Close More Deals With Predictive Lead Scoring

close more deals with predictive lead scoring

As an experienced B2B marketer or sales representative, you are always looking for ways to close more deals. 

You’ve tried it all – from nurturing leads to pinching your messaging – but nothing draws the desired result. 

What if we told you that you have sales-ready prospects hidden in your existing leads? And you can tap into them anytime without adding to your sales efforts.

You only need a refined, automated lead qualification system to save time, money, and resources. 

In a recent article, we discussed predictive lead scoring and its market usage. Let’s discuss how predictive lead scoring can help you close more sales with lower sales effort. 

What is Predictive Lead Scoring?

Predictive lead scoring is the process of evaluating leads on data points and ranking them on their likelihood of conversion into paying customers. 

Unlike traditional lead scoring, the modernized and automated lead scoring method assigns a numerical value to leads on a scale of 0 to 100. This system uses custom signals gathered from existing customer profiles and aligns with the ideal business ICP.

Identifying top-quality and highly suitable leads swiftly is a near-impossible task in today’s times of expansive market capture. With predictive lead scoring, you can fine-tune your efforts toward leads with the greatest potential. So, close more deals without manually sifting through datasets and CRMs. 

Predictive Lead Scoring Algorithm 

The Predictive Lead Scoring algorithm generates numerical scores for leads based on their location, employee, revenue, engagement, and other behaviors. This qualification and classification use smart tools and machine learning to determine the most valuable lead.

predictive lead scoring meme

The metrics used in scoring leads can be listed as;

  • Customer Fit
  • Company Data
  • Product Usage
  • Usage Pattern
  • Financial Data
  • Engagement
  • Onboarding Data
  • Pain Points and Challenges
  • Completion Rate of Key Actions

Each set of metrics in the algorithm lets the business know how much interest the buyer has in store for their product/service.

Once a lead is scored, you can immediately assign it to a sales representative who can personalize their outreach and focus their efforts on closing the deal. 

predictive lead scoring algorithm
Predictive lead scoring algorithm

Lead scoring is a traditional practice that dates back to the beginning of commerce. But instead of approaching the best-dressed gentlemen at the party with a sales pitch for a car, businesses can now spot hot leads from a deluge of cold prospects by letting an algorithm rank them for their behavior.


The Role of Integrations and AI

Integrations AI, and automation are central to predictive lead scoring.

predictive lead scoring using machine learning
The role of integrations and AI

When a lead engages, makes an impression, or enters the sales funnel, these advanced technologies go to work right away, sifting through huge amounts of data to predict the lead’s likelihood to convert.

Using rank-based algorithms and machine learning models, businesses can carefully sort through their prospects to find the ones who are most likely to become customers.

This targeted approach not only makes sales easier but also makes it more likely that deals will go through. Also, the smooth integration of these tools makes sure that the scoring process is both flexible and responsive to changing market trends and customer behavior.

How Predictive Lead Scoring Closes Deals Faster

how predictive lead scoring close deals faster
How is predictive lead scoring close deals faster?

The process of closing a deal is sped up by predictive lead scoring, which finds leads with a high chance of converting and shortens sales cycles. Here are five ways that predictive lead scoring makes it easier to close deals:

1. Prioritizing High-Quality Leads

If you have a solid marketing team and lead-generation strategies in place, you probably talk to thousands of prospects every week. But should your sales team try to get in touch with all of them?

It doesn’t have to. Predictive lead scoring puts an end to chasing shadows. 

In traditional ways of closing deals, teams often spend their energy diving into a huge pile of prospects without preemptive knowledge about their background and funnel status. 

With predictive lead scoring, leads with a comparatively better profile surface at the top. This leads to higher conversion rates. Closing more deals is the natural consequence of nurturing leads that are situationally aligned to make a buying decision. When sales efforts are directed towards leads with a higher probability of conversion, the sales team will see a boost in their conversion rates. 

2. Automation Reduces Manual Sifting

Traditional lead qualification is manual. It involves checking metrics, analyzing behavior, and trusting gut feelings.

Predictive lead scoring adds automation. It uses data to rank leads. The top leads are backed by strong data insights, and ready for nurturing and conversion.

Imagine a salesperson sifting through a month of emails. They manually group leads based on interest. It’s time-consuming and error-prone.

Predictive lead scoring changes this. Modern systems automate the ranking. Leads get scores from factors like engagement, past purchases, and online activity.

Consider a lead visiting a product’s pricing page multiple times and downloading materials. They’d score higher than a newsletter subscriber.

With this automated system, sales teams target top leads. This ensures better interactions and higher conversion rates.

3. Focus on Nurturing Strategies

Personalized email campaigns, drip campaigns, follow-up calls, and remarketing ads are lead nurturing systems employed by the sales team to court potential buyers. However, it gets increasingly challenging to personalize outreach as businesses scale.

With predictive lead scoring, sales teams are privy to information about the entire funnel and can determine each prospect’s exact point of entry. This allows for personalization at scale. 

For example, leads entering the database after seeing a paid ad will love learning about the benefits highlighted in the ad. In contrast, leads who have engaged with your educational webinar might be more receptive to in-depth content that delves deeper into niche topics. 

Predictive lead scoring is humanity’s biggest leap from cold calling. With the elite selection of leads, sales teams can allocate their resources smartly instead of scattering their efforts across a broad spectrum. 

The meticulous personalization of sales efforts also ensures that each interaction adds substantial value to lead nurturing. This tailored nurturing shortens the sales cycles and creates a positive impression in the eyes of the prospect. 

4. Optimizing ICP

When a business knows its customers, it does well. The Ideal Customer Profile (ICP) is a key part of this. But in markets that are always changing, a fixed ICP could mean that you miss out on opportunities. It’s important to keep reevaluating based on how the market changes and what customers say.

