Lead scoring is the process of ranking leads by their likelihood to convert based on their behaviors and characteristics. Learn how to build your own lead scoring system to increase sales faster and improve your marketing efforts.

Here, you’ll find:

In digital marketing, the goal isn’t just to accumulate prospects — it’s to increase qualified leads.

Lead scoring allows you to filter your leads, find the best ones with the most potential, and focus your energy where it’s most likely to pay off.

Without it, you could waste your time and efforts on people with low intent, while your competitors scoop up those most likely to convert.

HawkSEM blog: PPC lead scoring

It’s key to be thoughtful about your sales funnel and the actions leads take that qualify them. (Image: Unsplash)

What is lead scoring?

Lead scoring is the process of grading each lead to rank them by their potential value for your business. This is done by assigning point values based on explicit data (information given by the lead) and implicit data (observed behaviors).

Once a lead achieves a certain score, they can be routed to sales or placed into a targeted nurturing workflow.

Why lead scoring is important

Lead scoring helps you prioritize the leads most likely to convert, maximizing revenue while minimizing wasted effort.

It also helps you better understand how keywords, campaigns, and user behaviors contribute to conversions. This makes it easier to optimize your PPC and broader digital marketing strategy around revenue — not just engagement.

It also gives you deeper insight into how keywords, campaigns, and user behaviors contribute to conversions—making it easier to optimize your PPC and broader digital marketing strategy around revenue, not just engagement.

How to determine the value of lead data

It may be a process of trial and error to figure out the best lead scoring process, model, and metrics for your business. The main criteria for high-quality leads include:

  • Persona fit
  • Level of interest
  • Conversion readiness

Similarly, you can use negative scoring to filter out leads that are fake or spam.

Furthermore, there are many ways to gauge each criterion.

Lead scoring models

There are several lead scoring models using different combinations of attributes and metrics to evaluate leads.

Many scoring systems assign points on a scale (often from 0 to 100) but the structure of each model should be tailored to the signals that best predict conversion for your specific audience and business goals.

1. Demographic and firmographic data match

Every business should develop a good understanding of its target audience.

To start, find similarities between your existing customers and ask them questions about themselves to find trends. This information can help you create your ideal customer profile.

Helpful demographic data could include:

  • Age range
  • Gender
  • Location
  • Marital status
  • Parental status
  • Job title
  • Income
  • Household size

You may also want to include product or service-specific metrics. For example, a toy company might target parents. However, parents of children in college probably aren’t a good fit.

For B2B companies, firmographic data like company size, industry, and revenue can be more predictive than demographic traits alone

2. Behavioral factors

Unlike explicit data (like a job title or geographic location), implicit lead scoring leans on observed behaviors.

Behavioral interest indicators might look like:

  • Multiple site visits
  • Longer time spent on a page
  • Scrolling to the bottom of a page
  • Visiting multiple pages
  • Downloading a resource
  • Contacting your team
  • Requesting more information
  • Requesting a demo
  • Providing their email address
person typing on a laptop

Implementing lead scoring using up-to-date best practices can be an effective way to have your sales and marketing teams working together better and more efficiently. (Image: Unsplash)

3. Purchase qualification

Purchase qualification helps determine whether a lead has the ability and readiness to buy using intent data.

This is also determined through behavioral data alongside first-party and third-party data sources, such as form fills and IP addresses.

For example, leads who visit pricing pages, request quotes, or ask detailed product questions often indicate higher purchase readiness than those engaging only with educational content.

4. Negative scoring

Negative scoring models assign point deductions to behaviors or attributes that indicate a lead is actually spam — or unlikely to convert.

Assigning negative scores helps prevent inflated lead scores and misaligned sales handoffs.

For example, leads on your email list can get points just for joining. However, each lead that doesn’t open an email can earn negative points with each unopened email in a row, lowering their score further.

Similarly, a lead who only downloads educational content but never opens product-specific emails or visits pricing pages (or unsubscribes altogether) could strongly indicate interest in information rather than intent to buy.

5. Predictive models

Companies with access to a large amount of lead data can explore predictive lead scoring. Predictive lead scoring models use machine learning to analyze historical data points.

Traditional lead scoring can be more subjective, since your team lists the criteria they think are relevant and a point system to rank them.

Predictive lead scoring, on the other hand, is data-driven and uses algorithms to find patterns that may otherwise be overlooked.

How to calculate a lead score

While there is no one single way to calculate a lead score, many digital marketers follow a four-step process:

1. Calculate your baseline conversion rate for all leads

Start by determining your overall lead-to-customer conversion rate. This establishes the benchmark you’ll use to evaluate which attributes truly indicate value.

