be targeted at a specific age range or gender. In these circumstances a lead from outside those targets may receive a negative score.

Commonly multiple lead scoring models might calculate a score on many parameters. Some scoring examples are listed below;

• Increase a score slightly when an email is opened
• Increase a score slightly when a website is visited
• Increase a score moderately in response to email clicks or landing-page submissions
• Increase a score significantly to and event registration or attendance
• Stop counting / ignore interactions some time ago
• Reduce lead’s score as it ages
• Increase or decrease a score based on associated contact (demographic) or company information (firmographic).

Note: Each lead could be measured against one or more lead scoring models simultaneously.

When considering lead scoring we need to keep in mind that with Dynamics 365 for Marketing a lead must always be associated with a contact. Meaning;

• Lead scoring only works for leads that are associated with a contact.
  • Lead scoring will fail if no contact is associated
  • Manually created leads must (therefore) be manually linked to a contact.
• Marketing segments only include contacts. Meaning you interactions are based on the emails sent to contacts.

Lead Scoring Models

Each lead scoring model is made up of a number of conditions and actions. (Meaning the condition and action tiles always appear as a pair.)

The conditions maybe “fixed” rules looking at demographic or firmographic data. Or they could be “behaviour” based conditions uses to measure interactions such as email clicks, event registrations etc.

Each condition will always have an action. The action will increase (or decrease) the points assigned to a lead when the condition is met.

Each condition can have properties. Here you define the field / interaction to be considered. Notice that you can have a frequency and date range.

The frequency options are “Each”, “At Least” and “None”. Often you might assign a score for each time an email is opened. But you could also use the “At Least” option. By adding a counter we can say the score is only awarded if the email was opened at least “n” times.

The date range logic is used to either apply the condition for the lifetime of the lead or define a custom range. The custom range would allow us to only apply the condition for the last “n” days, months or years. This may be useful to exclude any old irrelevant data.

Note:
You can have multiple condition tiles and multiple conditions within one condition tile. (When adding multiple conditions into one tile the “frequency” of all the conditions should be of the same type.)

Complex conditions are possible. See below that I have used the “.” syntax to hop into contact and its parent customer account. I can then filter based on fields from the account entity. (There is a restriction of a maximum of 5 hops.)

Note: Lead scoring works with your GDPR consent logic. Below you can see that on the summary tab we can ensure a minimum consent level is available on the contacts associated with our leads. Imagine what would happen without this …. leads might be marked as sales ready but without the required consent level our sales teams can’t contact them. Therefore linking the lead scoring model to the consent level would stop our sales people having to review leads they can’t contact.

The grades tab allows us to define the sales ready score for each lead scoring model. Additionally we can (optionally) add grades of leads.

The grades might be a really useful concept in your customer journeys. As segments can be created to find contacts who have leads at particular grades. You might then want to target specific messages to those people based on how close they are to your sales ready score.

Having created a lead scoring model you will need to save it, check it for errors and then make live. If you later wish to make changes to the scoring logic then you will need to stop the scoring and then make your amendments before making it live again.

Once your lead scoring model has been created. You will be able to view the associated grade and score of leads directly on the leads form. Notice below that I have only just made my new scoring model live. It is showing “Calculating Score” as the initial calculation can take time.

After the lead scoring has been completed you can see then my score and grade changes according to the conditions / actions in my lead scoring model.

When my score reaches the sales ready level, a flag on the leads is set to show that they are now sales ready. The sales ready flag is available on the lead entity, out of the box you’ll find it in the business process flow on leads.

Additionally, below you can see that we have an insights form available on the lead scoring model. This can be used to view the number of leads being scored overtime.

I hope I have covered all of the main points you’ll need to be aware of during your MB2-719 exam prep. As always I suggest you get plenty of hands-on practice. As part of your revision I suggest you create multiple lead scoring models and experiment with them to see how leads can then be made sales ready.