If you optimize your website and run campaigns that hit hard, but still end up with a low conversion score, the problem isn’t the number of leads, it's their quality. 

The initial goal of all lead generation efforts is to fill up your sales pipeline. However, Hubspot reports that 57% of B2B companies consider "turning leads into paying customers" a top priority in their sales funnel.

After all the effort you put into grabbing attention and bringing in leads, you must look at the quality of those prospects and how soon they might be ready to buy. 

You need to figure out who's casually browsing on the interest, who seems interested in what you offer, and who’s actually ready to pull the trigger. Building a lead-scoring system helps you understand your leads. 

In this article, I’ll explain what is lead-scoring, why you should start doing it, its different models, and a quick way to calculate your lead score. 

What is Lead Scoring?

Lead-scoring is a method to figure out how ready a lead is to become your customer. It is a system where you assign points to potential customers (or leads) based on different things they do or characteristics they have. 

The higher the lead score, the more interested or qualified they are.

Lead scoring takes several kinds of data points into account, such as lead demographics, behavioral data, industry and revenue for B2B leads, engagement levels, etc. 

The process of lead-scoring can be manual or automated. In manual scoring, your marketing and sales teams set up rules and assign points based on their experience. 

On the other hand, automated lead scoring tools track, score, and update leads automatically, which, of course, is more efficient and consistent.

Recently, there has also been quite some buzz about predictive lead scoring. 

Instead of just adding up points based on set rules, predictive lead-scoring uses AI and machine learning to analyze past data and predict which leads are most likely to convert. 

CRM systems combined with AI lead generation tools are used to look at tons of historical data and make lead-scoring decisions.

Importance of Lead-Scoring

Lead-scoring helps you sort through all the potential customers and figure out who’s actually worth spending your time on. According to Marketing Sherpa, companies that use lead scoring typically see a 77% increase in lead generation ROI compared to those that don't use it.

You can have hundreds or thousands of leads coming in, but without a system, your sales team will end up wasting hours chasing people who aren’t really interested. 

Lead scoring makes sure your team is putting energy into leads that are ready to buy or are at least highly interested. 

When leads are scored and prioritized, it’s easier for lead generation specialists to hand over warm, qualified leads to sales. That way, the sales team isn’t starting from scratch with cold calls but working with people who are already halfway in the door.

A lead scoring system also helps you understand your audience. You start to see patterns when tracking what actions and characteristics add up to a high score. Let’s say, you notice that people who attend your webinars are more likely to buy your product. 

This data is pure gold because it guides your future marketing strategies. You have a clear understanding of marketing channels that work for your business and can easily refine your campaigns.

Different Lead Scoring Models

Different lead-scoring models you set up will highlight specific traits of your ideal customer on a score of 1 to 100. 

Here are 3 most popular models:

1. Demographic and Firmographic Lead-Scoring

This lead generation model qualifies leads based on who they are and, in B2B scenarios, what their company looks like. You can narrow down your leads just by knowing whether they have the right background or work for a company that matches your target criteria.

Demographic scoring focuses on individual-level data. For example, it looks at attributes like the lead’s age, gender, occupation, education level, location, you get the gist. 

Firmographic scoring is for B2B and looks at company-level data, such as industry, company size, annual revenue, tech stack, growth rate, etc. 

This model is the first step in a lead-scoring system where you quickly weed out leads that don’t fit your ideal customer profile. 

2. Sales lead Scoring

Sales-based scoring leans on insights and direct input from the sales team established on their interactions with potential customers. It works best for companies that have a sales-led approach, especially at the enterprise level. 

Such a sales process includes custom pricing, tailored contracts, or multiple meetings to close a deal. 

Key lead scoring metrics of this model include sales email open rate, response rate, participation in meetings, quote and demo requests, etc. 

3. Engagement-based Lead-Scoring

Engagement-based lead scoring looks at how leads interact with your company across various channels, email, social media, your website, and the content you put out.

It is perfect for businesses that rely on nurturing leads through educational content, regular communications, and multi-channel outreach. 

If your business uses email campaigns, blogs, webinars, and social media to move leads down the funnel, this model identifies which prospects are most engaged and ready for a direct approach. 

Some main metrics for engagement-based lead-scoring models include page visits, time on site, blog/post views, comments, shares, followers, etc.

How to Calculate Lead Score: 6 Easy Steps + a Simple Lead Scoring Calculator

Here’s a basic step-by-step guide on how to calculate lead score manually:

1. Calculate Your Lead Conversion Rate

The purpose of calculating your baseline lead conversion rate is to understand how effective your sales and marketing efforts are at turning leads into customers. 

To calculate your lead conversion rate, divide the number of leads that convert (become customers) by the total number of leads and multiply that number by 100. 

For example, if you had 200 leads and 20 of them converted, your conversion rate would be (20/200) * 100 = 10%. 

2.  Pick the Right Attributes to Score

Next, you will define the factors that make a lead more likely to convert. Now, this requires a bit of skill. You should base your choices on discussions with your sales team and previous data analysis to make an informed decision.

You can consider customer behavioral data, as in, how many times they visit your website, what specific pages they look at, if they open your emails, or if they participate in webinars. 

The more specific you can get about what actions or characteristics predict conversion, the better your scoring model will be.

3. Find the Conversion Rate for Each Attribute

Once you know which attributes to score, look at your past data to see how likely a lead with each specific attribute is to convert. 