This flexibility is shown by predictive lead scoring. It is a process that is always learning and adapting to new information. As it changes, it gives sales teams, marketing teams, product teams, and strategy teams valuable information.

Think about a few B2B giants as per the latest newsletter published by Lenny Rachitsky:

At first, Gusto focused on a specific niche: small Californian businesses that didn’t offer benefits. As they learned more about their leads, they grew their ICP to meet their new needs and take advantage of new opportunities.

Some startups, like Databricks and Persona, went into business without a clear ICP. Their trip shows how important it is to find new things. They learned from a wide range of clients, and as patterns emerged, they were able to narrow their focus.

For new businesses, the advice is clear: find out who likes your product the most and how they engage with it.

It can be helpful to start with a tight, even funny, ICP, but it is just as important to be flexible and open to change. Because predictive lead scoring is always changing, it acts as a guiding light along this path, making sure that businesses stay in touch with their most likely customers.

5. Detecting Revenue-generating Actions

Predictive lead scoring is more than just a way to rank potential clients because of its adaptive nature. It’s a tool that helps businesses figure out the most important things they can do to make money. How does this happen? By constantly changing to reflect new information and taking into account which metrics are most important for closing deals.

For example, let’s say you find out that a lot of your highest-paying customers went through a certain part of your website. In that case, it would be smart to make that section more visible, maybe by putting a lot of effort into promoting it on social media and through paid advertising.

On the other hand, if there are leads that always rank high but rarely convert and they all share a common metric, this could be the key to making your predictive model more accurate.

We know that for businesses, especially new entrepreneurs, understanding revenue-generating activities can sometimes be challenging. However predictive algorithms have the power to reveal those patterns.

How Software Tools Power Lead Scoring 

Having a well-functioning marketing team that captures as many corners as possible is a sweet sight for businesses.

However, the abundance of leads without a strategic approach can lead the sales team to chase after less likely to convert leads. 

usermotion sales intelligence

Software tools, CRMs, pipeline automation platforms, AI-powered predictive lead scoring tools, segmentation software, and data enrichment tools sift through the deluge of leads to prioritize and push leads that are best suited for the company. This ensures that marketing efforts are concentrated on leads that hold value and have the potential to convert.

Integration Across SaaS Tech Stack 

Lead scoring tools help streamline data flow by integrating across SaaS and creating a synergy of software tools across the SaaS tech stack. This allows for seamless integration of datasets and opens up easy access to sales and marketing teams across the board. 

Here’s an example of what could happen:

  • CRM Integration: Two-way data integration lets you import users and companies, tag them with “will buy” or “will churn,” and improve your Ideal Customer Profile.
  • Financial Data Sync: Connect your financial platforms to easily share transactional data. To keep your ICP sharp, track and evaluate successful transactions. From getting a new customer to noticing a payment error, record every financial touchpoint.
  • Integrate real-time event data from multiple platforms into the lead scoring system. The predictive algorithm improves as it learns more about customer fit data, app use, and interaction.
  • Integration of Instant Messaging Tools: Always know what your customers and leads are doing right in your messaging tools. To avoid missing money-making opportunities, get real-time notifications on important interactions and new leads.

Sales Intelligence at Your Fingertips

Predictive lead scoring is a step forward from CRM, as it allows for account-level insights into buyer behavior. This allows the sales team to prioritize leads, refocus their efforts, and make other informed decisions that ultimately lead to closing more deals. 

When predictive lead scoring software and CRM work together, your database changes. You don’t just look at leads; you look at possible opportunities through the lens of what you think they will do.

Your team isn’t just responding to leads; they are also putting them in order of importance based on real-time predictive metrics. Every lead is given a score, and every opportunity is ranked. This makes sure that your efforts are always focused on the customers with the most potential.

With smart tagging features of predictive lead scoring software, you can quickly identify and group companies on your CRM based on what they are likely to do next. You don’t have to guess if they’re about to make a purchase, are looking for ways to grow, or are on the edge of churn.

And what’s the cherry on top? Engagement in real time. No more missed chances or taking too long to act. This kind of speed not only makes things run more smoothly but also helps build relationships, which is a key factor in sales success.

Selecting the Right Software for Your Needs

Your software of choice for predictive lead scoring must offer a comprehensive set of features, including customization, scalability, tech integration, account-level insights, and real-time updates on your leads.

Selecting the ideal tool from various options might seem a bit laborious. Nevertheless, there are certain guidelines you can adhere to in order to choose software that aligns with your budget and effectively addresses your current requirements.


Predictive lead scoring is an essential tool in every sales team’s inventory. 

Say goodbye to guesswork, and let the algorithm pinpoint your sales team to the hottest leads. 

Optimize your sales strategy by focusing on leads most likely to convert. Predictive lead scoring makes the dream of closing more deals with less effort a reality. 

Frequently Asked Questions about Predictive Lead Scoring

What is predictive lead scoring?

Predictive lead scoring uses an algorithm to rank and prioritize leads with the highest chances of conversion. The algorithm uses custom data points, advanced analytics, and predictive analysis to filter leads most likely to result in meaningful engagements and conversions.

How can software tools help in predictive lead scoring?

Software tools like UserMotion help B2B SaaS companies by ranking their prospects and arranging them in a way that lets the creme-de-la-creme of the leads get to the top.

How to use predictive modeling on lead scoring?

Predictive modeling is a marketing automation tool that scores leads based on their engagement with the business’ marketing channels. The goal of the process is to prioritize leads that are farther ahead in their buyer journey. For instance, a prospect who checked out your website’s payment page is more likely to convert than someone who glanced at your Instagram page.