What Is Lead Scoring? [Models & Best Practices]
Successful marketing teams can generate hundreds of leads every week. Your sales reps have to prioritize who to contact first and decide who not to contact at all.
The solution is lead scoring—
It takes the guesswork out of following up on leads. Your marketing team knows when to hand off the leads to the sales. And sales can focus on closing deals.
In this article, we will:
- Explain the lead scoring methodology
- Mention predictive lead scoring & software
- Give examples of lead scoring models
- Tips for improving lead quality
What is lead scoring?
Lead scoring is a process of ranking leads based on different attributes and data points to assess their readiness to buy. Using a predetermined scale helps identify which leads are valuable to your business and increase conversion rates.
You can build models to score leads based on the following criteria:
- Intent data
- Firmographic data
- Prospect behavioral data
- Engagement with your organization
- Lead source
A lead scoring system (or model) lets you attribute point values to prospective buyers. Once they accumulate a set number of points, they become qualified leads. It means they are likely to make a purchase and sales reps can contact them. Those who rank the highest on the scale should be contacted first.
I know what you’re thinking—
The lead scoring definition sounds great but how to work out the lead score?
Well, every organization does it differently. Generally, you have to assess the attributes of prospects who became customers and those who did not. Then, you can weigh different attributes to decide which of them describes good leads for your business.
Here are some examples of lead scores for different attributes:
- +5 points for visiting the pricing page
- -10 points for visiting the careers page
- +5 for joining a webinar or downloading a white paper
- +10 for opening a promotional email
- +10 when a prospect is a middle manager and +25 if they are a decision-maker in a company
Why is lead scoring important?
Gleanster Research found that only 25% of leads you generate are legitimate and have the potential to convert. And from those legitimate leads, about 79% won’t convert into sales. It leaves you with five customers out of 100 leads. That sucks.
Lead scoring is important for sales and marketing because it helps identify where the leads are in the sales process. It is crucial in determining whether the lead should continue to be nurtured (MQL) or handed over to the sales (SQL).
The lead scoring methodology is especially important for longer sales cycles and high price-tag services that require direct interaction with prospects.
On one hand, the purpose of lead scoring is to save time, lower lead generation costs, and improve alignment between marketing and sales. On the other hand, lead scoring means a better experience for customers because they are approached with the right type of messaging at every stage of the sales funnel.
What to consider before implementing scoring models?
If your sales cycle is fairly short and you can easily close leads, introducing a lead scoring process might be an overkill for your business model. Before you invest in lead scoring, make sure you capture relevant data points to differentiate leads. For example, your qualifying criteria must correspond to the fields on lead capture forms.
Another point to consider is whether you have enough leads to rank. If leads are slim, it’s better to spend more time on lead generation. Likewise, if sales development reps are busy chasing leads and conversion rates are good, then lead scoring might not be for you. But if you have a lot of leads coming in and sales reps complain about their poor quality or low conversions is necessary.
What is predictive scoring?
Finding patterns and fine-tuning B2B lead scoring gets complicated if you have more than a couple of contacts in your database. The good news is that you can build your sales lead scoring models into CRM software to get accurate results.
Marketing tools use predictive lead scoring to automate the process thanks to machine learning and AI. Algorithms make reviewing B2B data much faster and eliminate the possibility of human error. It saves sales development reps a lot of hassle and helps them align with marketing teams better.
Predictive scoring software also segments customers and helps forecast conversion rates, customer lifetime value, and other key metrics if they have enough historical data to analyze.
Predictive scoring has its limitations as well—
Over-relying on predictive lead scoring may prevent your business from branching out to new opportunities. For example, it may not recognize relevant leads without prior knowledge of them.
How to pick lead scoring software?
Establishing lead scoring models is easier than keeping track of lead scores manually. Many popular CRMs, like HubSpot and sales automation tools, include lead scoring features. So before searching for a lead scoring tool, look into the CRM that you’re currently using.
When choosing lead scoring tools, look for basic options like pipeline and opportunity management, reporting, email marketing, and syncing contacts. You can also check advanced options like tracking, routing, and prediction features.
Tip! Some of the popular lead scoring tools include HubSpot, Salesforce or ActiveCampaign.
