In fact, according to Salesforce’s “The State of Marketing” report, Artificial Intelligence is already the technology with the greatest growth and application 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 user behavior and know their probability of becoming a lead.
How does it all begin?
The process begins with the training of AI algorithms, which are fed with millions of data points of user behavior 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 navigation, interaction, and behavioral patterns to develop a deep understanding of the target audience.
Toni-Moragues-Walmeric
AI comes into play through real-time monitoring. Every click, scroll and action is instantly recorded and evaluated, assigning a lead conversion probability to each user , which we call “visit scoring”. This provides the company with a real-time view of each visitor’s level of interest. – Toni Moragues, R&D Manager & Cofounder of Walmeric
So what are the benefits of all this? One of the most powerful gambling data india facets of visit scoring is its ability to precisely segment users . Using a scoring scale ranging from 0 to 9 (with 9 being the highest), users are classified into categories that reflect their predisposition to convert into 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 allow you to adapt the design, calls to action (CTAs), messages, and channels based on the likelihood of conversion. This not only improves the user experience, but also maximizes the conversion capacity.
All of the above allows the success of lead scoring to be measured not only by the number 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 you to direct the most suitable users towards channels that are usually more expensive but highly effective. At the same time, those less prepared can be directed to cheaper channels.
What are the results of our model?
To start, we generate 10 groups based on the probability of each visitor converting into a lead. We do this based on different variables , such as the ad and channel through which they arrived, the device they use, and their behavior on the website, among many other factors.
These 10 groups are ordered based on these variables once they have been analyzed, with the highest ranking being those groups in which the majority of visitors with the greatest chances of becoming leads are concentrated.
Within these high-value groups, we identified 74% of the leads and, in addition, 79% of the sales. Thus, we obtained homogeneous groups with higher than average conversion probabilities.
Ultimately, at Walmeric we are committed to innovation and efficiency, and the application of Artificial Intelligence to determine the probability that a user will convert into a lead and then into a sale is a key part of digital marketing strategies and improves our ROI.
