Predicting user behavior? With AI it is possible


IPMARK magazine echoes Walmeric’s lead visit scoring in its Marketing Tech 2023 Special.

According to Marketo, “70% of large B2C companies have already implemented a lead scoring system to calculate the propensity to purchase leads, but only 40% get any benefit from it”. Digital marketing has undergone a revolutionary transformation thanks to the application of Artificial Intelligence (AI), especially in the interpretation of user behavior and the prediction of the possibility of purchase, and even the moment of the funnel in which they are.

In fact, according to Salesforce’s “The State of Marketing” report, AI is already the fastest growing and most widely applied technology in marketing tools. Thanks to Artificial Intelligence, it is possible to identify the attributes that define a hot lead, create scoring models based on the particular needs of each company and be flexible enough to adapt to a dynamic, competitive and changing market. From Walmeric, today we bring you the keys on how to predict the behavior of users and know their probability of becoming a lead.

How does it all start?

The process starts with the training of AI algorithms, which are fed with millions of user behavioral data on the client’s website. It is crucial to emphasize that this process is carried out without compromising user privacy, as no sensitive data is used. The algorithms assimilate browsing, interaction and behavioral patterns to develop a deep understanding of the target audience.


AI comes into play through real-time monitoring. Every click, scroll and action is recorded and evaluated instantly, assigning a probability of conversion to lead for each user, what we call “visitor scoring”. This provides the company with a real-time view of each visitor’s level of interest. – Toni Moragues, R+D+i Manager & Cofounder of Walmeric

Now, what are the benefits of all this? One of the most powerful facets of visit scoring is its ability to accurately segment users. Using a scoring scale ranging from 0 to 9 (9 being the highest level), users are classified into categories that reflect their predisposition to become leads. This fosters exceptional personalization of marketing strategies.

This is followed by real-time personalization, which is one of the keys to success in modern digital marketing. AI makes it possible to define highly personalized marketing actions for each user group. Platforms such as Google Marketing Platform and Google Optimize make it possible to adapt the design, calls to action (CTAs), messages and channels based on the probability of conversion. This not only improves the user experience, but also maximizes the ability to convert.

All of the above allows the success of visit-to-lead scoring to be measured not only by the quantity of conversions but also by the probability. The quality of the traffic generated is evaluated, which becomes crucial information for making strategic decisions.

Another relevant advantage is the ability to optimize marketing channels. The score allows directing the most suitable users to channels that tend to be more expensive but highly effective. At the same time, those less prepared can be steered to less expensive channels.

What are the results of our model?

To begin with, we generate 10 groups based on the probability of conversion to lead for each visitor. We do this based on different variables, such as the ad and channel through which it arrived, the device used and the behavior on the website, among many other factors.

These 10 groups are ordered according to these variables once they have been analyzed, with the highest groups being those in which most of the visitors with the highest chances of becoming leads are concentrated.

Within these high groups, we identified 74% of the leads and, in addition, 79% of the sales. Thus, we achieve homogeneous groups with higher than average conversion probabilities.

In short, at Walmeric we are committed to innovation and efficiency, and the application of Artificial Intelligence to know the probability that a user converts into a lead and then into a sale is a key part of digital marketing strategies and improve our ROI.

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