B2B Lead Scoring: Guide and Best Tools for 2022

Published by Nilangan Ray on

This post is part of a series called Lead Scoring

Article Updated on 4th April, 2022.



The digital landscape allows businesses to reach new audiences at a rapid pace. But, that comes at a price. Reaching more people means that you are now exposed to more unqualified leads, those that would never buy from you. And, if you are not weeding them out, you would end up wasting resources, resources that could have been spent on leads who are more likely to purchase. This is especially true in B2B where ticket prices are high and a lot of resources and time needs to be spent on acquiring those high ACV deals.


Unqualified leads don’t disguise themselves in the herd. There are obvious signals, and red flags. On the contrary, leads who are qualified also show signals, positive ones. Lead scoring is a system that turns these signals into numerical points that can help you prioritize leads.


Organizations that use B2B lead scoring experience a 77% lift in lead generation ROI, over organizations that do not currently use lead scoring. In this article, we will discuss the what, why, and how of lead scoring for B2B businesses.


What is Lead Scoring for B2B?

Lead scoring is a methodology used to rank prospects against a scale in numerical values. It uses rules to positively or negatively score leads based on characteristics and actions. Lead scoring, for B2B businesses, is done using various account and intent (first-party and/or third-party) data attributes.


Lead scoring is also used to determine the sales readiness of leads, especially in B2B sales, and move them through stages of the buying cycle. Leads can either be given positive points or negative points. Positive points are awarded for positive characteristics or behaviors (eg: lead is from a targeted business demographic). Similarly, points are deducted for negative behavior (eg: unsubscribing from important mailing subscriptions or removing payment information).


While job role and company data are key elements for initial qualification, behavioral data is what lead scoring shines with. Why? A B2B lead won’t buy on their first visit. They would gradually engage with you by consuming your content (case studies, webinars, etc.). They might also schedule a call, start a free trial, or talk to support. All of these engagement points would be used to gradually score leads.



Who is Lead Scoring For? Is it the Right Thing for Your Business?

Now that we understand what B2B lead scoring is and how it works, it is time to determine if lead scoring is right for your business. Depending on how many leads you generate and your ticket size, lead scoring can either be essential or good to have. You might also not need lead scoring at all.


Lead scoring is essential for you if you:


  • Process hundreds or thousands of leads per month and your sales/marketing system is being pushed to the limit.
  • Have to deal with a lot of unqualified leads and waste time on them.
  • Are missing out on good leads because you can’t prioritize them.
  • Are you spending a significant amount of resources on leads who don’t convert?
  • You want to replicate your best leads and customers and run personalized retargeting campaigns for the best leads.


If any of these apply to you, you need lead scoring. If your volume is on the higher side, both predictive and rule-based scoring will work for you (discussed later). If your volume is on the lower side, predictive scoring won’t be as effective as it relies heavily on data.


Coming to advertising, the more data you have, the more lead scoring can help you create lookalike audiences of your best leads and customers or qualify best leads and show personalized content on your website, through emails, and with retargeting.


Lead scoring is good to have for you if you:


  • Have a lower volume of leads to deal with.
  • You deal with unqualified leads but you don’t lose out on opportunities because of it.
  • You don’t miss out on good leads because your volume is low.
  • You want to replicate your best leads and customers and run personalized retargeting campaigns for the best leads.


If these apply to you, lead scoring is absolutely not essential for you but it is still something that you would benefit from having. While your reps will deal with all leads, having lead scoring will help you prioritize leads and act accordingly on leads with high scores. You can also personalize your retargeting campaigns for higher priority leads and create lookalike audiences. Your reps will also know the strong attributes of the leads (if your scoring system provides breakdowns of scores).


If you fall in this category, rule-based scoring will work more efficiently as you have less data to work with, and having close control would suit you better. Basic predictive scoring to go along with it would be a bonus.


You don’t need lead scoring at all if you:


  • Are a startup or a very small business with a small number of leads generated every month.
  • You have very high ticket prices (but a low volume of leads) and have a fixed selling process where you talk to all leads regardless.


