September 27, 2023

Why Marketing Teams Should Adopt AI Lead Scoring

Don Simpson

Updated September 25, 2023: We’ve edited the article to focus on the pros of AI lead scoring rather than pros and cons of traditional lead scoring tactics.

We’ve added more clarity around how B2B marketing analytics tools can be improved and brought all the links in the article up to date.

In the past, your BDRs would manually gather all the relevant details about every lead coming in, ask additional questions, and decide how close each lead is to your ideal customer profile

Now, the lead qualification process is much more sophisticated. You can rely on CRM tools for lead scoring, or assigning a numerical value to leads by screening on-page data.

Lead qualification helps businesses prioritize their sales efforts based on expected customer value, as opposed to pursuing everyone on the first-come, first-served basis. However, these predictive scores are based on rules derived from small sets of data and are influenced by subjective opinions of what good leads are. 

There’s a better way to sort through your leads today — AI lead scoring.

Tip: Why not get the benefits of AI lead scoring in one click? Try Lift AI — it’s a buyer intent solution that automatically screens and rates every website visitor, connecting the top ones with your BDRs.

How Does Predictive Lead Scoring Work?

AI lead scoring is a subset of the wider predictive lead scoring approach, which uses algorithms to process data about your leads and automates predictions that used to be done manually before.

A predictive analytics algorithm looks at everything you know about any web visitor from an existing database (e.g. your CRM), determines which information is important, and adds more data sources, including on-page behavior (e.g. page clicks or the number of pages visited).

As a result, the algorithm can predict which of your known leads are more likely to purchase your solution based on the information about them in the database plus their on-site actions. 

Predictive lead scoring can become more accurate by learning what all the converted customers (and unconverted leads) have in common. 

Marketing automation solutions that include predictive lead scoring are popular and used by lots of businesses today. But predictive lead scoring does have its pros and cons. 


  • Saves time by processing data automatically through an algorithm
  • Boosts the quality and accuracy of scores with rules and weights
  • Improves based on common and uncommon traits in hot leads


  • Relies on an existing database to work with (e.g. a CRM)
  • Remains subjective due to using rules and weights initially designed by humans 
  • Doesn’t account for anonymous or unknown web visitors

Is Artificial Intelligence the Future of Predictive Lead Scoring? 

Although predictive lead scoring represents an exciting leap in technology, it has been superseded by a new ground-breaking approach that Lift AI calls “buyer intent scoring.”

Imagine being able to score leads based on existing CRM data and their pre-action behavior. You’d be able to look at the data you have and augment it with data from vast arrays of third-party sources and machine-learning models that can determine which attributes inform buying behavior. That’s buyer intent scoring

The advantages of buyer intent scoring over predictive lead scoring include: 

  • Using more data and real-time inputs analyzed with machine-learning tools that eliminate guesswork, improve accuracy, and automate complex processes
  • Bringing objectivity to decision-making, freeing you from human errors
  • Uncovering greater sales insights that highlight previously unseen patterns
  • Evaluating leads who were unknown to you before
  • Enabling real-time actions on new leads
  • Allowing your BDRs to work on high-potential leads faster compared to time-consuming, manual lead-scoring tools

In addition, buyer intent scoring is cost-effective. Take your average BDR payroll and multiply it by the percentage of unqualified leads you’re getting every day to calculate how much money is going to waste. All calls pursuing bad leads are an opportunity cost for not getting the leads you want.

Since generating leads in today’s competitive online market is hard enough, making the most out of your existing lead flow is critical. That’s why the benefits of testing new lead-scoring methodologies are hard to overstate.

Why AI Lead Scoring Is More Accurate and Efficient

There’s no reason to avoid using machine-learning tools like buyer intent scoring by Lift AI. It works with any company size, revenue level, and data you have in your CRM. It even works with visitors who are not recorded in your contact lists and have no email associated with them. 

You might think that machine-learning models could assign less accurate scores since they depend on the quality and accuracy of their input data. But algorithms, unlike humans, are not prejudiced and are able to continuously get better in the judgement. Machine-learning models are based on millions (if not billions) of data points — you can rest assured that their accuracy is higher than any human calculation, even when supported by basic predictive lead scoring features. 

Start by checking the buyer intent accuracy yourself — go over the scores and compare them to what you’d have assigned as the best guess, given the information you have on hand. Try this for a few days to see the difference. 

Since algorithms lack charm and charisma, they are as objective at evaluating potential prospects as possible. 

For example, a skilled BDR might occasionally upsell a low-scoring lead and turn them into a profitable client that a buyer intent scoring model would rate as a low priority. But if you estimate how many customers that fit you better the same BDR would be able to acquire from high-scoring leads provided by AI, you’d understand the difference. The volume would be incomparable. 

Get Started With AI Lead Scoring Today

Lift AI is the most advanced iteration of predictive lead scoring, powered by 15 years of machine-learning data. Right out of the box, Lift AI uses more than one billion profiled website visitors, 14 million sales engagements, and real-time behavioral data.

Buyer intent scoring is valuable because it’s able to process every single visitor on your website, even if they are anonymous (as up to 98% of them can be). 

Here’s how Lift AI works. When it identifies a visitor with high buyer intent (about one in 10), it connects them directly to your BDRs via online chat (or displays them in other marketing tools), thus helping increase conversion rates. Visitors with medium or low scores might be directed to a nurturing bit or a self-help guide instead. 

Within the first 90 days, Lift AI can increase chat conversions anywhere from two to 10 times. PointClickCare saw a 400% increase, attributing over $1M of extra revenue to their Lift AI integration. Formstack increased their conversions by 420%

Lift AI works with any chat platform (e.g. Drift or LivePerson) or marketing tool of your choice. It’s simple to install and doesn’t even require a credit card to get started. 

Try Lift AI free — for 30 days. Stop relying on outdated contact forms as your main source of conversions and see what the new proactive AI technology can do for you. 

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