Having a robust Account-Based Scoring Methodology in Salesforce can help you separate the wheat from the chaff in your prospect accounts. This will allow your sales team to quickly follow up on leads that might have a low lead score, by prioritizing the account fit in your target market.
Account based scoring is similar to Lead Scoring Methodologies, which are, in essence, just an individual score for a single person (in Salesforce as an email contact/name/etc). Key components of a Lead Score can be whether this ‘person’ is downloading content from your site, visiting key pages and/or many pages in one session, how frequently they visit, and other key factors.
NOTE: I will be sure to elaborate more about lead scoring best practices in another article in the future, so stay tuned!
Likewise, if you are able to discern what your target market Customer company looks like, you will also be able to score these accounts. Some key components are easy to find, and others, not so much. For example, things such as Location, Employee Size, Industry, and Revenue can help you zone in on which companies you are a best fit with. Some of these factors should be relatively easy to identify and locate the accurate information of. For example, if you are located in the SF Bay Area, and you are a service company, you may want to score an Account higher if they are within your service location. Similarly, if you sell analytical software for tracking visitors on ecommerce websites, knowing that your prospect’s industry is Ecommerce (they use Shopify/Bigcartel/Magento, or some other ecommerce software) would mean that they, more often than not, could be within your target demographic.
There is other data that may not be so easy to find out. For example, say you sell a bolt on plugin for users of Microsoft Outlook. Knowing that your prospect has that software as their corporate-mandated email service would most likely include them as a fit within your target market. There are multiple vendors who can provide this data [for a fee] that I have had experience working with, such as Builtwith, Datanyze, Hunter.io, and HGData.
The exercise of identifying key components of your target demographic will be left to another post. What is relevant here is that this data can also be included in an Account Based Scoring Model.
Creating an Account-Based Score in Salesforce
Creating an Account Based Score in Salesforce, in practice, is easy to implement. After you’ve identified the attributes of your target customer, you can then start tracking that data. You’ll first need to have fields that you can capture the relevant data in. Let’s create four sample fields in a hypothetical scenario, where each will have four picklist values as well:
A) An Industry field with picklist values of:
-Software
-Real Estate
-Distribution
-Service
B) An Employee Size field with picklist values of:
0-10
10-99
100-999
999+
C) A Location field with picklist values of:
-United States
-Mexico
-Canada
-Canada
D) A Revenue field with picklist values of:
-$0-$100k
-$100k-$1mm
-$1mm-$10mm
-$10mm +
NOTE: In practice, these fields may not be necessary. For example, you can use the selection of “Billing Country” within Salesforce or another CRM to build out the scoring formula field in the next section.
Account Based Scoring Best Practices
For best practices, and to get the correct score on your prospect Accounts, each of the above picklist values can have an associated score as well. Let’s say we’re going to figure out the Account score on a 0-100 point scale, and we decided to give equal weight to the four scores to each of the fields that are attributes of your scoring model. We would then have to decide the individual score of each picklist value in each field above. We can give each picklist value a score of “0-5”, because we’ll be using the Salesforce CASE function in a formula on a each field as a score.
To use the CASE Function to figure out the score of each picklist value, we’ll create four new fields: Industry Score, Employee Score, Location Score, & Revenue Score:
For the each of the attribute fields, we’ll create the associated scoring field in the same process. As an example, we’ll just create the Revenue Score field here. Create a new field on the Account Object, and set field type as a Formula. Have the field return a number. In our hypothetical company, let’s say that we have found success selling to companies in the $1 million to $10 million dollar range. For small companies, with found only some success to selling to them if they have revenue with less than $1 million, but not as much as the sweet spot. Let’s also say that we don’t sell to enterprise or small seed stage startups due to long sales cycles and churn rate, respectively. We’ll say the our sweet spot revenue is a ‘5’, and the secondary revenue figure is a ‘3’, while the rest would be 0 (or null). To create the Formula field, we’ll set it up like this:
CASE(Revenue__c,
“$1mm-$10mm”, 5,
“$100k-$1mm”, 3,
0)
What this formula does is look at the Revenue field (Revenue__c), through the case object, if it has the picklist value of “$1mm-$10mm”, it will return 5. If Revenue has a picklist value of “$100k-$1mm”, the Revenue Score will return 3. Now let’s save the formula. We don’t have to add this to any page layout. Do this for each of the other three scoring fields.
To bring this Account Score all together, we’ll create another Formula Field that sums up the four Account Scoring fields. Let’s called this field Account Score. Since we said our Account Score will be based on a 100 point scale, and each account score is given equal weight, we can create the account score formula as follows:
(Industry_Score__c + Employee_Score__c + Location_Score__c + Revenue_Score__c) * 5
What the above formula will do is sum the values from the CASE formulas in each of the “Score” Field. Again, these CASE formulas will return a number based off the picklist selections of the Account Based Scoring model we developed. Since each picklist value will be scored as a maximum value of 5, if we summed all four score fields at the highest score, they would equal (5 + 5 + 5 + 5) * 5, simplified to 20 * 5, or return the score of 100 in the Account Score formula field above. Any picklist value of the attribute fields with a score below 5 will fall along the spectrum of 0-100 points.
Once these fields are created for the account records, you can then add them to your Prospect and/or Customer page layout.
Congrats, you’ve successfully created an Account Based Scoring Methodology in Salesforce!
Let me know what factors you might have to identify your target customers in the comments below.