Here’s the equation to calculate your overall lead-to-customer conversion rate:

(Number of leads who became customers) / (Total number of leads) X 100

2. Identify attributes of current high-value customers

Analyze your current customers who began as high-quality leads to uncover shared demographic, firmographic, and behavioral attributes.

This could be the type of industry they’re in, company size, customers who asked for a live demo or webinar, or the role or job title they hold at their company.

3. Calculate the close rate for each individual attribute

Using your list of lead attributes, determine the number of leads who became customers based on their behavioral attributes or demographic characteristics.

Attributes or actions that were more likely to lead to a conversion will be assigned a higher score.

4. Compare attributes’ close rates to your baseline

Compare each attribute’s close rate against your overall conversion rate.

  • Attributes that convert above baseline should receive positive scores
  • Attributes that convert at or below baseline should receive low, zero, or negative scores

This ensures your scoring model rewards revenue-driving actions, not just engagement scores.

Lead scoring tools

Getting more than a couple of leads per week? Then it’s probably best to leverage a tool like Google Analytics to help you track keyword conversions.

You or your marketing agency can connect this application to your customer relationship management (CRM) tool, such as HubSpot, or a marketing automation platform (MAP) or other lead scoring software.

This will allow you to begin scoring leads based on behaviors and actions the new contact or potential customer has taken.

Lead scoring best practices and optimization: 6 expert tips

Lead scoring best practices help ensure your model stays accurate, adapts to changing buyer behavior, and drives higher-quality leads to sales.

Here are our top tips:

1. Refine your model over time

Don’t try to create a perfect model on your first try. Begin with a basic set of scoring criteria — like persona fit, engagement, and purchase readiness — and gradually add more factors as you gather data.

When you’re ready, you can get more granular by weighing things like different pages and pieces of content differently.

For example, a case study, white paper, or service page may be worth more points than an evergreen guide or your homepage.

Use lead generation tools to make real-time adjustments so your sales team can qualify inbound leads accurately.

2. Don’t forget negative lead scoring

Scoring actions too broadly — like giving points for page visits without considering the page type, dwell time, and actions on-page — can easily lead to falsely inflated scores.

3. Use explicit and implicit data

Combine explicit data (concrete information leads provide) with implicit behavioral data. A blended approach gives a more complete picture of a lead’s quality and sales-readiness.

4. Be thoughtful about weighted scoring

Assign higher points to behaviors that indicate stronger purchase intent, such as requesting a demo, and lower points to low-intent interactions like reading a blog post.

5. Set follow-up workflows based on scores

Define score ranges that trigger follow-up actions. For example, nurturing for low-scoring leads, marketing-qualified lead (MQL) status for medium scores, and sales outreach for high scores. Make sure score thresholds are informed by historical conversion data, not guesswork.

6. Align your marketing and sales team

Scoring leads is a great way to ensure your sales and marketing teams are aligned.

With that in mind, it’s a good idea for marketing team members to periodically check in with the sales department to see which types of leads are closing most often.

This will ensure that the lead scoring parameters you have in place are as accurate as possible.

You want to have enough time to accrue significant data that you can analyze properly, so aiming to do one of these check-ins a few times a year is usually sufficient.

Does lead scoring make sense for longer sales cycles?

A longer sales cycle means it can take a longer time to see results. Lead scoring is still important for these campaign types because you need to understand each lead’s value along the sales cycle.

This falls under the low-hanging fruit theory of easy wins. By scoring leads, you’ll know which prospects are closer to a sale and which are further away.

This will help you better prioritize where to put your efforts as the cycle moves along.

The takeaway

Forget hot leads falling through the cracks or wasting time following up on unqualified or uninterested prospects.

Implementing lead scoring using up-to-date best practices can be an effective way to have your sales and marketing teams working together better and more efficiently.

While it may take some tweaking to find the exact right method of lead scoring for your business, the time and investment are sure to be worth it once you see more leads becoming closed deals.

Whether you’re a small business or a SaaS supergiant, HawkSEM’s team of digital marketing experts can help you score your leads, optimize your marketing strategy, and rev up your sales process.

If you need more than lead generation, reach out.

This post has been updated and was originally published in August 2014.

Josie Rojewski

Josie Rojewski

Josie is a content marketing writer with more than 7 years of digital marketing, content writing, and editing experience. She uses her linguistics and teaching background to compose in-depth articles, how-to guides, and other SEO-friendly content to help marketing leaders succeed. She loves reading, baking, and searching for the perfect pen.