What is lead grading? How does it differ from lead scoring?

While lead scoring and lead grading are often used interchangeably in the world of sales & marketing, they’re technically two different practices with their own unique objectives.

What is Lead Scoring?

Lead scoring focuses on the behaviors of a prospective lead and aims to quantify how much interest they have in your company’s offering. Prospects typically earn or lose points based on implicit data gathered as they interact with your website and marketing materials. Prospects who show a strong level of engagement with your website and consume much of your relevant content would be scored higher than prospects who may view your homepage once or have limited interaction with your brand. 

What is Lead Grading?

Lead grading focuses on the characteristics of your leads and aims to qualify how valuable they may be to your company. These leads are often given a letter grade based on explicit data they provide, evaluating how closely their characteristics match your ideal lead profile. Relevant characteristics often start with information provided by the lead through a web form or a similar conversion opportunity. Attributes like their stated industry, geography, company size, job function, and seniority level are all characteristics that often inform a lead grade.

How Lead Scoring and Lead Grading Work Together

While lead scores and lead grades aim to value separate factors, they’re often joined together when ultimately evaluating the total value of each potential lead. The table below shows how lead grades (an estimate of potential fit) can be joined with lead scores (an estimate of interest), where A1 leads have the highest lead grade (A) and the highest lead score (1). 

The combination of lead grades and scores can benefit sales and marketing efforts in a number of different ways. Leads with high score/grade combinations are often prioritized by sales to ensure they’re contacted as quickly as possible, while leads with lower scores or grades may instead fall into a less resource-intensive nurture campaign aimed at building their interest through additional marketing interactions.

Lead score and grade combinations can further be utilized to inform optimal messaging through sales and marketing initiatives as well. Leads who may be graded as an ideal fit (A’s) but with below average interest (e.g. an A3) often benefit from more catered messaging with the understanding that their interest has not yet peaked. These leads are often ideal candidates for nurture campaigns exposing them to marketing content focused on additional product features they may have been unaware of that better align with their interests. 

Lead grading methodologies

Lead grading methodologies range from simple to complex. The simplest and easiest-to-implement models can focus entirely on a small set of characteristics provided by the lead through a web form (i.e. if the lead reports an ideal company size and job title that may be enough to earn an A).

More complex lead grading methodologies typically consider a broader array of lead characteristics, may employ 3rd party data enrichment to capture data that was not explicitly provided by the lead, and may utilize a grading model derived objectively through data-driven algorithms.

The ability to capture and consider a broader array of lead characteristics can often be derived by longer lead forms, where more qualifying questions are asked of the prospect. However additional characteristics can often be considered outside of form fields as well. For example, identifying that a lead originated from a marketing campaign targeting members of a valuable trade group can be included as a defining characteristic of a lead deserving a higher letter grade. Alternatively, the recognition that the lead’s company may already have engaged with sales in the past where structural hurdles prevented the sale may be a characteristic that can decrease the prescribed lead score.

Data enrichment can also be leveraged to supplement the volume of characteristics used to discern a lead score. Oftentimes the characteristics that truly define the most qualified leads may not be accessible through typical website forms. It’s not uncommon for individual characteristics like income, ideology, and other personal attributes to be valuable considerations from a grading perspective while not being questions you can typically ask of a lead through a traditional form. This is where 3rd party data providers can often support a lead grading model without impeding and detracting from the lead conversion process.

Finally data-driven modeling is an increasingly popular lead grading methodology that minimizes any subjectivity in the grading process. Simple models often require you to make a judgement call on how much certain characteristics should inform a lead grade. Keep in mind, common assumptions like ‘larger company sizes should be valued with higher lead grades’ may not always hold true when evaluated through the lens of an algorithm or a data-driven grading model. Data-driven models can utilize regression modeling, pathing analysis, and other cohort evaluations to more objectively discern which characteristics matter the most, and what the optimal values are for each (perhaps we learn mid-sized companies are more valuable to our sales team than large companies). 

How to get started with lead grading

All lead-gen companies prioritizing sales and marketing should utilize some form of lead grading. The question is how sophisticated the model needs to be. The good news is there’s likely an existing solution catered to each level of the market, from Hubspot to Salesforce to bespoke enterprise-level custom software packages. Here are some steps you can take to begin the lead grading process:

  1. Start by evaluating your current customer base. What characteristics do they have in common? Which of those characteristics seem to matter the most when closing a sale? What lead attributes currently tell your sales team that this lead is high value?
  2. Next, discern how you can fill-in-the-blank for each of these characteristics for incoming leads. Can you reasonably expect leads to answer all of these qualifying questions within the scope of your standard lead form? Do you need to lengthen your lead form to gather more information? Does it make more sense to consult a data provider to help fill-in-the-blanks without requesting the information from the lead directly?
  3. Finally, by the time you’re done establishing your lead grading model, you’re actually just getting started. Treat your grading model as a living breathing thing; regularly revisit your grading rubric to ensure you’re continually evolving your framework. Each new lead brings valuable new information about new characteristics and attributes you can value. And as businesses, markets, and industries change and evolve over time, so should your lead grading methodology. The single most important factor in lead grading is to ensure your ability to grade never stops improving.

To learn more about lead grading or how Mindgruve can grow your business, get in touch.