In today’s competitive business landscape, marketing and sales teams are under immense pressure to deliver results. A valuable tool in this effort is lead scoring—a process that, when done right, can significantly increase the likelihood of closing new business. However, many companies struggle with one big issue: their sales teams often ignore the lead scores provided by marketing. So, why is that? How can you make your lead scores more effective in driving sales and ensure they are helpful across your organization? This guide will walk you through common pitfalls of lead scoring and offer practical solutions to bridge the gap between your marketing and sales teams.
It’s a scenario that plays out in countless companies. Marketing works hard to create what they believe is a robust lead scoring system, only to have sales shrug it off—or worse, actively dismiss it. Why does this happen?
First, lead scores are often designed in isolation by the marketing team. Without input from sales, these scores may not reflect the reality of what makes a lead valuable. If sales doesn’t see the score as helpful, they won’t use it.
Second, many lead scoring models focus solely on generating Marketing Qualified Leads (MQLs). While MQLs may look impressive on paper, if your lead scores are not based on accurate parameters, they are unlikely to translate into sales. A scoring system that hands off leads without clearly justifying why they should be considered qualified is unlikely to gain acceptance from sales teams.
Additionally, lead scores can become overly complex or arbitrary over time. The score loses credibility if no one on the sales team can explain why a lead has a particular score. And if the criteria for scoring aren’t based on quantifiable data but rather on gut feelings or outdated assumptions, the score becomes even less valuable.
In short, if your sales team ignores lead scores, it’s likely because they don’t see their value. But don’t worry—there are ways to fix this and increase alignment between your sales and marketing teams.
Before diving into the exciting task of building and implementing your lead scoring model, it’s crucial to take a step back and involve your sales team in the process. Skipping this step might seem tempting, but it’s a sure way to set your lead scoring system up for failure in the long run.
Including sales in the scoping phase of your lead scoring project offers several key benefits. First and foremost, it fosters adoption. When sales is involved in the discussions and decision-making process, they’re far more likely to trust and use the lead scores. Instead of feeling like they’re being handed a marketing-only metric, they’ll see the score as a tool that can genuinely help them prioritize leads and close deals.
Many sales reps quickly dismiss lead scores because they don’t trust them. They see them as arbitrary numbers that don’t reflect the actual value of a lead. This often happens when the lead scoring process is done behind closed doors, without input from the sales team. By involving sales from the start, you can increase their trust in the process and, as a result, boost the usefulness and adoption of your lead scores.
Another significant benefit of including sales in the lead scoring process is that it can help improve the efficiency of your sales team. Salespeople always look for ways to streamline their workflow and close deals faster. A well-designed lead score, built with input from sales, can help them do just that. For example, adding additional data layers—like demographic indicators—can help sales reps prioritize leads more effectively, saving time and focusing their efforts on the most promising opportunities.
The final and most important reason to include sales in your lead scoring process is to increase sales. A lead score that sales believes in and uses will lead to more deals closed. By ensuring sales is involved in the discussion, you can ensure that the lead scoring model aligns with what drives your business's success.
But collaboration between marketing and sales isn’t always easy. These teams often have different priorities, and bringing them together can be challenging. That’s why it’s essential to build a team of decision-makers who see the value in collaboration and can bring different perspectives to the table. Include people from various levels of seniority, set clear ground rules for discussions, and ensure that data, not just gut feelings, support all ideas.
It’s also important to set a meeting schedule and stick to it during the project's discovery phase. Building a lead scoring model isn’t a one-time task—it requires ongoing collaboration, testing, and revision. Establishing a regular meeting cadence will keep the process moving forward and help you continually refine your lead score to ensure it remains effective.
Finally, ensure end users—like SDRs and Account Executives—are involved in the process. After all, they’ll be using the lead scores daily, and their feedback is invaluable in creating a lead scoring process that truly works for your entire organization.
By involving sales in the lead scoring process from the beginning, you’ll build a process that’s not only more effective but also more widely adopted across your company. This collaboration between marketing and sales can be the key to unlocking better results and a smoother lead-to-customer journey.
Many teams default to a simple numerical score when it comes to lead scoring. This approach can be effective for small teams or when you’re just starting out. However, as your processes become more complex and the need for more detailed information grows, you may find that a single numerical score is too limited. In this section, we’ll explore different lead scoring models and how they can be used to better align your scoring system with your organization’s needs.
Choosing the right lead scoring model depends on your specific goals and processes. Some models work well independently, while others can be combined to offer a more nuanced view of your leads. Selecting the appropriate model—or combination of models—can be the difference between a lead score actively used by your sales team and one that gets ignored.
