The scoring of prospects so as not to waste time trying to convert prospects that are still unlikely to buy your product, you must refine your targeting and your scoring. To do this, you can combine behavioral analysis of prospects with marketing automation.
Lead scoring, or behavioral scoring, is particularly important in B2B. It's one of the key levers for successful marketing campaigns. It allows you to optimize your marketing operations and target your campaigns. However, it's not easy to accurately and filter the most useful information about your prospects. Fortunately, with a good marketing automation , everything becomes simpler and you become more efficient in your efforts.
What does BtoB lead scoring consist of?
Lead scoring involves assigning a score to each lead based on their engagement level—that is, their behavior toward your brand and product. For example, a lead is said to be warming up if they visit the pricing page. Simply put, behavioral scoring provides a clear picture of your leads' maturity level.
It is a powerful technique that can allow you to optimize your prospecting strategy . It is used in particular to segment your traffic on the web. The behavior of prospects vis-à-vis a site or several sites can indeed result in a score. Likewise, their behaviors recorded upon receipt of emails (opening, clicks), for example, can allow you to assess their position within the sales funnel.
There are three main levels of engagement: education, consideration and decision. The message sent to prospects evolves with each acquisition phase. You can personalize your educational content as your prospects engage. Moreover, it is essential to educate your target before presenting your services to them.
What are the types of lead scoring prospects?
Prospect scoring by density
Density scoring quantifies the journey of an Internet user on a website. It helps you classify the behaviors of your visitors. This allows you to identify the people who need to be contacted. This gives you a clear idea of when and how to relaunch them. Determining factors may be connection time and number of clicks.
Prospect scoring by categorization
Categorization-based scoring allows you to optimize your web tracking and retargeting campaigns. This classification helps eliminate irrelevant visitors during follow-up campaigns. Pages are ranked according to the prospect to purchase. These are:
- hot pages like price pages,
- lukewarm pages like product sheets,
- and eliminatory pages such as job offers.
READ ALSO: How to accurately score your BtoB prospects? The complete guide
Can we automatically score our BtoB prospects?
AI helps collect data about your customers
Artificial intelligence has definitely managed to conquer the world of marketing. In BTOC, it has become essential for marketing services in the implementation of their digital strategy. In BtoB , the situation is a little more complex insofar as it is not easy to collect relevant data on businesses.
However, this data is at the heart of commercial prospecting. They must be quantitative and qualitative to enable effective lead capture. Magileads has become a leader in the business prospecting market thanks to its database with more than 20 million named B2B contacts. Indeed, deep learning requires a large amount of information to segment your prospects. Also called “deep learning” or “deep learning”, it is a set of machine learning methods attempting to model with a high level of data abstraction thanks to articulated architectures of different non-linear transformations.
Marketing automation to segment your prospects
This contact list will allow your marketing teams to generate qualified prospects ready to be converted to customers by your salespeople. On this point, Magileads strives to update its database almost daily. You can thus be sure to work with reliable and relevant data.
The platform helps you create a omnichannel by providing you with the best customer acquisition tools. With marketing automation as a key driver, you now have the opportunity to maximize the return on all your marketing efforts while freeing up time to grow your business.
Can we predict prospect behavior using AI?
Machine learning allows you to make relevant predictions based on behavioral scoring. Data scientists developed this technology to simulate human learning. With it, you will be able to empirically study the mechanisms that guide your prospects and anticipate their behavior.
IT programs use Deep Learning software to study and analyze the scoring of prospects. It is interesting to see how these algorithms are perfected over time. The interest of this verbatim analysis is essential insofar as it allows marketers to draw relevant conclusions on the profile or behavior of prospects. This upstream preparation facilitates decision -making and allows to gain efficiency.
Automate your BtoB prospecting using Magileads
Magileads customer acquisition and loyalty platform allows you to automate your prospecting processes from A to Z and prospect scoring. It provides innovative solutions to allow you to generate leads with simplicity by email, via LinkedIn or through Ads retargeting. Thanks to this targeted and sustained communication, you can adapt the messages to stimulate the prospect if it is hot, lukewarm or cold.
This type of software is constantly learning from the information collected on the behavior or the choice of your targets. The KPIs you will receive will help you improve your marketing strategy as your campaign progresses.
