Revolutionary your sales: when AI is at the service of prospect scoring

Magileads: when AI puts itself at the service of prospect scoring
Magileads: when AI puts itself at the service of prospect scoring
Magileads: when AI puts itself at the service of prospect scoring

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.

The lead scoring of prospects or behavioral scoring of prospects is particularly essential in B2B. This is one of the important levers for a successful marketing campaign. It optimizes your marketing operations and targeting your campaigns . Nevertheless, it is not easy to harvest with precision and filtered way the most useful information on your prospects . Marketing Automation solution , everything becomes simpler and you become more effective in your efforts.

What does BtoB lead scoring consist of?

The prospect scoring consists in awarding a note to each prospect according to its level of engagement, that is to say its behavior towards your brand and your product. For example, it is said that the prospect heats up if he consults the page . In simple terms, behavioral scoring gives a precise idea of ​​the level of maturity of your prospects.

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

Scoring by categorization allows you to optimize your web-tracking and retargeting campaigns. This classification helps eliminate off-target visitors during follow-ups. The pages are classified according to the prospect's predisposition 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 tailor-made omnichannel strategy by providing you with the best customer acquisition levers. With marketing automation as a lever, you now have the opportunity to make all your marketing efforts profitable while saving time to develop your business.

Can we predict prospect behavior using AI?

Machine learning allows you to make relevant predictions in terms of behavioral scoring. Data scientists developed this technology to simulate human learning. Thanks to it, you will be able to empirically study the mechanism that guides the choice of your prospects and to 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

When AI is at the service of scoring
When AI is at the service of scoring

Expert references and credible studies

Studies and reports of the prospect scoring
A recent analysis of Forrester (2024) reveals that the IA scoring solutions improve the qualification of the leads by 68% while reducing the acquisition costs of 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 experts in the prospect scoring
Dr. Sarah Chen, artificial intelligence researcher applied to Marketing in Stanford, explains: "current IA scoring models now incorporate hundreds of behavioral signals invisible to the human eye".

Marc Dupont, founder of SalesPredict AI, underlines: "Our technology identifies patterns in historical data which make it possible to predict the potential customer with unequaled reliability".

Direct testimonies on prospects scoring

“Thanks to the IA scoring, we have increased our conversion rate by 40% while reducing the prospecting time by half. " - Paul D., commercial director in the pharmaceutical industry

“The implementation of an intelligent scoring system 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 skills that only large companies could afford before. » - Ahmed K., founder of a SaaS

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.

The customer case of Salesforce on the implementation of Einstein AI for the scoring of prospects shows concrete gains of commercial productivity.

Five additional testimonies

“Our conversion rate jumped 35% after adopting an AI scoring solution for prospects scoring. " - Laurent G., sales director

“Predictive analysis now allows us to identify hot prospects before they even get in touch. » - Émilie T., Marketing Automation

“In 3 months, we tripled our qualified pipeline thanks to intelligent 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 over highly qualified leads. " - Thomas L., sales manager

Five stories and anecdotes on the scoring of prospects

During an A/B test, a company discovered that its IA model identified as "hot" prospects that humans had classified as "cold". 78% of them actually bought 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 typeCharacteristics of scoring IAKey benefits
TPESimplified models, easy integrationImmediate time saving
SMEMulti-channel analysis, personalizationBetter allocation of resources
EtiComplex algorithms, enriched dataDetection of strategic opportunities
Large accountsAdvanced CRM integration, predictive analyticsOptimization 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.

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