What is Lead Scoring? A Guide to Models & Effective Scoring

Jul 1, 2023 - By Skirmantas Venckus

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Everyone’s busy chasing more prospects and interested leads than ever before. But do you know that nurturing and scoring leads can give you better results in the long run? 

Lead scoring involves scoring leads based on their engagement and activity and helps you keep your prospects interested by sharing personalized and relevant communication at the right time. When done right, lead scoring can increase your lead conversion rates. In this blog, let’s look at lead scoring and how to get started with it. 

What is Lead Scoring? 

Lead scoring is a method to assign a numerical value or score to individual leads, indicating their likelihood of converting into a customer.

Think of it as a simple system of assigning points to all your leads, let’s say, on a scale of 0 to 100. The closer a lead is to 100 (high score), the higher the likelihood of conversion. 

The lead scores depend on different attributes or behaviors of a lead, like clicking a button, checking the pricing page, engagement behavior, or online activity. For example, a lead who has signed up for a free trial will have a higher lead score than someone who has just signed up for your newsletter. 

Lead scoring helps optimize marketing efforts by helping identify and prioritize leads with the highest potential for conversion. There are two ways to score leads — implicit and explicit. While implicit lead scoring leverages behavioral data to assign scores based on engagement, while explicit lead scoring relies on information provided directly by leads. 

Explicit Lead Scoring

Explicit lead scoring involves collecting information directly provided by the leads themselves, usually through forms or surveys. This information includes demographic data, job titles, company size, purchase intent, and other relevant details. Here are a few attributes used to score leads explicitly: 

  • Demographic information. Age, gender, location, industry, company size, etc.
  • Job title and role. Decision-making positions, specific departments, management levels; 
  • Firmographics. Company revenue, annual budget, years in operation; 
  • Purchase intent. Timeframe for purchase, budget availability, and specific requirements; 
  • Form responses. Specific questions answered, level of detail provided; 
  • Interaction history. Previous purchases, webinar attendance, and event registrations.

The explicit data is used to assign scores to leads based on predefined criteria set by the marketing team. For example, imagine a B2B company that sells marketing automation software. They may consider leads from enterprise-level companies with specific job titles, such as marketing managers or directors, as more valuable. In their lead scoring model, the scoring criteria assign higher scores to leads that match these attributes. 

By gathering explicit information through forms or surveys, they can identify leads that meet their ideal customer profile and prioritize them for targeted sales outreach or tailored marketing campaigns.

Implicit Lead Scoring

Implicit lead scoring involves gathering data and analyzing a prospect’s online activity or behavior during their interactions. These ‘implied’ actions are typically tracked using marketing automation tools, heatmaps, or web analytics platforms. Here are some of the implicit attributes to track: 

  • Website behavior. Number of page visits, time spent on the website, specific pages viewed; 
  • Content engagement. Whitepapers, case studies, eBooks download or watching videos; 
  • Email engagement. Email opens, click-through rates, interactions with links or attachments; 
  • Social media activity. Likes, comments, shares, mentions, followership; 
  • Online advertising response. Clicks on ads, engagement on ad campaigns; 
  • Customer support interactions. Live chat conversations and support ticket submissions. 

Evaluating implicit signals like website visits, content downloads, email opens, clicks, and social media engagements help businesses assign a lead score based on their level of engagement and interest.

Take the example of a software company that offers a free trial. A trial customer frequently uses different features, and raising support tickets suggests a higher likelihood of converting to a paid customer. The implicit behavior makes them a priority for the marketing team to target using personalized nurturing campaigns or incentives to accelerate conversion further.

Benefits of Implementing Lead Scoring

Lead scoring helps you rank prospects in accordance with their buying intent and, in the process, identify higher-quality leads. Understanding which leads are more likely to convert will save you time and improve your marketing effectiveness. Businesses reveal the following benefits of using lead scores: 

Here are some of the significant benefits of lead scores: 

1. Lower Marketing and Acquisition Costs

Businesses can reduce marketing and acquisition costs when they implement lead-scoring tactics. Prioritizing and focusing on nurturing qualified leads helps optimize marketing efforts and allocate resources more efficiently.

