How To Use HubSpot Lead Scoring to Qualify Contacts, Companies & Deals

Before I decided to focus exclusively on HubSpot lead scoring and consulting, I worked as an in-house digital marketing manager. One time my employer was generous enough to send me and the lead sales rep to a sales and marketing alignment workshop. After a day-and-a-half of mostly forgettable lessons, the seminar leader—a salesperson by trade—shared one of the worst pieces of business advice I’ve ever heard.

‘You should have your marketing person call and qualify every inbound lead before handing it over.’

At the time, I couldn’t believe any sales rep would want me—someone with no experience or enthusiasm for making sales calls—to be the first point of contact for a new prospect. Now, with the benefit of a few years I’ve come to understand that was a byproduct of the fact that, in many companies, sales teams simply don’t trust leads generated by marketing. There are a lot of reasons for this—lack of understanding what qualifies a lead to be a MQL (marketing qualified lead) or and SQL (sales qualified lead), too many leads coming in, etc— but it’s often because there’s no easy way to tell which leads are worth pursuing.

That’s where a lead scoring tool comes in.

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What is Lead Scoring?

Lead scoring is an automated process for ranking leads in your CRM (customer relationship management software) based on demographic information those leads provided while converting, information your team already knows about those leads and the interactions that lead has had with your website and other marketing assets. There are many methods for calculating a score, but the end result is a single number meant to summarize the overall quality of a lead or prospect.

It’s important to recognize that lead scoring in CRM is related to but separate from lead ranking. Generally, lead ranking involves assigning a grade (A, B, C, etc.) to a lead based on strictly demographic data like industry, annual revenue or headcount, then prioritizing those leads based on that grade.

For example, you might assign a lead with a lead score or 100+ a grade of A. The score allows for more granularity than the ranking, but the ranking lets users—sales or marketing—focus on the bigger picture.

How is a HubSpot Lead Score Calculated?

Lead scoring is a native feature of HubSpot’s marketing automation platform. By default there will be a HubSpot Score property in your HubSpot account when it’s activated but it won’t start calculating until you configure it.

Configuring the HubSpot Score property means providing a series of positive and negative attributes that assign points according to rules you set up based on the data in contact properties. For example, here are a few common criteria I’ll recommend when setting up lead scoring for a client:

• Number of session in greater than 2: +5 points
• Number of emails clicked is greater than 1: +10 points
• Company size is greater than 100: + 10 points
• Number of forms submitted is greater than 1: +25 points
• Job title contains CEO: +25 points
• Time last seen is greater than 30 days: -10 points

In the example above, a VP of Marketing who submitted two forms over three visits to the website more than a month ago would have a HubSpot lead score of 20. Then, it would be up to you and your team to decide whether a score of 20 points warrants immediate follow-up, enrollment in nurture workflow or no action.

When you’re building scoring criteria in HubSpot, you can use up to 100 different criteria to calculate your score and the score will be calculated for every contact record in your database. Your goal should always be to ensure someone who matches your ideal customer profile with a meaningful submission gets scored highly enough to count as an SQL.

Beyond the basic setup there are a few other key things to keep in mind when it comes to planning your lead scoring implementation.

Unexpected Paths to Qualification 

You’ll likely find that most people reach your score totals in the ways you’d expect—submitting key forms, attending events, etc.—but people will find ways to reach your target scores in ways you didn’t expect. That’s not a problem, per se, but it does mean your team needs to understand how to determine a lead’s path to qualification.

For example, if you allocate five points every time someone reads a blog post, it’s possible that some enthusiastic newsletter subscribers could end up with the same score as a CEO that requested a demo.

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Retroactive Scoring

A HubSpot Score isn’t a static number. It’s constantly recalculating for every contact record as they interact with your organization. If you make any changes to the scoring criteria it will recalculate the scores for the entire database, so you do have the flexibility to edit over time.

That means when you add a new criteria to your lead scoring it will change the score for anyone that meets that criteria, not just those moving forward. So, if you plan to add a new criteria, be aware that you’ll see a jump in points for the whole database.

It’s also important to remember that those recalculated scores will trigger any automations based on HubSpot Score, so you might want to pause those automations before editing scoring criteria.

Cookie Data Required

Organizations typically want website interactions—page views, time last visited, etc.—to contribute to the lead score, which makes perfect sense. However, they often don’t realize HubSpot can only track website interactions for contact records which have submitted a form at some point (and matched their browser cookie to a specific contact record in HubSpot). That means any Contacts imported or added via an integration aren’t eligible to have their website activity tracked and factored into the HubSpot score.

This often causes confusion when a user knows a Contact has visited the website but doesn't see those points reflected in the lead score. The only way to resolve this is by driving as many Contacts as possible to website conversions and by educating your users.

