When it comes to generating demand for your business at scale, understanding the importance of efficiently prioritizing leads is critical for your success. Now you might have curated an extremely useful outbound prospecting list with thousands of prospects, but the challenge lies in discerning which of them warrant your immediate attention.
With organizations seeing a staggering 77% increase in results through B2B lead scoring, it’s not just a methodical approach but a strategic one. If you’re a B2B business, it’s imperative that you prioritize the most potent leads and reach out to them first.
Over the course of this article, we’ll explore everything you need to know about B2B lead scoring & how you can automate the process using AI in just a few easy steps.
Let’s get started.
B2B Lead Scoring Definition: Know the Basics
B2B lead scoring isn’t just another buzzword, but more of a strategic approach used by savvy revenue & sales teams. Under this method, a numerical value is assigned to leads based on certain predefined criteria, helping the salespeople identify which leads are ripe for outreach first.
The higher the score, the more likely they are to buy.
That being said, lead scores are ascertained by considering multiple variables, which are then divided into two categories: implicit and explicit lead scoring.
Given below is a overview of what both of these B2B lead scoring types include:
- Explicit lead scoring: This involves assessing observable demographic and firmographic information like company size, industry sector, or job title. Such type of lead scoring is mostly based on data we’ve received from the prospect directly.
- Implicit lead scoring: Implicit lead scoring is based on lead behavior – website visits, content downloads, or email engagement.
For this type of scoring, it’s important to analyze the prospect’s behavior, and the process usually includes scoring based on active & passive buyer behavior and various behavioral analysis methods.
How to Create an Effective B2B Lead Scoring Process?
Now that we know the basics of B2B lead scoring, the next question is: “So how do I get started with creating my own lead scoring process?”.
Simple, just follow the below steps to get started:
1. Start with the ICP
As is the case with any B2B marketing or sales activity, we’ll always start our B2B lead scoring process by defining the ICP, where we analyze the demographic, firmographic and behavioral characteristics, among others.
You can analyze your existing customers, conduct market research or interview sales & marketing teams to create your own lead scoring and prioritization method.
Some common questions to answer here include:
- What’s the industry your ICP operates in?
- What is the company size you’re targeting?
- What is the location of your ICP’s business?
- What is the decision-making process involved? What factors come into play?
- What pain point or challenges do you solve for them?
Once you’ve got a deeper understanding of the ICP, you can start targeting companies who match the exact criteria. This way you’re not randomly picking & choosing leads, but pursuing them in a strategic, more qualified manner.
2. Use historical data for predictions
Historical data is critical for the B2B lead scoring process, since it enables you to identify trends & patterns which can be used to predict future outcomes. By analyzing previously available data, you can gain insights into the characteristics of prospects that have already converted.
To find out these insights, you can dive deeper into the CRM and use it to analyze patterns and conduct a 360-degree view of your ideal customer.
3. Establish the scoring criteria
To rank the leads objectively, you must determine the main criteria for scoring them. This process usually involves considering 2 types of lead scoring parameters – the implicit and explicit scoring methods.
While the explicit criteria focuses on the demographic & firmographic data, the implicit one includes activities such as website visits, content downloads and social media interactions.
Once you’ve uncovered these insights, here’s how you can use them to create your own lead scoring model:
4. Decide the point value
The fourth step in creating your own B2B lead scoring process involves prioritizing the implicit and explicit criteria by grouping them based on different orders of importance.
To do this, you could use the following points system or B2B lead scoring formula:
- Critical criteria: 10 to 15 points
- Important criteria: 5-9 points
- Influencing criteria: 1-4 points
- Negative criteria: Negative points
Now, say a prospect completes multiple actions, and the sum total of the points comes around 13, it’ll fall under the ‘critical criteria’. In such a scenario, such leads would be highly-qualified and should be prioritized first during your outreach.
You can use a similar approach to assign a cumulative score to the leads & segment them in categories like hot, warm and cold.
By following the above steps, you can easily create your own B2B lead scoring system, and fine-tune it as you receive more lead data. Once you have it, analyze what values translate into higher conversions & shorter sales cycles.
You can even automate this entire process using AI, something that we’ll explore in the next few paragraphs.
How to Automate B2B Lead Scoring Using AI? – Stepwise Analysis
When it comes to B2B lead scoring, AI can be a gamechanger for your business. Over the next few steps, we’ll dive deeper into how you can leverage tools like Clay for automating the B2B lead scoring process in a step-by-step manner.
So let’s understand how to do this.
Step 1: Setting up the foundations
In the first step to automate your B2B lead scoring, you must have a list of companies and people who are part of your ICP alongside the merge fields which you want to score and prioritize based on specific criteria, in a tabular format.
