How To Implement a Lead Scoring Model Step-by-Step

This article guides you through the different lead-scoring models and how to use them to enrich and prioritize leads.

TL;DR

• Lead scoring is a methodology marketing and sales teams use to rank leads according to their perceived value or likelihood to convert.

• Lead scoring can be manual, assigning points to leads based on predetermined criteria, or automated using tools like HubSpot or PhantomBuster.

The main lead scoring models are:

• Intent-Based Model: Identify and score engagement signals, like website visits or email opens.

• Demographic & Firmographic Model: Score based on company size, job title, or revenue.

• Negative Scoring Model: Deduct points for leads engaging with competitors or showing low interest.

• Degradation Model: Assign negative points to leads for inactivity or lack of engagement.

Here are the steps for implementing lead scoring:

1. Analyze existing customers to uncover attributes and undertake lead enrichment.

2. Find intent signals your best customers use to base your lead-scoring system on.

3. Assign points for each action or inaction based on conversion rate data.

• We recommend using tools like PhantomBuster to streamline your process and enhance your lead data for automated lead enrichment and scoring.

Try PhantomBuster free for 14 days!

What is lead scoring?

Lead scoring is a methodology marketing and sales teams use to rank leads according to their perceived value or likelihood to convert.

This process involves assigning numerical scores to leads based on their behavior, demographic information, and level of engagement with a company's content or brand.

The higher the score, the more likely a lead will convert into a paying customer.

What is a lead scoring model?

A lead scoring model is a way of defining attributes that matter to your sales process.

For example, award points to a lead based on certain important actions, such as visiting your pricing page (10 points), downloading an eBook (5 points), or opening an email (2 points).

Manual vs. predictive lead scoring models

Manual lead scoring involves assigning points to leads based on predetermined criteria or researching a prospect in depth to assess their readiness to buy.

While it's a personalized approach, it's also admin-heavy, which can increase the risk of human error. Manual lead scoring can deliver a highly personalized approach if you have just a few contacts to manage.

However, it can be hard to implement if you have hundreds of contacts.

In contrast, predictive lead scoring uses AI to automate the scoring process.

Tools assign scores based on defined criteria and predictive models.

Given enough historical data, predictive scoring can also segment customers and predict key metrics like conversion rates and lifetime value.

Types of lead scoring models

You can use one or multiple scoring models based on what best fits your business. The recommended models are based on intent data, as these will help qualify leads instead of scoring them based on demographics only.

Here are the most used scoring models you should look into.

Intent-based leads scoring model

This model is focused on intent signals gathered from a mix of first-party data points (such as how they engage with your website, emails, etc.) and third-party points (such as their LinkedIn activity).

Some examples of intent-based activities can be:

• Liked a post from your company

• Attended an event in your industry

• Visited your pricing page 3 times in the past week

• Subscribed and read your newsletter

• How they stayed on each web page

Demographic and firmographic lead scoring model

Firmographic data does what it says: It gathers intelligence about a contact's company and sets scores based on different data.

Firmographic data points:

• Company Revenue

• Company technology stack

• Company sector

• Number of employees

Demographic data points:

• Job seniority

• Job title

• Job department

• Tenure at company

• Tenure in sector

Negative lead scoring model

A negative scoring model is about subtracting points based on unwanted activities, making a lead less qualified.

Hubspot CRM, which integrates many tools that help you build lead enrichment, describes how it processes this by removing points from the score. Once they don't meet the criteria, those points will be credited back.

Some examples of negative lead-scoring activities:

• Worked at a competitor business

• Has stopped engaging with your email newsletter

• Company revenue has fallen below the threshold

• Based in a country you do not serve

• Applies for a job role

Defining score criteria in HubSpot

Lead scoring degradation model

Using a lead scoring degradation model will help when you have stagnant leads.

This helps identify prospects unlikely to move through the sale process, marked by indicators of degradation of engagement.

