Combined scoring and grading automation
Posted: Mon Dec 23, 2024 7:44 am
This data could exist in a range of formats - free text, dropdown values, numbers - but importantly, the data needs to exist in a field in Account Engagement, and you need to have logic around how to reference it.
For example, if you’re looking for prospects with a job title of ‘Operations Manager’, you’ll need to specify this explicitly in your Grading Profile. This means prospects with a similar job title of ‘Head of Operations’ or ‘Ops Manager’ will not match your criteria. Think about the way data is captured, validated, and referenced to ensure this works cleanly.
If you don’t have the relative values you need for grading, check out our blog post on building your data collection strategy around Account Engagement Grading.
3. Setup Automation Rules
Grading automation
Lead grades automatically adjust via Automation Rules you set up based on the data you hold about a prospect. This data can be about the person, for example, job title. However, the data can also be about the company – industry, the number of employees, and location are frequently used criteria in lead grading.
The system is set out in thirds e.g. 1/3 to represent how much the prospect should increase or decrease. When a lead grade value changes in Account Engagement, it does this in one of three ways:
by a whole letter (D > C)
by 2/3 of a letter (D > C-)
by 1/3 of a letter (D > D+)
Let’s look at an example Automation Rule and how the criteria matches the prospect to the relevant Grading Profile:
Screenshot of a Grading Profile with criteria
In this example, you can see that prospects with the ‘Industry’ of ‘Technology’, ‘Finance’, or ‘Sport’ would match the rule, and the action will change a particular profile criteria by 3/3, meaning it would shift them up a full grade (from C to B, for example).
The starting point for setting this up is to review your prospect profiles. Make sure you add any criteria for your profile that you’re planning to grade your prospects on, as data fields.
TIP: It’s important to note that the default grade for a prospect danish telephone numbers in Account Engagement is always D, so it will take at least three criteria in the Grading Profile to turn a D into an A.
Lead scoring and grading used in tandem enables sales teams to prioritise not only those who are the best customer fit, but those showing real interest in the brand too. Both the score and grade of a prospect will help qualify the prospect as ready for sales contact. We call these types of leads ‘marketing-qualified’ or MQLs.
The key takeaway is that when a prospect reaches a certain ‘threshold’ based on their score and grade, we can assign them to a salesperson for action.
In summary:
Scoring - the prospect’s buying intent based on their engagement with different marketing assets tells us how interested the prospect is.
Grading - the prospect’s likelihood to become a paying customer based on the information they’ve disclosed and how well it matches your buyer personas, such as industry, job title, size of company etc. Grading tells us how interested you should be in a prospect.
For example, if you’re looking for prospects with a job title of ‘Operations Manager’, you’ll need to specify this explicitly in your Grading Profile. This means prospects with a similar job title of ‘Head of Operations’ or ‘Ops Manager’ will not match your criteria. Think about the way data is captured, validated, and referenced to ensure this works cleanly.
If you don’t have the relative values you need for grading, check out our blog post on building your data collection strategy around Account Engagement Grading.
3. Setup Automation Rules
Grading automation
Lead grades automatically adjust via Automation Rules you set up based on the data you hold about a prospect. This data can be about the person, for example, job title. However, the data can also be about the company – industry, the number of employees, and location are frequently used criteria in lead grading.
The system is set out in thirds e.g. 1/3 to represent how much the prospect should increase or decrease. When a lead grade value changes in Account Engagement, it does this in one of three ways:
by a whole letter (D > C)
by 2/3 of a letter (D > C-)
by 1/3 of a letter (D > D+)
Let’s look at an example Automation Rule and how the criteria matches the prospect to the relevant Grading Profile:
Screenshot of a Grading Profile with criteria
In this example, you can see that prospects with the ‘Industry’ of ‘Technology’, ‘Finance’, or ‘Sport’ would match the rule, and the action will change a particular profile criteria by 3/3, meaning it would shift them up a full grade (from C to B, for example).
The starting point for setting this up is to review your prospect profiles. Make sure you add any criteria for your profile that you’re planning to grade your prospects on, as data fields.
TIP: It’s important to note that the default grade for a prospect danish telephone numbers in Account Engagement is always D, so it will take at least three criteria in the Grading Profile to turn a D into an A.
Lead scoring and grading used in tandem enables sales teams to prioritise not only those who are the best customer fit, but those showing real interest in the brand too. Both the score and grade of a prospect will help qualify the prospect as ready for sales contact. We call these types of leads ‘marketing-qualified’ or MQLs.
The key takeaway is that when a prospect reaches a certain ‘threshold’ based on their score and grade, we can assign them to a salesperson for action.
In summary:
Scoring - the prospect’s buying intent based on their engagement with different marketing assets tells us how interested the prospect is.
Grading - the prospect’s likelihood to become a paying customer based on the information they’ve disclosed and how well it matches your buyer personas, such as industry, job title, size of company etc. Grading tells us how interested you should be in a prospect.