Step 2: Enrich your data
Once you’ve got the first step done, go to the ‘Enrich Data’ option on Clay & then search for scoring-related actions in the search bar. Under the ‘Actions’ tab, you’ll find integrations such as ‘Score Rows in Clay’ or ‘Score Words in List’ which you can choose from, to start scoring specific rows for your outreach.
Step 3: Add your B2B lead scoring criteria
Once the data has been enriched, you can start adding the necessary B2B lead scoring criteria for refining the lead list further. This process involves defining the values, comparing types, scores and keywords.
To get your lead scoring criteria right, consider the following factors:
- Are the people you’re targeting in the right industry?
- What is their recent headcount? Are they hiring people?
- Did they recently get funding?
- Is their company growing?
In addition to the above, you can also apply some additional criteria to score leads in your prospecting list, some of which can be as follows:
a. LinkedIn followers
B2B lead scoring on the basis of LinkedIn followers can be your first scoring criteria. To do this, simply select the ‘Follower Count’ option and using the ‘between number’ comparison, define the grouping you’d want. These could be anywhere from 1,000 to 5,000 and 5,0001 to 10,000 and beyond.
You can then assign a points system (e.g. – 1 point for group 1, 2 points for group 2 and 3 points for the 3rd group) to each of the above groups.
b. Job Title
The job title is yet another useful lead scoring criteria based on the prospect’s job title. You can assign points to the leads, based on certain titles or keywords like ‘sales’, ‘finance’, ‘marketing’, ‘CEO or founder’ among others.
Then you can apply the same points system to assign a value to the title-based groups under this criteria.
The third B2B lead scoring criteria could be to score the leads based on their location. To apply this, you can add criteria which says that if a prospect is in the UK, you must assign them an extra point.
Doing this helps you prioritize the leads which belong to a specific country and are relevant to your ICP and offer.
d. Founding year
This another useful B2B lead scoring criteria that focuses on the year of establishment of a company. You can assign points to companies by grouping them based on their founding year and then assigning points again to each group.
Once each of these scoring criteria have been defined, simply click ‘Save and Run’ to run the scoring for all rows in the prospect list table.
Step 4: Categorizing prospects
Once the scores have been assigned, you can create specific views for each prospect type, such as ‘Medium Quality Leads’, ‘Lower Priority Leads’ and ‘Best Quality Leads’ among others, each of them filtered and prioritized based on the final lead score.
So these are some of the steps you need to follow for scoring B2B leads based on different criteria. You can simply follow the above steps, and narrow down your own criteria and weighted scores to prioritize leads for outreach.
In addition, if you’re keen to explore how to score leads by using your own B2B lead scoring formula, feel free to check out Clay’s own resource on the topic and learn how to prioritize leads using your own scoring methods.
B2B Lead Scoring Advantages and Disadvantages: Is the process worth it?
B2B lead scoring offers an extremely useful method for lead prioritization and outreach. By using this method, you can easily decide which are the top leads for your business that not only match the ICP, but also have the required intent and buying power.
In the below paragraphs, we’ll explore some common benefits of B2B lead scoring you should know about:
Advantages of B2B Lead Scoring
- Lower acquisition costs
When it comes to B2B lead scoring, one of the standout benefits is the ability to lower acquisition costs. By honing in on leads that have the highest potential to convert, businesses can optimize their marketing and sales efforts, focusing resources on the most promising prospects. This targeted approach is not only efficient but also cost-effective.
The Aberdeen Group’s findings underscore this point, revealing that companies employing lead scoring experience a 192% higher lead qualification rate than those without such systems.
This efficiency translates into a significant reduction in the resources spent per lead, showcasing the financial benefits of a well-implemented B2B lead scoring system.
- Higher conversion rates
Another significant advantage of B2B lead scoring is the improvement in conversion rates. By systematically identifying and prioritizing leads that are more likely to make a purchase, businesses are essentially fishing in a well-stocked pond.
Marketo’s study supports this claim, stating that organizations with mature lead scoring processes see a 9.3% higher sales quota achievement rate compared to those without.
This boost in conversion rates is a clear testament to the efficacy of B2B lead scoring, as it ensures that sales teams are engaging with leads that have a higher propensity to convert.
- Less time wasted
Timing is a crucial cog in the wheel for B2B sales, and lead scoring plays a pivotal role in ensuring that sales teams do not squander their time on leads with a low likelihood of conversion.
By prioritizing leads based on their score, sales representatives can focus their efforts on engaging with the most promising prospects, thereby maximizing their productivity and effectiveness.