This is often used alongside implicit scoring, so if a prospect gets 20 points for subscribing, they lose 20 when they unsubscribe. You can also use this for assigning point values when prospects:

• Stop opening newsletters or emails

• Download one content piece but never anymore

• Unfollow your business on LinkedIn

• Move into a new sector or industry

How to define relevant lead scoring criteria

We recommend a mix of methods to define relevant scoring criteria, including analyzing exciting customers, looking at data, and finding your best intent signals to build a new sales pipeline.

Let's take a closer look.

Analyze existing customers to uncover attributes

Say you want to start defining a lead scoring system based on demographic or firmographic data. The best way to begin is to look at all your best customers for demographic data.

• What is their seniority and title? Are they VPs or assistants?

• What sector are they in?

• Are your ideal customers a certain size or in a specific location?

• What tech stack do they use?

• What revenue is a good target market for you?

Understand the behavior of power users

While analyzing customer data, find your superstar customers.

Consider how they use your service or tools. This will indicate their pain points and needs, which you can use to base your lead scoring system.

• Do they use one feature repeatedly? Consider assigning points to new leads who use key features during a trial.

• What is their main role and job to be done? Find similar prospects with the same job title.

• Have they attended a recent event or webinar in the industry or with your business? Leads who also attended the event but are not your customers yet can be assigned a higher score.

Assign points based on conversion rate data

Examine the activities of your recent customers. Identify key actions, like form submissions or content downloads, that led to their purchase and assign higher points to these activities.

Work with your marketing teams to identify what has led to a high conversion rate and ensure you assign more weight to these activities.

Criteria to consider adding to your lead scoring model:

• They came through a referral.

• They visited your website after browsing your LinkedIn page or profile

• They follow your founder on LinkedIn

• They have previously worked with a competitor

• They downloaded a gated piece of content that asked for many details

• They have watched over two videos on-site over a certain period

How to automate lead scoring using tools

We recommend automating the lead-scoring process using a CRM or sales tools with AI functionality.

Here are the best ones to use.

HubSpot

HubSpot can automate lead scoring in multiple ways, including negative scoring and using behavioral and demographic data to calculate a lead score. You can also integrate lead scoring into your automated workflows.

How to use HubSpot for lead scoring:

1. Navigate to your HubSpot account, go to Settings > Properties > Custom store property and Add criteria

2. You can add Positive or Negative actions to add or remove points from the score.

   Defining score criteria in HubSpot

3. Save your scoring model, and HubSpot will automatically begin scoring leads based on your criteria. You can add up to 100 groups of criteria.

4. When a lead reaches a certain score threshold, HubSpot can automatically trigger actions such as sending a follow-up email, notifying a sales representative, or moving the lead to a specific stage in the sales pipeline.

PhantomBuster

PhantomBuster is a lead automation tool that helps you enrich your leads with the data you need for proper lead scoring. Data enrichment is the missing link for many sales teams when prospecting, and it helps identify relevant intent signals.

For example, you can use LinkedIn Profile Scraper to export LinkedIn data for your lead list in HubSpot and then use LinkedIn activity extractor to extract posts and other activity from a list of LinkedIn profiles.

Try PhantomBuster free for 14 days!

How to use PhantomBuster for lead enrichment:

1. Use LinkedIn Profile Scraper to export LinkedIn data for your lead list in HubSpot.

   

2. Use LinkedIn activity extractor to extract posts and other activity from a list of LinkedIn profiles.

   

3. Use LinkedIn Post Commenters and Liker extractor to identify who engaged with specific posts on social media.

   

How to use PhantomBuster to score leads:

• Use the AI LinkedIn profile enricher and customize a prompt to calculate a score based on your criteria. The AI will use available data that was previously scraped to analyze each contact on your list.

  

• Sync HubSpot and PhantomBuster so you have one source of truth.

  

Lavender.ai

Lavender is designed as an email coach to optimize outbound email campaigns through feedback and recommendations.

This tool integrates seamlessly with popular email marketing platforms to enhance lead nurturing and increase conversion rates.

