Table of Contents
What if there were a way for your marketing team to identify its most qualified prospects, understand their engagement journey, nurture them with tailored information, and present the sales team with the accounts most likely to convert? There is, and it’s called lead scoring. Read on to learn how to incorporate it into your marketing plan.
What Is Lead Scoring?
Lead scoring is the process of assigning numerical values (scores) to potential customers (leads). Leads earn points based on their behavior related to your brand, product, or service.
The marketing and sales teams assign points based on how important each action is in terms of making a purchase, where the lead is in the sales funnel, timing of (in)activity, and so on. Leads earn — and lose — points based on their engagement with different assets and actions. Once a lead reaches a certain threshold determined acceptable by the sales and marketing teams, the prospect is turned over from marketing to the sales team as an MQL (marketing qualified lead).
Why Is Lead Scoring Important? What Are the Benefits?
Simply put, lead scoring helps demonstrate the interest and likelihood of a prospect making a purchase. This allows both the marketing and sales teams to better focus on accounts that are more likely to convert. This can mean a better return on marketing investment, shorter time to make a sale, more effort on hotter leads, less marketing and sales budget needed, and data-informed decision making.
Despite helping qualify leads, only 44% of businesses were found to use lead scoring to sort these highly interested accounts. If you’re part of the majority not using lead scoring, you could be leaving money on the table, and overtaken by competitors using this tactic. After all, two out of three (68%) marketers in one survey noted that lead scoring contributes to their revenue.
Improved Marketing ROI
When leads receive a score based on engagement, they also show a trail of which actions they took to receive that score. Marketers can see what contributed to scores — i.e., what’s really moving the needle to nurture leads toward becoming a qualified sales lead.
Marketers can also see where leads stalled in this process, dropped altogether, or may have backtracked, which can be parts of the scoring journey to improve underperforming assets. This all informs marketing tactics and budgets.
Shorter Sales Cycles
When the sales team is receiving only highly qualified leads, the team can focus on prospects that are more ready to buy. The benefits are twofold:
- Higher likelihood of sales related to overall prospects that sales receives.
- Shorter window to close a sale, since prospects have been vetted by marketing.
This allows the sales team to be more efficient and effective in their jobs.
More Alignment with Sales and Marketing
Establishing a lead-scoring system agreed upon by the marketing and sales teams means that each team must buy into the process, metrics, and shared definition of success. This creates understanding and alignment into when and how a prospect is qualified.
Data-backed Decisions
Creating a strong scoring model involves looking at your funnel’s effectiveness and making decisions on what’s working, how hard it’s working, and its role in moving people toward purchases. A strong scoring model allows you to adjust, add, or modify the overall journey and experience to improve outcomes.
Key Components of a Lead-Scoring System
Demographics and Firmographics Information
Data and facts related to what people and organizations are interacting with are known as demographic and firmographic information. This can include details such as their role in the organization, what industry they are in, the location they do business in, company size, or revenue. The closer a fit these (and similar traits) are to your ideal customer profile, the higher a chance they are to be a warm target for your services, and a better fit your customer base.
User Behavior Traits
User actions and activities are behavior traits — think of this as how people interact with your brand. This can be measured as website activity (what content they looked at and how long they spent with it), email or social media interactions (such as opening, clicking, replying, or forwarding to others), form completions, or content downloads.
Metrics that involve more time commitment (over a certain amount of time on a page, filling out a form, sharing information with others, etc.) show heightened interest, and are typically weighted higher in lead-scoring models.
Types of Lead-Scoring Models
When evaluating the best lead-scoring model for your organization, consider things like what data you currently have and collect, the assets that can be weighted, what measurements matter to the marketing and sales team, the duration of a sale, and key behaviors. There are multiple ways to score leads, including creating hybrid or blended approaches.
Rules- or Points-based Lead Scoring
In the straightforward points approach, marketing and sales teams determine a numerical value for marketing efforts. Together, the group defines how much weight each interaction is worth, based on how important it is to a sale.
For example, booking a product demonstration might be weighted much more than just following a brand on social media, if the team determines that action is worth more to them. Once a lead has acquired a certain number of points — as previously agreed upon by marketing and sales to signal a hot lead — the information is passed from the marketing team to the sales team. Sales can then use the information (total points earned, actions users took to receive the points, and so on) to prioritize and refine sales efforts.
Predictive Lead Scoring
Information such as past user behaviors and company or public data can be used to analyze future potential sales. Through the use of artificial intelligence (AI) and machine learning (ML), a predictive lead-scoring model identifies which accounts or users are most likely to convert. The use of this technology decreases the time marketing and sales teams need to spend in setting up a scoring model, and allows for more time to create experiences and assets, or have meaningful conversations that move a user to become a customer.
Demographic Lead Scoring
Demographic lead scoring involves collecting a person’s or organization’s traits — such as industry, job role, company budget or revenue, business size, contact information — to determine qualified leads for sales. This approach can be helpful when targeting your ideal customer profile.