If any of these match your situation, lead scoring will probably not help you much.

Why Should I Use Lead Scoring and Not Another Method?

The need for qualifying leads is pretty apparent by now. But, you might be wondering why lead scoring is the best method for B2B lead qualification. After all, you can just match with your customer profile once or have your reps qualify. The answer is simple. Lead scoring works gradually as leads progress through the funnel. In B2B, the sales cycles are longer and lead actions play a crucial factor in helping you understand their intent. Plus, if you have your reps call everyone manually, a lot of time will be wasted.


If you are still not convinced, here’s data for you, going into 2022:

  • According to Hubspot, the top priority for the next 12 months for most marketers (40%) is to generate more leads.
  • According to Semrush, generating more quality leads is a priority goal for 79% of marketers worldwide.
  • 34% of people interviewed by Pipedrive claimed that lead qualification and prospecting are the biggest challenges for salespeople.


Breakdown of Data Points

Let’s have a look at all the sales and marketing data points that can be used to qualify leads:


Individual Data: This data consists of information about the person who is evaluating the product on behalf of their company. The most commonly used individual data for lead qualification are job role and seniority. This helps in identifying leads who are decision-makers.


Company Data: This dataset consists of firmographic information of your leads like company size, industry, revenue, etc. The data helps you filter out leads who match your target business profile and also separate leads based on ticket size.


Attribution Data: This data point connects your qualification strategy with your marketing campaigns. Let’s take an example. You are a CRM company and you are running an ad campaign on keyword ‘CRM’. Two leads land from this campaign with one landing after searching ‘best CRM software’ and the other after searching ‘what is a CRM’. Which of them do you think has higher buying intent? Similarly, leads who visit after finding your blog post from social media usually have lower intent/urgency than those who visit your website while actively looking for your product.


Marketing attribution connects your leads to campaigns and source of visit which in turn helps you qualify your leads. The loop gets closed in the sense that marketing attribution helps you identify campaigns that bring you the most customers which you, in turn, use to prioritize leads and amplify the outcomes of higher-performing campaigns. So, leads from historically better-converting campaigns can be given higher scores.


Behavioral Data: As we mentioned earlier, this is the data point where gradual scoring comes into action. Leads perform different activities while interacting with your content and touchpoints. As leads perform these desired or undesired activities, their score keeps changing dynamically. Apart from helping understand a lead’s intent for initial qualification, behavioral data also helps in moving leads through different stages of the buying process and serving personalized content.


Sales/CRM Data: This dataset brings information from sales to marketing for revenue attribution, lead qualification and targeted nurturing. The information from sales interactions and CRM databases can be brought back to marketing for an aligned qualification effort.


Businesses also use other data points like technographic data and demographic data in accordance to their requirements. Lead scoring is heavily reliant on data and data enrichment is needed for a proper lead scoring strategy.


Setting up lead scoring


Types of Lead Scoring

There are two prominent methods to score leads: predictive and rule-based. Let’s have a look at them and find out how they differ from each other.


Predictive Lead Scoring:

A predictive lead scoring software uses algorithms to automatically score your leads based on your marketing or sales data. Some lead scoring software would also use external data or combine with a third-party data enrichment software to score your leads.


Predictive lead scoring is completely automatic and will work based on the data it is fed and how the software has been designed.


Source: https://untitled-research.com/blog/lead-prioritization-with-predictive-analytics-in-recruitment


Rule-based Lead Scoring

Rule-based lead scoring is a simpler lead scoring method where you set up rules to score your leads. Rules can be set up based on the data available to you and the functionality provided by the lead scoring software.


When a lead triggers a rule set by you, the lead score is updated. You can set up rules based on desired or undesired characteristics and behaviors like we mentioned before and the score will keep changing. You can then trigger workflows based on lead score or set up a minimum scoring threshold to mark a lead qualified. For example, you can create a system where when a lead accumulates a minimum score of 100, they are sent to sales or served pre-sales content.