This document provides an overview of four types of lead scoring models: Numerical, Temperature, Grade, and Tiering. Each has its strengths and weaknesses, and understanding these will help you decide which model to implement.
The numerical model is the most common and familiar. It assigns points to contacts based on their activities or demographics, and the score builds over time. This model is quick to implement and easy to understand. While this model can be quickly built using nothing but HubSpot’s lead scoring tool, it often lacks context and can be challenging to interpret. For example, a contact may accumulate points through low-quality activities, leading to a misleading score. For instance, is a lead actually qualified, or did they simply hit the threshold from 100 page views? This model is often used to trigger MQLs at a specific point threshold, such as 50 or 100 points, but may not offer much utility beyond that.
The temperature model is less common but can be helpful, especially in shorter sales cycles. It translates activity into a temperature—hot, warm, or cold—making it easy for sales teams to prioritize leads. This model is simple to implement and understand, but it doesn’t provide much detailed data, similar to the numerical model. Additionally, it focuses on activity rather than demographics, which can lead to static scores over longer sales cycles.
The grade model is particularly effective for demographic scoring but can also be applied to activity scoring. It’s based on the familiar A—F grading scale, making it easy for most users to understand. Grades can also be nuanced with pluses and minuses, providing more detailed insights. This model is beneficial for evaluating contacts and companies, offering a more precise picture than a simple numerical score.
The tiering model is often associated with account-based marketing (ABM). It ranks companies based on how closely they fit your Ideal Customer Profile (ICP). While this model works well for company-level scoring, it can be combined with contact-level activity to provide a fuller engagement picture. Tiering requires substantial data to be effective, making it more suitable for organizations with complex sales processes.
While each model can be effective independently, they often work best when combined. For example, combining a grade with a numerical score can give you insights into both the quality of the lead and their level of engagement. However, combining models does add complexity and requires ongoing maintenance. By combining models, you can unlock actionable insights across your organization that can significantly improve your lead management process and lead to increased sales.
In the next section, we will explore how different model combinations work and how to decide if a single model or a combination is right for your organization.
Now that you’re familiar with the different lead scoring models, it's time to dive into what to score. There are countless ways to score a lead, but focusing on the right areas is crucial for effective lead management. This section will explore the three primary areas to focus on when building your lead scoring model: Activity/Behavior, Demographic/Firmographic/Fit, and Time.
Activity and behavior scoring is the most straightforward and commonly used. It tracks what the contact does online and offline and assigns scores based on these actions. These activities often include website visits, email engagement, social media interactions, event attendance, and more. In a CRM like HubSpot, many activities are automatically tracked and can be scored accordingly.
Remember to include negative behavior scoring as well. Not all activities indicate a potential sale. For example, a contact visiting your careers page multiple times might indicate they’re looking for a job, not your product. Adding negative scoring can help you more easily disqualify leads, saving your sales team valuable time.
Hubspot’s new model allows for removing contacts from scoring entirely based on a suppression list. Using a suppression list allows you to remove contacts from scoring entirely so they do not move to qualification. For example, a common practice is to give someone who unsubscribes a high negative point value so they would not convert. Instead of working out the math required to ensure they don’t convert, simply add them to a suppression list until they meet your criteria to be viable.
Demographic and firmographic scoring help you determine how well a contact or company fits your Ideal Customer Profile (ICP). Compared to activity-based scoring, these data points are typically more stable and fixed.
Using BANT (Budget, Authority, Need, Timeline) criteria can help provide a basic structure for demographic scoring. However, make sure your scoring is data-driven. Salespeople’s perceptions may skew the scoring, so rely on objective data to build a trustworthy model.
Negative demographic scoring is also important. Not every lead is a good fit; identifying these before the scoring threshold is crossed can save time and resources. For example, scoring a contact negatively if they are in an industry outside your ICP ensures they won’t be prioritized.
Time plays a crucial role in lead scoring, often in the form of decay. Time decay models reduce a lead’s score over time if there’s no activity, ensuring that older, less engaged leads don’t get passed to sales unnecessarily. Decay periods can vary—some companies use a 30, 60, or 90-day model.
You can also use time as a positive factor by positively scoring shorter times between interactions. This shows that a lead is actively engaging and should be prioritized.
Keep your activity and demographic scores separate. While combining them may seem convenient, it can lead to inflated scores and push contacts through the buyer’s journey too quickly. Remember, activity scores show how much a contact wants you, while demographic scores indicate how much you want them.
Your lead scoring model should be honest, data-driven, and valuable. It should build trust between your marketing and sales teams and ensure only qualified leads are passed along. By focusing on activity/behavior, demographics/fit, and time, you can create a robust lead scoring system that helps your organization identify and convert the right customers.
