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"To improve is to change"

(Winston Churchill) 



Data Analysis and Business Intelligence for the development of Data-driven companies

Using artificial intelligence algorithms for modeling, organizations can make better decisions with the help of insights.


CRM Analytics

CRMs simplify processes and improve profitability, but often have limited Analytics and Business Intelligence functions. Having analytics tools applied to CRM allows you to improve commercial performance with a decisive impact on customer satisfaction and loyalty. For example, thanks to Customer Segmentation, you will be able to identify specific segments of customers with the aim of serving them with products and services tailored to their needs and consequently structuring a value proposal and a suitable marketing plan.

Internet of things

The challenge of Industry 4.0 is based on the principle of having a unified and integrated vision of industrial and management processes. The integration in industrial machinery of IoT sensors connected to the internet allows continuous monitoring of the operating status; based on the data collected, predictive models can be developed to optimize the maintenance strategy and identify anomalies, reducing operating costs.

Time series Analysis

When you have a sequence of data ordered by time, different statistical methods can be used to determine the process underlying the time series; this can be useful to forecast future values or to detect anomalies. For example, knowing in advance the specific market trends or how much your products will sell can help the decision-making process of a company.

Supervised Classification

In supervised machine learning a model is built using labeled data, with the goal of learning to make predictions on unseen observations. For example, a churn predictive model can identify customers which are likely to abandon a particular service, helping companies to minimize the churn rate and to increase customer retention. A supervised classification can also be applied on unstructured data, like words and images: for example, analyzing comments and reviews allows to perform Sentiment Analysis in order to understand how much a certain product is liked by the customers.

Get value from the data you already own

Imagine having the ability to predict business results or make your processes more efficient, the predictive models we develop provide these predictions, leveraging machine learning algorithms and statistical calculations to analyze data and search within answers.

Process & Methodology

1. Business Requirement & Data Preparation

Once the data has been collected, the objectives defined, the context analyzed and the needs of your company understood, we prepare the data to create relationships, trends and characteristics to be able to design ad Hoc models and algorithms.

2. Modelling

The best model is identified to achieve the set goals and, according to the result, tuning and performance model comparison activities are carried out.

3. Evaluation

The results are analyzed and the choice of the most performing model is shared with the customer.

4. Deployment

The environments are prepared for the release in production of the model and the monitoring for the Continuous improvement cycle is activated, in order to guarantee your company optimal performance in all circumstances.

Improve your business

The fields of application of predictive models are many, these are just some of the ways in which the use of predictive modeling can provide value to the business, contact us to find out more.


In order to provide a 360 ° consultancy service, we take advantage of YoctoIT's experience and skills in managing and implementing cloud and on-premises infrastructures.

The achievement of the goals you wanted for your company are closer than ever and we will accompany you along the way.

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