What lead scoring models are there?
You can score leads based on various types of data you capture about potential customers. Here are some examples of developing scoring models to rank potential customers.
1. Purchase intent model
Intent data helps you gauge a person's conversion probability. It looks into prospects' web activity and informs you if they are actively considering your product. Intent data can be collected from various digital sources (first-party and third-party) to pinpoint when a prospect enters a buying journey. Lead scoring models based on intent data let you get in front of potential clients early.
Cognism Intent Data helps you target key decision-makers and reduce manual and budget resource needs. Gartner’s 2021 report intent signals from potential B2B buyers improve marketing lead scoring. Watch the video explainer below to learn more.
2. Firmographic and/or demographic model
B2B lead scoring depends on firmographic data as much as the B2C scoring process on demographic information. You can create lead forms to elicit relevant information and assign points to leads that fit your ideal customer profile or buyer persona.
Here’s a simple example of lead scoring for B2B—
Tip! You can also subtract points from people who haven’t got the characteristics you need.
3. Online behavioral model
You can also assign scores for actions and activities that leads perform on your website or online. Lead scoring software, like Salesforce, uses algorithms to calculate lead rank. It automatically creates and updates the score by assigning numerical values to different actions, like visiting the pricing page or filling in a form. You can determine which activities or types of content on your blog have the highest value to your business.
Tip! Salesforce lets you use various criteria to set up a lead grading system, including a lead’s location, industry, job title, and company size.
4. Engagement models
You can gauge how interested leads are in your product or service by scoring them based on their engagement with your brand. Lead scoring in email marketing means tracking open and click-through rates. You can even get more granular if you assign different scores for various types of emails. For example, a higher score for opening a promo email.
Similarly, it’s possible to track interactions (and their frequency) on your social media channels and score leads on likes, comments, or shares. You can decide that once leads accumulate a number of points (e.g. open four emails), it’s time to hand them over to the sales.
5. Negative scoring attributes
Some lead interactions indicate little or declining interest in your brand. Negative lead scoring is a way to excuse non-prospects from the process or adjust their rank. For example:
- Unsubscribing from your email list
- Browsing your career page
- Typing ‘Student’ in the job title
- Spam submission
- Contact is a competitor
- Internal team member
- Friend or relative
All of those people might open your emails or browse your website for different reasons, e.g. academic. You should simply not pursue them. You can even subtract a thousand points if the contact email address includes our partner or competitor company. This way, even though they will still take positive actions, they will be forced out of the sales lead scoring system.
Tip! Lead scoring software, such as HubSpot continually updates the scores based on criteria set up in Negative and Positive sections.
Lead scoring best practices to improve lead quality
Lead scoring doesn’t have to be difficult. Here are some top lead scoring tips to identify hot leads.
1. Define sales qualified lead criteria
First things first—
You need to decide what factors contribute to lead conversion. Or what attributes suggest it’s better to disqualify leads? In B2B lead scoring, you may prioritize company size and budget, while local companies will focus on geographical data.
2. Consider the conversion process
You can conclude how close a lead is to conversion if you analyze their behavior. For example, if your sales-qualified leads usually subscribe to a newsletter before joining a sales demo, you’ll know when to make a discovery call.
3. Assign points to every action and attribute
Assign higher value points to actions closer to conversion. Actions performed by new leads, like visiting a homepage or signing up for a newsletter shouldn’t weigh as much as contacting the sales team about pricing.
Leads can accumulate points for different actions so think of what a minimum qualification score is before reaching out to your contacts.
4. Evaluate and adjust scores
Don’t just set and forget your lead scoring process. Customer journey is likely to change over time which means you need to adjust your scoring models. It helps you constantly generate targeted leads.
- Lead scoring is a great way of assessing and qualifying leads. The process can be shared by marketing and sales teams.
- You can rank potential customers based on multiple criteria such as firmographics, online behavioral activity, or engagement with your brand.
- Purchase intent data and buyer intent data can significantly improve lead scoring models. According to Gartner’s report, it’s been gaining traction thanks to recent developments in intent marketing.
- Predictive lead scoring automates the process and helps recalibrate lead scoring models in real-time. CRM software, like HubSpot, provides teams with accurate data.