A lead scoring strategy helps businesses identify and prioritize the leads most likely to convert. By ranking leads based on demographic, behavioral, and firmographic data, you can optimize your sales and marketing efforts. And if you want to take things to the next level? Incorporate intent data for unbeatable buying insights. Here, we’ll explore why lead scoring is essential, the best practices for creating a data-backed strategy, and how to customize your approach to fit your business needs.
Why Lead Scoring Is Important
Lead scoring prioritizes leads by ranking them on various parameters, allowing organizations to concentrate efforts on high-quality, in-market leads. When a lead scoring system is implemented, businesses can streamline their sales and marketing efforts by rating each prospect with a numerical value or lead score, depending on their perceived value and likelihood of purchase.
A well-structured lead scoring system ranks leads based on how well they align with an organization’s ideal customers. By identifying leads most likely to buy and assigning them tangible values or points, companies can:
- Direct their efforts toward the most promising opportunities
- Prioritize follow-up activities
- Optimize resource allocation
- Improve sales and marketing alignment
- Unify sales and marketing efforts by targeting the same audience(s)
- Increase overall efficiency and effectiveness in the lead generation process
Key Criteria for Scoring Leads
Whether you’re new to lead scoring or looking to refine your existing system, understanding the fundamentals of this powerful technique can significantly boost your organization’s sales performance and return on investment. Scoring leads effectively involves evaluating key B2B data points such as:
- Demographic information
- Behavioral data
- Intent data
- And firmographic data
Before you can start scoring leads, you’ll need to understand your ideal customers. Let’s dive deeper into each of these lead scoring criteria to understand their significance in the lead scoring process.
Your Ideal Customer Profile (ICP)
An Ideal Customer Profile (ICP) helps streamline marketing and sales efforts by providing a target to focus on. By defining the characteristics of your perfect customer, companies can focus their resources on leads that are more likely to convert.
To build an ICP, start by identifying previous customers that you’d like to do more business with. From there, comb through your CRM and tease out key attributes that align across multiple buyers. Identify these buyers’ core needs and how your solution solves their problems. When building ICPs, you’ll want to use pieces of data to create fleshed-out personas that help you intimately understand your target audience. Once you’ve built an ICP or multiple ICPs, you can begin creating your lead scoring system.
Demographic Information
Demographic information, such as job title and years of experience, plays a crucial role in determining lead quality and targeting decision-makers. Scoring job titles ensures that sales teams are engaging with the person within an organization who can push the opportunity forward. Assessing the lead’s role within the company’s buying process offers significant insights into their influence and decision-making power. Other demographic data points, like tenure and overall reporting structure, can further contextualize a buyer’s needs.
By focusing on key demographic attributes, businesses can ensure they are targeting the most relevant contacts and improving their chances of conversion.
The Role of Intent Data in Lead Scoring
Utilizing intent data in lead scoring provides valuable insights into a lead’s likelihood to buy, enhancing lead prioritization and personalizing sales outreach. Insights from intent data provide valuable information about a lead’s potential and likelihood to buy. High-intent behaviors include actions like submitting a request to talk to sales, signing up for a freemium product, or reading educational content.
Platforms like Predictiv Data can offer powerful insights that help sales and marketing teams:
- Identify traits or actions that indicate a lead’s profile fit, funnel stage, and willingness to buy
- Use intent scores to prioritize leads within high-fit accounts
- Improve the timing and personalization of sales outreach
Integrating intent data when it’s time to score leads can provide an extra layer of insight into the real behaviors of ideal customers. This intelligence directs sales teams to the right buyers and helps marketing design nurture campaigns that influence a lead’s likelihood to buy.
Firmographic Data
While demographics focus on individual leads, firmographics examine a company as a whole. In some cases, a lead could check all your boxes, only for you to find they’re employed by an organization that isn’t compatible with your solution. Firmographic data, such as company location and industry, helps assess lead quality and ensure alignment with target markets.
By incorporating these firmographic data points into the lead scoring model, businesses can more accurately identify leads that match their ICPs. This allows sales teams to prioritize leads from organizations that are most likely to benefit from and invest in your product or service.
How to Establish a Lead Scoring System
Once you have a solid grasp of the data that weaves together to form your ICPs, it’s time to create your custom lead scoring system. Most CRMs have lead-scoring features integrated, and depending on your service level, you may be able to organize a call or meeting to jump-start your lead scoring efforts.
Assign Points
Once you’ve identified the data points you’d like to score, it’s time to assign point values to each lead trait or activity. You’ll want to assign numerical values to each criterion based on its importance in predicting lead quality. Keep in mind that toward the beginning, there may be a bit of guesswork as you learn what behaviors and characteristics align with closed deals — and that’s okay. You can always refine the way you score points over time.
Set Up Lead Score Ranges
Next, you’ll set up scoring ranges that indicate the quality of your leads. A common scale is 0-100, with ranges like:
- 0-20: Cold lead
- 21-50: Warm lead
- 51-80: Hot lead
- 81-100: Sales-ready lead
Once you’ve determined your scoring ranges, you can refine the tactics you deploy for leads based on their position in your sales funnel.
Incorporate Negative Scoring
Incorporating negative scoring helps filter out unqualified leads and those with low engagement, saving time and resources. Negative scoring can occur at the moment a lead enters your CRM, reducing lead scores based on behaviors or traits that indicate a poor fit, or it can happen in real time when leads demonstrate a lack of interest or engagement with your outreach. For example, you may assign negative points for a contact ignoring emails. By disqualifying leads that are unlikely to convert, you can focus your efforts on more promising prospects.
Continuous Monitoring and Optimization
Like any other new process, lead scoring takes time to refine. Balancing data-driven insights with strategic adjustments can ensure your scoring system is helping you concentrate on quality leads. When you’re first getting started, set time aside for your sales department and marketing teams to discuss whether or not the current scoring model is working. If leads with a high score aren’t demonstrating sales readiness, you may want to take another look at how many points you’re assigning to traits and behaviors — or if those traits and behaviors should be part of your scoring rules at all.
What about Predictive Lead Scoring?
Predictive lead scoring leverages machine learning and AI to assess lead conversion likelihood, theoretically automating the evaluation process and eliminating human bias. Some benefits of predictive lead scoring include:
- Automating the lead evaluation process
- Eliminating human bias
- Identifying patterns in data for accurate predictions
- Customization to fit different industries and business needs
If you’ve rolled out a lead scoring system that isn’t quite working the way you wanted it to, you may want to consider if predictive scoring could help you fine-tune your processes. That’s where we come in.
Predictiv’s Unified Intent Model Makes Lead Scoring a Breeze
Predictiv Data is a best-in-class provider of intent data that allows sales and marketing teams to understand buyer behavior like never before. Within our platform, clients can explore over 30,000 technographic filters, rich demographics, and firmographics. But we’re so much more than just a database.
We partner with LeadSift and Bombora to verify account intelligence we source ourselves, allowing each of our clients to build a unique intent model. Our predictive analytics bubble up high-quality, in-market leads based on the criteria that matter most to you, simplifying lead scoring through intent-powered prospecting in the blink of an eye.