When creating a lead scoring model, following best practices is essential to ensure the process is effective, efficient, and easy to refine. Here, we’ll discuss several key best practices that will help you build a reliable lead scoring system that drives results.
The first best practice is to build your lead scores using proven data rather than aspirational information. Proven data provides a solid foundation, while aspirational metrics can lead to inconsistencies and misaligned expectations.
For example, if you aspire to target Fortune 500 companies and assign them a high score, but your team lacks experience closing deals with them, you may pass leads to sales they’ll struggle to convert. While it’s fine to aspire to reach these companies, don’t let that aspiration influence your scoring until you have data that reflects success.
Suppose a conscious effort to work those kinds of opportunities is a business priority. In that case, the sales team should be clear that scoring may be inflated due to business requirements. The score's reliability needs to be protected for trust to remain.
Avoid scoring based on aspirations that aren’t backed by proven success. Otherwise, you risk converting bad leads and misallocating resources.
Another beneficial best practice is to identify common traits among your successful customers. This may uncover interesting correlations in demographics or behaviors that aren’t immediately obvious.
For example, you might discover that many of your primary contacts hold a master’s degree in accounting. While this doesn’t guarantee success, it’s worth considering as a scoring factor if the data supports it.
However, remember that correlation does not always equal causation. Just because 20% of your clients prefer a specific type of soda doesn’t mean it’s a reliable indicator of a good customer. It’s important to carefully select which data points you incorporate into your scoring model.
Look for meaningful commonalities, but be cautious not to overemphasize irrelevant correlations.
Historical data is a powerful tool for optimizing your lead scoring model. While marketing often focuses on lead volume, what ultimately matters is revenue and closed deals. Comparing lead volume to historical can help you prioritize leads most likely to close.
For example, you might generate a high volume of leads from California, but if your close rate in that state is low, you might reconsider how you score leads from that region. Conversely, if a smaller state like Alabama has a high close rate, it might deserve a higher score.
Score based on your ultimate goal—close rate, not only lead volume.
Simplicity is key to building a lead scoring model that people will actually use. The more complicated your scoring system, the harder it becomes to understand, update, and deploy.
For example, suppose you score webpage visits but add overly complex criteria (e.g., visits a product page more than X times but no more than Y times within a specific date range). In that case, it may confuse future users, even if your reasoning is sound.
Keep your scoring model as basic and straightforward as possible. A simple model is easier to understand, use, and refine.
The most important best practice is to ensure that your score is helpful. A poorly understood or used scoring model will not add value to your organization.
Here’s how to ensure your score is useful:
A useful score is a score that gets used. When it’s easy to understand and deploy, it will become a valuable asset for both your marketing and sales teams, leading to higher conversions and greater efficiency.
By following these best practices, you’ll create a lead scoring model that is reliable, effective, and adaptable as your business evolves.
Now that we have covered the background of scoring models, selecting the right one, and scoping out the process, it's time to build your lead scoring model.
The first step is to implement your model. Each model has a specific build process. Depending on your choice—whether it’s a single property, numerical, temperature, grade, or tier model—you must ensure you build the right properties and workflows to make it functional. The build will naturally be more intricate if you’ve opted for a more complex model, like a combination of score plus score, grade plus temperature, or a co-dynamic approach.
Before you start building, it’s critical to document everything related to your scoring model. This document should live outside HubSpot and serve as a living guide for the entire process. It will be beneficial when making updates after the initial build.
Each model requires different sets of properties. For example, a numerical model needs a HubSpot score field, while a temperature model requires a custom scoring property that translates temperature from a HubSpot scoring property. In more advanced setups, like the co-dynamic model, you’ll need custom and counter properties to limit the frequency of scoring activities. HubSpot even allows for AI-powered scores using their new Breeze AI technology.
Once your properties are in place, you need to build workflows to connect everything. This might involve translating scores into grades or temperatures for simpler models like numerical or temperature-based scores. For more complex models like the co-dynamic approach, you will need to create workflows for every activity, manage decay over time, and combine demographic and activity scores into a final lead score.
As you build your model, test everything thoroughly. Check that the workflows trigger as expected and that the scores align with your criteria. Refining this process might involve tweaking properties, updating workflows, or revisiting your documentation to ensure accuracy.
By now, you should clearly understand the importance of choosing the right model, documenting your processes, and constructing the necessary properties and workflows.
Your final steps involve training your team to use the new scoring system and ensuring they understand its benefits and functionality. Proper training will make all the difference in helping your team adopt and leverage this powerful tool effectively.
With your lead scoring model in place, you can expect more targeted marketing, more effective sales efforts, and, ultimately, a more streamlined approach to managing your leads. For help building a lead scoring system and training your team, set up a consultation with The Pros!
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