The Key Difference Between Predictive Lead Scoring And Rule-based Lead Scoring Approach

The main difference in these two approaches is that with predictive lead scoring, the software does the work for you and with manual lead scoring, you set up your lead scoring workflow based on how you intend it to work. Rule-based lead scoring offers you the flexibility to set up your rules how you want to and assign weightage to each characteristic or behavior.


Let’s say, based on previous won deals, you have found out that a key product interaction (eg: trial extension) is a very strong indicator of purchase intent. You can simply create a lead scoring rule for this but can a predictive lead scoring software find this correlation? Maybe it can, but this entirely depends on how the machine learning process and the algorithm works. So, the results might vary from software to software. Also, it would be harder to use predictive lead scoring to move deals across different stages of the buying process through stage-based nurturing.


The advantage predictive lead scoring has over rule-based lead scoring is that it can pull data from a lot of different sources and you essentially don’t have to work on setting anything up yourself or analyze data to find key indicators. Depending on which software you use, you might also need to subscribe to data vendors for setup. This applies to both predictive and rule-based solutions but not all vendors need you to purchase 3rd-party data. Salespanel, for example, comes with data out of the box.



Some B2B Lead Scoring Tools in the Market and Their Prices

Rule Lead Scoring:

LeadSquared: Lead scoring is available on plans starting at $1200/month
Salespanel: Lead scoring is available on plans starting at $249/month
Hubspot (rule-based): Customizable rule-based lead scoring is available on plans starting at $800/month.



Predictive Lead Scoring:

Infer: Price not disclosed
Madkudu: Starts from $999/month
Hubspot (predictive): Predictive lead scoring on Hubspot is available on Enterprise plans. Price is not disclosed.



Setting Up Lead Scoring

For predictive lead scoring, setup is fairly simple. You integrate the software with your CRM, marketing tools, data enrichment service or your website and you are good to go. The software will start scoring your leads automatically. For rule-based lead scoring tools, on top of connecting your lead scoring software to your sales and marketing workspace, you would also need to set up your rules. The flexibility that rule-based lead scoring provides needs you to put a bit more effort in setting up your workflow.


In this article, we will provide a quick brief of how you can set up rule-based lead scoring with Salespanel. The fundamentals should be the same for other tools as well. So, on Salespanel, we provide you a person’s individual, company, and activity data right from the start. Salespanel just needs to be connected to your website (and also to your CRM if you want to use sales data). Once set up, you can create different rules based on the data that is provided to you.


Before you set up your rules, you should research your previous deals and find out strong indicators. Some data filters that will be helpful for this are job role, company size, page visits, email engagement, etc. Behavioral data will let you progressively score leads and also move them through the sales process like we mentioned before. If you need some information to find out strong indicators, check out reports of customers on Salespanel and also discuss with your sales team. They often know which indicators are stronger.



Syncing Data and Triggering Marketing Automation

The lead scoring data can stay on your lead scoring software but it makes more sense if you leverage the data to trigger certain workflows or send the data to sales to help them prioritize hot leads. Salespanel can sync lead scores to other platforms like your CRM or Slack instantly. This will help your sales know about intent signals in real-time and prioritize hotter prospects. You can also create a system to notify sales when leads cross a certain minimum score.



Lead score can also be used to trigger nurturing campaigns or optimize bidding value for your retargeting and nurturing campaigns. We will talk more about it in the future. Please leave us a message if you are interested in knowing more.



To conclude, lead scoring is a crucial asset in modern B2B sales and marketing. It can be beneficial for all digital businesses irrespective of size. While predictive lead scoring is more geared towards enterprise businesses with high volume, rule-based lead scoring can be helpful for all.

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Nilangan Ray

Nilangan runs marketing operations for Salespanel. Join him on LinkedIn: https://www.linkedin.com/in/nilanganray

Nilangan Ray, Marketing Head Nilangan from Salespanel

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