For instance, if you’re scoring the “job title” attribute, you may see that “Marketing managers” have a 15% conversion rate, while “interns” only convert at 2%. 

You’ll want to go through each attribute in your chosen set and calculate its individual conversion rate.

If you notice that certain attributes have little to no impact on conversion, it’s a sign to remove them from the lead-scoring model.

4. Assign Points Based on Conversion Rates

Take a look at the conversion rate for each attribute and compare it to your overall lead conversion rate from Step 1. Then, assign it a point score on a simple scale, like 1 to 100. 

If an attribute’s rate is higher than your overall conversion rate, it’s a strong positive indicator and should be assigned a higher score. 

For example, if your overall rate is 7% but “Marketing managers” convert at 15%, then this attribute deserves a higher score. In contrast, “interns” with a 2% conversion rate get a lower score.

5. Account for Negative Scores

Negative scores are just as important for giving a complete view of your leads. Assign negative points to attributes that show low interest or poor fit. 

For example, if a lead hasn’t opened any of your emails in six months or has unsubscribed from your newsletter, they may get a -10 score. Leads that don’t match your ideal customer profile will also get negative scores.

Negative scores balance out the overall score so that leads that aren’t really engaged don’t look better than they should. 

6. Add Up the Scores

After assigning points to all your chosen attributes, both positive and negative, add them up for each lead to a get total lead score that shows how qualified a lead is. 

The higher the score, the more likely the lead is to convert, so you’ll know where to focus your efforts.

Here is a simple lead generation calculator:

<!DOCTYPE html>
<html lang="en">
<head>
    <meta charset="UTF-8">
    <meta name="viewport" content="width=device-width, initial-scale=1.0">
    <title>Lead Scoring Calculator</title>
    <style>
        body {
            font-family: Arial, sans-serif;
            background: linear-gradient(135deg, #2e3b4e, #1e2433);
            color: #ffffff;
            margin: 0;
            display: flex;
            justify-content: center;
            align-items: center;
            height: 100vh;
        }
        .calculator-container {
            background: #ffffff;
            color: #333333;
            padding: 20px;
            border-radius: 10px;
            box-shadow: 0 5px 15px rgba(0, 0, 0, 0.2);
            max-width: 400px;
            width: 100%;
        }
        .calculator-container h1 {
            text-align: center;
            margin-bottom: 20px;
        }
        .form-group {
            margin-bottom: 15px;
        }
        .form-group label {
            display: block;
            font-weight: bold;
            margin-bottom: 5px;
        }
        .form-group input,
        .form-group select {
            width: 100%;
            padding: 10px;
            border: 1px solid #ddd;
            border-radius: 5px;
            font-size: 14px;
        }
        .calculate-btn {
            background-color: #f76015;
            color: #ffffff;
            border: none;
            padding: 12px;
            width: 100%;
            font-size: 16px;
            border-radius: 5px;
            cursor: pointer;
            transition: background-color 0.3s ease;
        }
        .calculate-btn:hover {
            background-color: #d94c0f;
        }
        .result {
            margin-top: 20px;
            font-size: 18px;
            font-weight: bold;
            text-align: center;
        }
    </style>
</head>
<body>
    <div class="calculator-container">
        <h1>Calculate Your Lead Score</h1>
        <div class="form-group">
            <label for="leadSource">Lead Source:</label>
            <select id="leadSource">
                <option value="10">Organic Search</option>
                <option value="15">Referral</option>
                <option value="20">Social Media</option>
                <option value="25">Paid Search</option>
                <option value="30">Email Campaign</option>
            </select>
        </div>
        <div class="form-group">
            <label for="pageViews">Number of Page Views:</label>
            <input type="number" id="pageViews" placeholder="Enter number of page views">
        </div>
        <div class="form-group">
            <label for="timeOnSite">Time on Site (minutes):</label>
            <input type="number" id="timeOnSite" placeholder="Enter time spent on site">
        </div>
        <div class="form-group">
            <label for="emailEngagement">Email Engagement (1-10):</label>
            <input type="number" id="emailEngagement" placeholder="Rate engagement (1-10)" min="1" max="10">
        </div>
        <button class="calculate-btn" onclick="calculateLeadScore()">Calculate Score</button>
        <div class="result" id="result"></div>
    </div>

    <script>
        function calculateLeadScore() {
            const leadSource = parseInt(document.getElementById("leadSource").value);
            const pageViews = parseInt(document.getElementById("pageViews").value) || 0;
            const timeOnSite = parseInt(document.getElementById("timeOnSite").value) || 0;
            const emailEngagement = parseInt(document.getElementById("emailEngagement").value) || 0;

            const leadScore = (leadSource + pageViews * 0.5 + timeOnSite * 2 + emailEngagement * 10).toFixed(2);

            document.getElementById("result").textContent = `Lead Score: ${leadScore}`;
        }
    </script>
</body>
</html>

Automate Lead-Scoring with Intelligent Formaloo Forms!

Formaloo makes lead-scoring super simple with its online form templates that include automated lead scoring calculation features. You can create forms where leads answer questions about their business, needs, and buying intentions. 

Each answer automatically gets a point value based on what matters most to your ideal customer. As they fill out the form, their score is calculated behind the scenes, and once they’re done, they’re categorized into “Hot,” “Warm,” or “Cool” groups.

You can easily tailor the form to fit your specific buyer persona and customize the questions to get a clear, 0-100 score for each lead. 

Check out Formaloo today to make your custom lead-scoring form.