While those just starting out on their inbound marketing or HubSpot journey may be focused on just converting leads, what do you do when you start getting leads and want to hand them off to sales? You surely can't pass every single lead off to sales (or they may lose their minds). One of the most important things for a sales team is to know who is ready to close. Those are the most valuable conversations that a salesperson can have. But how do you know who is ready to buy and who has maybe just shown a small amount of interest? Enter lead scoring.
Lead scoring is the process of assigning a value to each of your leads. That score is then used to prioritize leads so that your marketing team knows who is not a fit, who still needs to be nurtured, and who is ready to be passed off to sales. From a sales team's perspective, they can use the score to dive even deeper into the leads that are passed to them and identify who is the most likely and most ready to close quickly. Those are their hottest leads and the leads that they should be prioritizing.
See, not all leads are created equal. Through lead scoring, you can start to understand who is really hot and who just downloaded a piece of content, never to be heard from again.
While there is no silver bullet or a straight forward answer to how to setup lead scoring, there are some best practices to get you started.
First, understanding the purpose of your lead scoring program is important. It should be that you are using lead scoring to determine who is most likely to close and become a customer. If that is the case, then you need to work backwards. Think about the actions that are most likely to lead someone to a purchase. What triggers signal to your team that the prospect is ready to buy?
Whenever possible, this should be backed by data. Starting with your lead:customer conversion rate. This is the percentage of leads that become customers. Then you should examine those leads that have become customers. This will help you to identify which attributes or actions make someone more likely to become a customer. You should be able to spot trends. These can be things like their original source, business size, industry, and behavioral data like page views, email opens, and even social media engagement. Then once you have that information, you'll want to determine the close rate of leads that have each attribute to determine how many points to award in your lead scoring program.
If you're just starting out and don't have a ton of hard data to reference, you can probably make some educated guesses as to which actions or attributes are most valuable to your business and to moving a lead through your funnel. Start there. And lean especially hard on your sales team for their expertise. They are the ones on the front lines with customers. They know what questions are coming up and they typically understand which pieces of marketing content help in their sales process.
Within HubSpot, depending on which hub you have, you may have manual lead scoring or both manual and predictive lead scoring. Let's dive into each:
Manual lead scoring is available in Marketing Hub Professional and above as well as Sales Hub Professional and above in HubSpot.
Manual lead scoring is the process of assigning specific values to actions or attributes of a lead in order to determine fit and funnel stage. This is the most common form of lead scoring, but it is also a manual process that should be kept up with regularly. It can't be a set it and forget it kind of thing. Manual lead scoring consists of both positive and negative attributes that are used to determine a single score which is used to determine fit and readiness for sales.
Predictive lead scoring is available in Marketing Hub Enterprise and Sales Hub Enterprise within HubSpot.
Predictive lead scoring is the process of leveraging machine learning and artificial intelligence to determine your best leads so that you don't have to come up with your own lead scoring program. It also learns as you update information in the CRM. As someone closes, the lead scoring program learns what pieces of content that person consumed, analyzes their demographic data, and this all helps to inform future scores. With predictive lead scoring, you don't need to add attributes or manage them regularly.
This model will look at what your closed customers had in common as well as what the leads that didn't close have in common to develop your scores.
The most common attributes added to a manual lead scoring program are positive attributes. These are positive signals that a a lead is moving closer to the bottom of the funnel. These are steps or details that someone has that makes them more likely to become a customer.
These are the good things. The things that we want to see. They can be things like email opens, viewing your pricing page, returning to your website, engaging with your brand on social media, filling out a request a demo form, and a million other things.
For these attributes, you'll assign a positive value which will raise their overall HubSpot Score indicating a move closer to the bottom of your sales funnel.
Negative attributes are often forgotten. It makes sense - it's human nature to only want to see the good things. We want to see a lead opening our emails, viewing important pages, and downloading content. We don't want to see them leaving emails unopened, ignoring our content, or unsubscribing from our messages.
But - your lead scoring program can't be one sided. Leads don't always move in one direction. It's not that simple. Leads will take steps forward and they'll also take steps backward and both should be accounted for.
Negative attributes are where you will take points away from a lead because of actions, non-actions, and demographic information. This helps to keep your manual lead scoring program accurate.
Think about it - if you gave a lead 10 points for opening your last marketing email, 30 points because they've viewed the pricing page in the last 7 days, and another 15 points for coming back to the website at least twice in the last month, you may look at that lead and think, hey this person is a hot lead and should be passed off to sales. They have 55 points!
But what if when they opened your last email, they actually unsubscribed? Probably not as high of a priority lead now, right? That's why you have to account for those backward steps.
This will all depend on your business model, but in general companies typically work on a 0-100 point model with 0 being either considered out of the funnel or very top of the funnel and 100 being ready to close.
When determining how many points (or negative points) an attribute is worth, you should be considering the impact of that action. Again, if you have real data, lean into it. If you don't, use your best judgement. What are the demographics that make someone perfect for your business, what are the actions that signal that someone is very interested, what are the non-actions that signal that someone may not be as interested as we thought?
Once you have those attributes, then you should prioritize them. The more impact, the higher the number of points. For negative attributes, the worse the action, the more points you should take away.
And remember - as you start to accumulate data, use it. Start to spot trends that inform whether someone is a good or a bad lead and update your positive and negative attributes.
Once you have set your manual lead scoring program up, it'll work automatically. Every single contact will automatically get a HubSpot Score. This property is found in the Contact Information group for each contact and is titled, "HubSpot score."
For predictive lead scoring, this property is also in the Contact Information group for each contact and is titled, "Predictive Lead Score."
You can also find these attributes by going to the gear icon in the top right > clicking on Properties in the left sidebar > then searching "score" in the search box.
So once you have attributes created and a lead scoring program running - you're done, right? Well not quite.
If I told you a contact had a HubSpot score of 62 - is that good? Is that bad? Is it ready for a sales handoff? You just don't know without establishing what the scores actually mean.
The next step is to set boundaries that signal where someone is in the funnel. This should be based on the values that you setup earlier, but here is a general idea of what it could look like using a 0-100 model:
With predictive lead scoring, you don't ever have to worry about updating your attributes or your program. Your only worry should be keeping your CRM up to date so that it can do its job accurately. If you don't update your CRM, the predictive lead scoring model will make false assumptions.
With manual lead scoring, you need to continuously monitor and adjust both your positive and negative attributes. These should be updated regularly as you gain more data, your sales team has more conversations, and your marketing team rolls out new content. Please don't just set it and forget it!