This strategic focus not only optimizes the use of time but also enhances the overall performance of the sales team.
- Ensures marketing & sales alignment
A key benefit of implementing a B2B lead scoring formula is the alignment it fosters between marketing and sales teams. By establishing a common framework for identifying and prioritizing leads, both departments work cohesively towards a unified goal.
This synergy is crucial in bridging the gap that often exists between the two teams, leading to more efficient lead generation and nurturing efforts.
When marketing and sales are on the same page regarding what constitutes a ‘qualified lead,’ the entire lead management process becomes more streamlined and effective.
Now that we’ve understood some of the benefits B2B lead scoring offers, it’s crucial to look at the cons of using this approach as well.
Given below are some common challenges and disadvantages associated with using B2B lead scoring for lead prioritization.
Disadvantages of B2B Lead Scoring
- Unorganized data-related hurdles
B2B lead scoring is not without its challenges, particularly when it comes to the quality of data. Inaccurate, outdated, or incomplete data can lead to erroneous lead scoring, which in turn can result in misallocated resources and missed opportunities.
Ensuring the integrity and accuracy of the data feeding into the lead scoring system is, therefore, paramount to its success.
- Lack of feedback loop
Another potential pitfall of B2B lead scoring is the absence of a continuous feedback loop from the sales team. Without regular updates and insights from those on the frontline of sales, the scoring model may fail to adapt to changing market trends and customer behaviors.
This lack of dynamic adjustment can lead to a disconnect between the scoring system and the actual sales landscape, rendering the lead scoring process less effective over time.
- Expensive to setup and maintain
Implementing a comprehensive B2B lead scoring system, particularly one that integrates advanced AI algorithms, can entail significant costs. For smaller businesses or startups, the initial investment in setting up and maintaining such a system can be daunting.
While the long-term benefits of an effective lead scoring system are undeniable, the upfront financial commitment can be a barrier for some organizations
- Potential bias
Finally, a critical disadvantage of B2B lead scoring lies in the potential for bias within the scoring models. These biases often stem from the historical data used to create the model. If this data is not representative of the entire target market or contains inherent biases, the lead scoring system may perpetuate these issues. This can lead to certain types of leads being consistently undervalued or overlooked, which in turn hinders the discovery of potentially lucrative opportunities.
For instance, a model might give lower scores to leads from newer industries or smaller businesses, simply because there is less historical data available for these segments.
To mitigate this, it’s essential to regularly review and update the lead scoring criteria to ensure they remain objective and relevant.
So this is everything you need to know about B2B lead scoring & how you can automate the entire process with AI. By following the above steps, you can easily assign scores to groups of prospective customers and prioritize them based on their adherence to different criteria.
At Cleverviral, our data intelligence solutions prioritize leads based on multiple criteria unique to different types of businesses. By adding AI to the mix, we’re not only able to achieve better personalization, but also understand which leads need to be contacted first.
If you’re looking for a B2B growth partner to help you leverage AI to score leads & reach out to them at scale, connect with us on [email protected] and our team of experts will get in touch with you to answer all your questions.
Until then, happy prospecting!!
Frequently Asked Questions
Can you score leads based on intent signals?
Yes, you can easily score leads based on intent signals. To do this, you need to understand the key demographic and firmographic characteristics of your ICP segments. As a B2B business, you must understand which prospects have attributes which make them a high-value lead, and then qualify them based on their potential LTV as a customer.
Once you have this data, assign points to each lead based on characteristics like the demographics, behavior, deal size and funnel stage. Next up, you can simply distribute weights to the different scoring categories based on how your sales & marketing teams define a high-quality lead.
What is lead scoring criteria?
Lead scoring criteria refer to the set of predefined factors used to evaluate and rank leads in terms of their sales-readiness and potential value to the business.
These criteria typically include both demographic information (explicit criteria) such as job title, industry, company size, and geographic location, as well as behavioral data (implicit criteria) like website visits, content downloads, and email engagement. The combination of these factors helps businesses assign a numerical score to each lead.
This score indicates the lead’s likelihood to convert into a customer, enabling sales and marketing teams to prioritize their efforts and focus on the most promising prospects.
How do you score leads in B2B?
In B2B contexts, leads are scored by evaluating them against a set of predetermined criteria that indicate their likelihood of becoming customers. This process involves assigning points based on various explicit and implicit factors
The total points a lead accumulates determine its score, which reflects its sales-readiness and potential value. Higher scores indicate leads that are more likely to convert, allowing sales teams to prioritize their outreach and nurturing efforts effectively.