  • Better understanding of qualified leads enables businesses to invest in channels and strategies that have a higher potential to reach and convert those leads, optimizing marketing spend; 
  • Efficient resource allocation based on lead scoring results in reduced costs per acquisition and improved overall cost-effectiveness of marketing campaigns.

2. Higher Conversion Rates with Less Time Wasted

38% of businesses confess that lead scoring helped them increase conversion rates of qualified leads to sales opportunities. When you score leads based on their behavior, activity or other relevant attributes, marketing teams save time that’s otherwise wasted on nonserious leads. 

  • Lead scoring allows for more targeted and personalized lead nurturing, resulting in improved engagement and higher conversion rates;
  • Lead scoring allows marketing teams to automate the identification of leads exhibiting strong interest, saving them precious time and energy. 

3. Better Sales and Marketing Alignment

Lead scoring fosters better alignment between sales and marketing teams by providing a common framework and criteria for lead evaluation. This alignment improves communication, collaboration, and overall efficiency in the lead management process. 

  • Marketing teams pass on qualified leads to sales with clear and relevant information, leading to more productive sales conversations; 
  • Improved sales and marketing alignment results in streamlined lead management, enhanced lead handoff, and more efficient utilization of resources.

4. Higher revenue

Lead scoring contributes to increased revenue generation by focusing efforts on leads that are more likely to convert. Businesses can improve their sales effectiveness and drive more revenue by prioritizing and nurturing qualified leads. Key points to consider:

  • Personalized and targeted nurturing based on lead scores improves engagement and conversion rates, resulting in more closed deals and increased revenue;
  • Efficient utilization of resources based on user engagement and interest helps reduce the cost of operations and improves marketing and sales productivity, adding to the bottom line. 

What are Lead Scoring Models?

With so many evident benefits of scoring leads, you’d be eager to get your hands on some lead-scoring tactics and models. We’ve curated the best-performing lead-scoring models based on common knowledge and industry performance. Check these lead scoring models below and pick one that suits your business model: 

Demographic Information

Demographic lead scoring involves giving scores based on personal information. This model focuses on demographic factors such as age, gender, location, job title, and industry to gauge the potential value and fit of a lead for the business. Some attributes and examples for demographic lead scoring include:

  • Job title. Higher-level positions may indicate decision-making authority or influence; 
  • Industry. Leads from specific sectors may be more likely to convert due to their relevance to the product or service;
  • Company size. Larger companies may have higher budgets and more significant potential for larger purchases;
  • Geographic location. Targeting leads in specific regions can help tailor marketing efforts to their needs or preferences;
  • Annual income. For B2C businesses, income levels can indicate purchasing power.

Company Information

This model evaluates the attributes and characteristics of a lead’s company to determine their potential value. It looks at factors such as company size, industry, revenue, and technographic data to assess the likelihood of a conversion. Here are some examples of attributes for company lead scoring:

  • Company revenue. High-revenue companies may have greater budget availability for purchases;
  • Industry fit. Leads in industries that align with the business’s target market are more likely to convert;
  • Technographic data. Identifying if a company already uses relevant technologies or tools can indicate their need for the product;
  • Growth rate. Fast-growing companies may have more significant demands and investment capabilities;
  • Funding. Companies that recently secured funding or received investments may have additional resources.

Online Behavior

Using online behavior for lead scoring is an implicit tactic that involves tracking and analyzing the digital interactions across the website and landing pages. This model focuses on actions taken by leads, providing insights into their level of engagement and interest. Examples of attributes for online behavior lead scoring include:

  • Website visits. Number of visits, time spent on the website, and specific pages viewed;
  • Content engagement. Downloads such as whitepapers, eBooks, or case studies;
  • Webinar attendance. Participation in live or on-demand webinars;
  • Form submissions. Filling out contact forms or request forms;
  • Search queries. Keywords or topics searched on the website.