Lavender focuses on scoring the effectiveness of email content at the outreach stage rather than scoring leads directly.

How to use Lavender for lead scoring:

1. Install Lavender on your email platform and integrate it with Gmail, HubSpot, Outlook, Outreach, or Salesloft.

2. Start composing your email. Lavender will provide real-time feedback on the email's structure, tone, and content.

3. Review Lavender's AI suggestions to tweak your email for better clarity and impact.

4. Send your email and check your results. While AI provides advanced predictive capabilities, there's a risk of over-relying on its scores without human oversight. You may miss nuanced insights that a human might catch, leading to potentially good leads being overlooked or lower-quality outreach, so build this into your plan.

   

Forwrd.ai

Forwrd.ai is a predictive lead scoring tool designed to identify sales-ready leads accurately. It uses AI and multiple data sources to score leads, accounts, and customers comprehensively.

Using advanced AI technology, Forwrd.ai uncovers patterns and trends that traditional methods might miss, offering a clearer picture of lead and account quality.

How to use Forwrd.ai for lead scoring:

1. Connect Forwrd.ai to your CRM to start analyzing your lead data.

   

2. Define what makes a lead sales-ready by setting criteria based on behavior, engagement, demographics, and more.

   

3. The AI algorithm will analyze all the data correlating with the success criteria and sort it by importance, providing a percentage score.

Brevo

Brevo can assign scores to leads based on prospect actions, such as email opens, link clicks, and form submissions. Then, it can create workflows to automatically update the lead score based on the contact's actions.

How to use Brevo for lead scoring:

1. Add a new attribute named 'SCORE' to track the lead scores. This attribute will be used in your lead-scoring workflows to update and track lead engagement.

   

2. When you create a new workflow, you can add criteria for updating contacts based on action. For example, set a trigger that adds points when a lead opens an email or clicks on a link.

   

Lead scoring best practices

How can you ensure success after identifying the tools and the best approach? Follow these lead scoring best practice tips.

Don't overdo it: sometimes you don't need a lead scoring model

Lead scoring isn't for every business; the cost may be too high if your sales cycle is short. Lead scoring models work best for products and services with a longer sales cycle where sales and marketing teams must prioritize high-quality leads.

Use multiple lead-scoring models

You don't have to pick just one approach. If your marketing team is focused on inbound marketing leads, they can still score qualified leads to uncover the sales-qualified ones. In contrast, your sales team can use a different model and lead scores based on different criteria.

By using multiple lead scoring models, you can tailor your approach to different audience segments and ensure that each lead is evaluated according to the most relevant criteria.

For example, marketing teams can prioritize leads showing high engagement with content, while sales teams might focus on leads demonstrating strong purchase intent.

This approach allows for a more comprehensive evaluation of lead quality, ensuring that marketing and sales efforts are aligned and optimized.

Additionally, using multiple models can provide valuable insights into which strategies are most effective for different types of leads, enabling continuous improvement of your lead-scoring process.

Adjust your lead scoring model periodically

Your prospects change roles, have budgets cut, or move in or out of the market, so keeping the pipeline fresh for your sales team is vital.

Analyze for stagnant leads; if lead volumes are low, you may want to adjust your thresholds. While lead quality is important, it's a balancing act that takes time.

Regularly reviewing and updating your lead scoring criteria is important to reflect these changes.

This involves monitoring market trends, customer feedback, and sales data to ensure your scoring models remain effective. Additionally, consider incorporating feedback from your sales and marketing teams to refine the scoring process continuously and better define what a sales qualified lead scoring model should include.

By doing so, you can ensure that your lead scoring system remains agile and responsive to the market's dynamic nature. This will ultimately lead to more effective prioritization of high-quality leads.

Conclusion

A lead scoring system can help you prioritize leads and optimize the sales process. Since no one model fits all businesses, we recommend you build your own. Start small with just a few criteria and improve it as you go.

For a quick start, you can use PhantomBuster's AI to score your leads. You can try it free for 14 days.

Try PhantomBuster free for 14 days!