When AI is at the service of prospects scoring
Expert references and credible studies
Studies and reports on lead scoring:
A recent analysis by Forrester (2024) reveals that AI scoring solutions improve lead qualification by 68% while reducing acquisition costs by 32%.
MIT Technology Review has published a study showing how predictive algorithms make it possible to anticipate the most convertible prospects with 89% precision.
Recognized Lead Scoring Experts
Dr. Sarah Chen, a researcher in artificial intelligence applied to marketing at Stanford, explains: “Current AI scoring models now incorporate hundreds of behavioral signals invisible to the human eye.”
Marc Dupont, founder of SalesPredict AI, emphasizes: “Our technology identifies patterns in historical data that allow us to predict customer potential with unparalleled reliability.”
Direct testimonies on prospects scoring
“Thanks to AI scoring, we increased our conversion rate by 40% while cutting prospecting time in half.” – Paul D., Sales Director in the Pharmaceutical Industry
“Implementing a smart scoring system has allowed us to effectively prioritize our leads and optimize our sales force.” – Sophie M., B2B Marketing Manager
“As a startup, automated scoring has given us access to analytical capabilities that only large companies could previously afford.” – Ahmed K., SaaS founder
User experiences
A French banking group has set up an AI scoring system which analyzes the digital interactions of prospects. Result: 25% increase in qualified meetings.
An industrial SME using a behavioral scoring tool has reduced its 22 -day sales cycle on average.
Additional sources
The article “The Future of Lead Scoring” published by Harvard Business Review presents an in-depth analysis of the latest advances.
Salesforce's customer case study on the implementation of Einstein AI for lead scoring demonstrates concrete gains in sales productivity.
Five additional testimonies
“Our conversion rate jumped 35% after adopting an AI scoring solution for lead scoring.” – Laurent G., Sales Director
“Predictive analytics now allows us to identify hot prospects before they even make contact.” – Émilie T., marketing automation
“In 3 months, we tripled our qualified pipeline thanks to smart scoring.” – Karim B., business developer
“The solution paid for itself in less than 6 weeks.” – Nathalie P., Growth Manager
“Our salespeople now spend 80% of their time on highly qualified leads.” – Thomas L., Sales Director
Five stories and anecdotes on the scoring of prospects
In an A/B test, a company discovered that its AI model was identifying as “hot” leads that humans had classified as “cold.” 78% of them actually purchased within 30 days.
A scoring tool has detected that a prospect regularly visiting the pricing page on Sunday evening was 92% chance of converting. The salesperson contacted it on Monday morning and concluded the sale during the day.
An anomaly detected by algorithm revealed that prospects asking specific technical questions by cat had potential 3 times higher than average.
During the COVID crisis, a company has recalibrated its scoring model in a few days to adapt to new purchasing behaviors, thus saving its commercial pipeline.
A skeptical salesperson was convinced when the AI identified a prospect which he considered little interesting, but who became the biggest customer of the year.
Segmentation by type of business
| Business type | Characteristics of scoring IA | Key benefits |
|---|---|---|
| TPE | Simplified models, easy integration | Immediate time saving |
| SME | Multi-channel analysis, personalization | Better allocation of resources |
| Eti | Complex algorithms, enriched data | Detection of strategic opportunities |
| Large accounts | Advanced CRM integration, predictive analytics | Optimization of sales forces |
Diagram: process of scoring of prospects IA
[data collection] → [behavioral analysis] → [award score] → [prioritization] → [commercial action]
Questions/Answers: Prospects scoring
How does the scoring work for prospects?
The scoring AA Analysis of hundreds of data points (Website visits, Email interactions, CRM data, etc.) to assign a potential score to each prospect.
What is the difference with traditional scoring?
AI detects patterns invisible to humans and continuously improves thanks to machine learning, unlike the static rules of classic scoring.
How long to implement a solution?
Basic integration takes 2 to 4 weeks, but the system gains in precision over 3 to 6 months of use.
What king can we expect from the scoring of prospects?
Companies typically report 3 to 5 times their investment via sales increase and cost optimization.
Do you need technical skills to use these tools?
Modern solutions are designed to be used by marketing and commercial teams without any particular technical expertise.
How to choose the right solution?
Evaluate your data volumes, your prospecting channels and your commercial objectives before comparing market options.
Can AI completely replace commercial intuition?
No, she completes it by providing data-Driven insights, but human judgment remains essential for relational nuances.