Email Engagement

Lead scoring based on email engagement involves assessing how leads interact with marketing emails. Factors such as opens, clicks, and responses are critical to assign lead scores. Examples of attributes for email engagement lead scoring include:

  • Email open rate. Tracking the frequency and consistency of a lead opening marketing emails; 
  • Click-through rates. Measuring the percentage of leads who click on links within emails; 
  • Conversion actions. Tracking specific actions taken, such as filling out a form or making a purchase, after clicking an email link; 
  • Unsubscribe rates. Monitoring leads who opt out of email communications; 
  • Email responses. Tracking leads who reply to emails or express direct interest.

Social Engagement

Scoring based on social media engagement is a great tactic to measure the stickiness and virality of your content. It involves evaluating a lead’s interactions and engagement on social media platforms, such as likes, comments, shares, and mentions. Higher the engagement, the higher the score. Examples of attributes for social engagement lead scoring include:

  • Likes and shares. Tracking the number of likes and shares of a company’s social media posts; 
  • Comments and replies. Assessing the engagement level through comments or reactions to posts; 
  • Mentions and tags. Monitoring when a lead mentions or tags the company on social media;
  • Follower count. Evaluating the number of followers a lead has, indicating their potential reach and influence.

Spam Detection

This involves evaluating leads to determine their likelihood of being spam or low-quality leads. This model helps ensure the scoring system focuses on genuine, high-quality leads. Examples of attributes for spam detection lead scoring include:

  • Disposable email addresses. Email addresses from temporary or disposable email providers indicate low-level of interest in a product or service; 
  • Suspicious or irrelevant form responses. Responses that may appear suspicious or irrelevant to the business should be given lower lead scores; 
  • IP address checks. The reputation and origin of the IP address associated with the lead should impact the lead score; 
  • Blacklist checks. Checking lead data against known spam email lists or databases.

Alignment Between Marketing and Sales

This lead scoring model evaluates the synchronization and fits between a lead’s real attributes and the ideal customer profile defined by the marketing teams. This model helps ensure that the pursued leads align with the business’s target market and sales goals. Examples of attributes for alignment lead scoring include:

  • Ideal customer profile fit. Evaluating how closely a lead matches the criteria set for the ideal customer; 
  • Sales and marketing interaction history. Assessing the level of engagement and collaboration between the lead and the marketing and sales teams; 
  • Lead qualification criteria. Determining if a lead meets the predefined qualification criteria the sales team sets;
  • Sales feedback and ratings. Gathering feedback and ratings from the sales team on lead quality and fit;
  • Opportunity stage. Evaluating the stage of the lead within the sales pipeline or funnel.

Lead Scoring Threshold

The lead scoring threshold is the prearranged score determining whether a lead is qualified. When a lead crosses the ‘threshold’ score, it’s passed from the marketing team to sales for sales enablement. This tactic helps establish a clear benchmark for lead qualification. Here’s how you can set up a lead-scoring threshold: 

  • Point-based scoring. Assigning a numerical value to each lead attribute and determining the threshold based on the accumulated score and past lead qualification history;
  • Scoring tiers. Grouping leads into different categories or tiers based on their scores and defining the threshold for each tier;
  • Qualification criteria. Setting specific requirements or conditions that a lead must meet to cross the scoring threshold;
  • Historical conversion data. Analyzing historical data to determine the score range that has resulted in successful conversions;
  • A/B testing. Experimenting with different scoring thresholds and measuring the impact on conversion rates to optimize the threshold value.