Behavioral Lead Scoring
In behavioral lead scoring, data is collected and assigned a score based on a user’s actions. This data, including single actions or a collection of activities, is used to indicate where someone is in the buyer journey. Examples of what to collect for behavioral lead scoring include what users register for and when, and what they download, click on, stop at, go to next, save and share, and so on.
How to Build a Lead-Scoring Model
A lead-scoring model should accurately incorporate your business objectives and ideal customer behaviors. Together, marketing and sales should create a system that creates mutual success for both teams.
Define Your Ideal Customer Profile and Buyer Personas
Identify what a successful conversion would be, and how that person might get there. Consider where your current customers fall, and adjust expectations accordingly. Understand current and future pain points, goals, their role in the buying process, and what assets and support potential customers need to make an informed purchase, as well as any roadblocks they face.
Study User Behaviors
Look at analytics and proof points you have, and measure them against your marketing efforts. List every piece of content that a prospect could come across, and consider how important it is to ultimately making a sale.
Assign Points Values Based on Information
Track scores based on how much of a fit a person or organization is for your business goals. The closer their demographics and firmographics are to your ideal customer profile, the higher the value. Give higher points values for actions people take closer to purchase, or that are more important to your qualifying process.
If a lead isn’t a fit (based on role, company information, etc.) or loses interest (doesn’t open any recent emails, stops visiting the website), subtract points from their total score. This helps keep the active prospects closer to a handoff from marketing to sales.
Lead-Scoring Best Practices
Once marketing and sales have established a model and scoring system that aligns to the ideal customer profile and buyer journey, consider additional lead-scoring best practices to enhance the process and results.
Integrate With a MAP or CRM
Once the upfront work is done, consider adding an integration, such as a marketing automation platform (MAP) or customer relationship management system (CRM). This integrated solution can score users, reduce the chance for errors, alert marketing and sales in nearly real time of a prospect’s progress, share information among programs, and manage a lot of requests at once.
Add Automations for Active Management
Layer in automation for always-on improvements and tweaks. This doesn’t mean a human touch won’t be needed, but adding automation enhances the model that sales and marketing have established. For example, filling a form could trigger an alert to the marketing team that the prospect is getting warmer.
Define Thresholds to Transfer From Marketing to Sales
Lead-scoring thresholds are the score that prospects must reach to be passed from the marketing team to sales, as agreed upon by the two groups. Setting a threshold is crucial to success, ensuring that only high-quality leads make it to sales, allowing sales to better focus efforts. It’s also vital to periodically review the accuracy and quality of leads being passed to sales. This will help ensure that scoring is not passing lower-quality leads to sales, or reveal if thresholds are set too high and keeping potential opportunities from engaging with the sales team.
Optimize the Entire Ecosystem
As previously mentioned, lead scoring is not a one-time activity. Ideal customer profiles may shift, product offerings can change, and external factors (like SEO, third-party data, or AI) can affect the overall experience and how people consume information. Be sure to audit behaviors, learnings, and even the initial scoring model. Is it working today to the best of its ability? Are there patterns that weren’t accounted for previously? During the initial six to 12 months of using your model, review it as frequently as monthly or quarterly. Moving forward, review and adjust your lead-scoring model at least once a year.
Key Takeaways
Lead scoring is a method of filtering interest in a product or service by assigning numerical values to the user based on intent, behaviors, and demographics or firmographics. Once a marketing prospect reaches a certain threshold in the model, they are passed to the sales team as a prospect interested in converting. This allows both marketing and sales to focus on users who are more interested and engaged, and nurture them towards becoming customers. An effective lead-scoring model is one that both marketing and sales come together and agree on, and aligns to the organizational ICP and buyer journey personas.
Frequently Asked Questions (FAQs)
How do you assign points in a lead-scoring model?
The sales and marketing teams should work together to determine what level of intent a certain action or asset elicits, and create a score based on it (where a more desirable activity is worth higher points). Together, these teams will also define when a lead is handed from marketing to sales, based on points accrued.
What data should you use for lead scoring?
When implementing lead scoring, consider the following types of data:
- Demographic: Information about the user, such as location, job experience details, age, gender, etc.
- Firmographic: Information about the organization, such as industry, revenue, or headcount.
- Behavioral: Information based on actions a user took, such as opening an email, engaging in pop-up messaging, or downloading content.
How do you score B2B leads vs. B2C leads?
While a B2B sales cycle can last well over a year and be decided by committee, a B2C cycle is often shorter, may be made by one person, and can even see a lot of emotional or impulse buys. Therefore, each scoring model needs to consider these nuances and adjust how much value to give different demographics or behavioral inputs. Make sure to align this to your ideal customer profile and buyer journey.
What do you do when low-scoring leads convert?
Sometimes low-scoring leads may convert, or high-scoring leads fail to. Use this as an opportunity to acknowledge there can be outliers, but also look to see if you should update or adjust your lead-scoring model.
What are common mistakes to avoid in lead scoring?
Lead scoring cannot be decided one time by one person. Create alignment among marketing and sales as to what constitutes a hot prospect, don’t over-rely on any one form of information without assessing the entire demographic and behavioral makeup, and remember to include lead decay. Consider a schedule to review how accurate your scoring values are, and assess if any scoring items should be added or removed from the model.
