No coding, no PhD’s. New insights,
new answers, new superpowers.


No coding, no PhD’s.
New insights, new answers, new superpowers.


The world of marketing is in great turmoil and are especially the innovations such as machine learning and artificial intelligence that contribute to creating this climate particularly electric.
One of the problems is that, while waiting to get the desired competitive benefits is exponentially growing, for many professionals such technologies seem complicated and inaccessible, far from the traditional skills and marketing techniques. However, thanks to our Machine Learning techniques they will become skills of common
use, with functions that will be integrated into the tools and software more used, and that marketers will necessarily have to master.
The current challenge is to overcome the “fog” and the vacuum of knowledge that momentarily surrounds Machine Learning, to understand which transformations could really be able to make.

1 – Customer Experience

Without Machine Learning it is very complicated and excessively expensive work andanalyze the enormous amounts of data we can have. Data that can come from numerous sources: buying behavior, website sales flow, use of mobile apps, replies to previous campaign, just to name a few.
Their correct and timely analysis could help in a decisive manner predict what actions to take, modulating offers no longer based on large segmentations, but rather on the individual customer. It would make it possible perform very precise forecasts and in times impossible for any human being.
That of the Customer Experience, will be the sector in which the Machine Learning will have the most significant impact and where it will bring the greatest benefits.
Every aspect (from attracting, to selling, to serving customers) will be improved and it will be possible to foresee the activities to be carried out with greater advance and precision.

2- Customer Segmentation

Machine Learning is very effective in selecting and extracting customer groups small and homogeneous, differentiated according to the degree of similarity of their preferences and behaviors. Always, that of segmentation is a fundamental practice for each marketing operator, but thanks to the automatic learning new doors are opening and the borders that can be reached are something which previously was not even imaginable.

3 – Reduction in the customer drop-out rate

To minimize the loss of customers, companies are turning to Machine Learning. Thanks to past user data, Machine Learning is capable of generate predictive models that
allow marketers to evaluate in advance how their intervention could affect the probability of abandonment. It is therefore possible to foresee what consequence an action will have before it is carried out, modulating the interventions according to the best possible forecast and minimizing dropouts.

4 – Price optimization

More and more marketing professionals, especially at high level, rely on Machine Learning to define their strategies based on price. Machine learning is able to optimize prices in order to make them more competitive and relevant to the reference context. Not only the “simple” prices, but – thanks to Machine Learning – also the sales period, the sales channels, the product location and the customer segment are optimized.

5 – Modulation of offers

Another field in which Machine Learning is making a real revolution is that of offers and sales incentives, how to present them and through which channels.
Specific sales offers are created and supported by additional content, offers and incentives. These elements are made available by an engine of optimization that uses the logic of Machine Learning, with the aim of provide the best combination of elements that will lead to a new one sale.

The future of Marketing is around the corner

Many of the things we do manually can be replaced and managed more effectively. Thanks to machine learning, marketing professionals can inquire about many threats and opportunities as they dedicate their own time to creativity and implementations needed to exploit the new advantages and knowledge in the best possible way.

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