Explicit Scoring

Explicit scoring involves gathering information directly from leads through forms, surveys, or other direct interactions to assign scores based on predefined criteria. This model relies on the information leads provide to assess their fit and potential as customers. Examples of attributes for explicit scoring include:

  • Demographic data. Collecting information such as age, gender, location, and job title to determine the lead’s relevance to the target market;
  • Firmographics. Gathering data on the lead’s company, including industry, company size, annual revenue, and number of employees, to evaluate their potential as a customer; 
  • Purchase intent. Asking leads about their specific needs, budget availability, purchase timeframe, or product requirements to gauge their readiness to purchase;
  • Qualifying questions. Designing targeted questionnaires and surveys to gather insights into the lead’s pain points, challenges, or goals, which can help determine their potential as a customer;
  • Lead source. Assessing the quality and relevance of the lead source, such as a referral, trade show, or website form, to gauge the lead’s potential fit with the business.

How to Score Leads in 4 Steps? 

You already know that scoring leads involve assigning numerical values or scores to prospects based on their likelihood of conversion. But how to get started with lead scoring? Here are four steps that will quickly help you set up a lead-scoring system: 

Calculate the Conversion Rate. 

Analyze historical conversion data, representing the percentage of leads successfully converting into customers. Use this as a benchmark for determining the potential for conversion. For example, if you had 1,000 leads in a month and 100 converted into customers, the conversion rate would be 10%;

Develop Characteristics from High-Quality Converted Customers. 

Identify the key characteristics and traits shared by past converted customers. Look for patterns in their demographics, firmographics, online behavior, and interactions. Some examples include demographics (age, gender, location), firmographics (industry, company size, annual revenue), online behavior (website visits, content downloads, page engagement), email engagement ( open rates, click-through rates); 

Calculate Scores for Each Attribute. 

Assign a score to each attribute based on its relevance and impact on the lead’s conversion potential. For example, if you found that people aged 30-35 are the highest converting section, you should assign a higher score for leads in this age group, and so on; 

Map Your Customer’s Journey and Key Traits. 

Finally, map the customer journey from lead acquisition to conversion, identifying key touchpoints and behaviors that indicate a lead’s progression towards becoming a customer. This helps assign scores based on the lead’s movement through the sales funnel. For example, an initial website visit followed by content downloads can signify lead acquisition and assignment of a score accordingly. 

Implementing A Stellar Lead Scoring Models For Your Organization

When serious about lead scoring, you must go beyond the basics and build a solid framework for your company. Here is an illustrative lead-scoring process on how you can improve your lead-scoring efforts over time: 

  1. Research. Go through your entire customer list manually and list attributes that are common to them. Use any analytics component inbuilt into your CRM for this; 
  2. Determine Key Attributes. Compare dominant attributes that many customers share in common with your leads list. This will tell you which leads indicate possible future conversion. For example, age, location, industry size, budget, source of the lead (from a specific social media platform), etc. Leads from the leads list with similar properties will be more valuable to you than the others;
  3. Assign Points. Remove subjectivity from the equation by assigning lead scores (based on the lead models above). Lead scores could be a scale of 1-10 to keep things simple;
  4. Add up. Design your lead score structure so the lead with the most potential could have a “perfect score” of 10. It helps keep things straight. If you’re using your CRM’s in-built feature or external lead-scoring plugin, you can use the predictive lead scoring feature, and all of your leads will be assigned a lead score;
  5. Define a Threshold for Sales Handoff. In this step, we define at what score all leads will be handed over to sales reps since they’ve been nurtured enough or if they have engaged with us enough. e.g., all lead scores of 6 and above could be handed over to the sales team; 
  6. Continuously Improve this Framework. As you convert more and more leads into paying customers, you will have more data that will give you even greater insights. Update your lead scoring attributes based on your goals and optimize them periodically. 

Key Takeaways

  • Score your leads to boost marketing effectiveness and sales revenue; 
  • Adopt a lead scoring model based on your past lead conversion data or business goals; 
  • Use marketing automation software to automate lead nurturing campaigns based on lead scores; 
  • Keep optimizing your lead scoring criteria to account for changing consumer preferences. 

Also, read:

Author Bio

Anmol Ratan Sachdeva is a content marketer and small business consultant who has a strong grip on topics like marketing automation, email marketing, and content marketing. He loves to write about building, improving, and growing a business.

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