Multiple Scores

Every HubSpot account has a HubSpot Score property by default, but it’s absolutely possible to create additional score fields. Sometimes organizations use this feature to track separate scores for different products or lines of business. It can be complicated to determine how multiple scores interact with lifecycle stages and pipelines, but it’s not an insurmountable barrier and it can add a lot of granularity to your understanding of a Contact’s journey.

What are the Benefits of Lead Scoring?

Now that we understand how a lead score is determined and some of the key things to consider, let’s talk about why it’s worth the effort of setting it up in the first place.

Better Marketing + Sales Alignment

Like I said in the introduction, a lack of understanding about why, when and how leads are being handed off to sales is a root cause of why sales teams don’t prioritize leads generated by marketing efforts. A lead score is essentially a shorthand sales and marketing develop in collaboration so that everybody knows the bar a lead needs to clear before being handed over.

This starts when determining what an ideal customer looks like, what actions should be scored and how much those activities should be worth. Sales and marketing should meet to review buyer personas, set the value of different scoring attributes and agree how many points are required for someone to become an MQL or SQL.

Is a newsletter signup more valuable than pricing page view? How many emails should someone open before we consider them a sales qualified lead? Both teams will have opinions on these questions and you’d be amazed by how much clarity the exercise of planning lead scoring can boost alignment.

Increased Conversions

Ultimately all the good vibes in the world won’t make a business case for lead scoring if it doesn’t have a positive effect on your conversion rate. Luckily, it almost certainly will but it’s worth understanding what that impact will look like.

The truth is your team probably doesn’t need a lead score to tell them to engage with folks that request demos, or CEOs that sign up for webinars. Where lead scoring excels is capturing those slow burn prospects lacking impressive job titles or big company recognition. After all, a middle manager that signed up for the newsletter three months ago and has read every article you sent along can still be a quality lead, but can be easily missed without lead scoring to track that history of micro conversions.

Simpler Automation

Automation is key to a scalable sales and marketing system but it’s almost impossible to scale a system without lead scoring—or something like it—in place. Without a single guiding light to reference in processes and workflows you end up needing to account for individual forms, email campaigns and landing pages when reporting on leads generated or handed over to sales.

However, if you can set up a robust lead scoring system you’ll find that the activities of individual campaigns naturally get picked up by your lead scoring model, so you can focus your automation around your lead score instead of lists of form submissions or specific email links. Whether that automation is to route a lead to the right team member or to start a nurture workflow for someone that hasn’t quite reached that point.

Lead Scoring Methods

Manual Lead Scoring

This is essentially the same process we’ve been talking about above, but performed manually by a member of your team. This might be necessary if you don’t have a marketing automation platform that can calculate a score on your behalf.

Some companies use Logistic Regression Lead Scoring, which is essentially creating a formula in a spreadsheet or other application that can calculate a lead score based on the same criteria HubSpot would use. It’s more scalable than doing the scoring manually and it might even allow you to do calculations HubSpot can’t, but it’s rarely worth the effort for any organization with a marketing automation platform. 

Predictive Lead Scoring

Predictive lead scoring uses machine-learning to identify which leads in your account are most likely to close. This calculation is based on the data from your account, so you’ll be training your predictive lead scoring model simply by working the leads you’re generating. HubSpot will rank each Contact in the Likelihood to close and Contact priority fields.

The downside to predictive lead scoring is that it requires a lot of data to produce an accurate model. I’ve yet to work with a B2B organization that had a lead volume high enough to produce a predictive lead score they felt comfortable using.

Fit-Based and Activity-Based

These models aren’t strictly lead scoring, but they are closely related. They are frameworks that require a lead to meet certain criteria (i.e. be located in a geography you serve, not have an @gmail.com email address, etc.) or have completed certain actions before being considered a lead.

This is relevant because your scoring criteria will continue adding points for someone that can never become a lead. You can add negative scores for certain criteria, but it is possible for a lead to out-engage certain negative criteria. So, many organizations will use HubSpot Lifecycle Stage, or another lead ranking field in conjunction with a lead score.

So, in order to be flagged as a lead rank that warrants follow-up, a lead will need to meet the target lead score and fit the criteria required to be considered a lead.

Setting a High Score

Lead scoring is simultaneously an exercise that will boost collaboration across sales and marketing teams and a sales enablement best practice that will drive increased conversions and smoother customer journeys. Getting it right involves a lot of work—from defining your scoring criteria to deciding what constitutes a qualified lead—but it’s work that will drive results as soon as it’s implemented.

Once you’ve got the basics laid out, you’ll need to revisit the lead scoring criteria regularly, since new pages, new channels and new definitions of what constitutes a qualified lead will naturally emerge as your processes change and you collect feedback from both users and prospects.

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