Sorgenia - Digital Analytics

Challenge - Understand the "human" side of each user

Sorgenia, a leader in the free market for electricity and gas, wanted to deepen the knowledge of the target audience by collecting different types of information.

In particular, Sorgenia wanted to retrieve qualitative and subjective information, essential to understand the “human” side of each customer, such as the themes and values ​ ​to which it attaches greater importance and psychological needs, to ensure an optimal customer experience in one-to-one logic.

Solution - Neosperience User Insight

To obtain this information we have decided to implement the Neosperience User Insight Solution in the Sorgenia website and Customer Area. In doing so, we were able to derive some propensities and subjective characteristics of users and customers, based on the analysis of their browsing behaviour and thanks to a combination of statistical techniques, Advanced Analytics and Machine Learning.

Neosperience User Insight has allowed Sorgenia to discover on each user:
01

Attention to Consumption

Attention to consumption and expenses, combined with the search for savings.

02

Social
Responsibility

The sensitivity towards social responsibility initiatives and the importance attached to the values ​of the Sorgenia Brand.

03

Innovation and Technology

The interest in innovation and technology and the propensity for smart use of digital.

04

Need for
Cognition

The tendency to seek detailed information and the willingness to thoroughly evaluate the characteristics of products, services, and offers.

05

Customer
Feedbacks

The importance attached to customer feedback and the awards obtained 
by Sorgenia as guarantees of reliability.

06

Need for
Interaction

The need for interaction and the search for contact 
with Sorgenia, combined with the propensity to word-of-mouth and member-get-member.

Impact - Understand to Customize

These new informations allow Sorgenia to enrich its Customer Database and customize communications, based on the propensities and subjective characteristics of each customer, both current and potential, improving its experience and increasing its involvement and propensity to purchase.

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DIMASDIA - Covid19 Detector

Challenge - Providing innovative diagnostic tools

In this period of fighting Covid-19, technology plays an increasingly important role. In addition to allowing the continuity of normal daily activities, technological innovation has also made it possible to facilitate diagnostic and treatment processes in the medical and healthcare field.

To address the emergency, the need emerged to develop a platform that could diagnose Covid-19 beyond traditional procedures.

Solution - A digital platform for the diagnosis of Covid19

Thanks to the Sacco Hospital in Milan, the Italian Auxological Institute, LoopTribe Srl, CRS4, the Lombardy Region, the European Fund for Regional Development and the Veronesi Institute, Neosperience has implemented the DIMASDIA-Covid19 project for the diagnosis of Covid-19 and related diseases through Artificial Intelligence and Machine Learning.

Together with our partners, we have developed two models: one for rapid diagnosis - at lower costs than any other diagnostic tool - of the early onset of Covid-19 through pulmonary radiographs, and another model for the detection of cardiac kinetics alteration.

This model will be further improved to meet clinical standards and made available to all affected facilities through the DIMASDIA digital platform.

Impact - Making the diagnostic process simpler and cheaper

Thanks to this project, the Neosperience group was able to provide standardized and evidence-based tools for the clinical management of COVID-19 patients. We then developed and made available a web platform - based on Artificial Intelligence - capable of assisting diagnosis, follow-up and filling gaps in the history of infection.

In addition, given the concrete possibility of pre-screening at home or in widespread territorial facilities, the application of these models could contribute to making the diagnosis both cheaper and easier to carry out.

New challenges and development opportunities for Artificial Intelligence in Healthcare are therefore opening up: we at Neosperience have decided to aim in this direction, because there can be no medical progress without technology.

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Benetton - Digital Analytics

Challenge - Giving the right value to every customer

Benetton, a company known worldwide for its fashion line, needed to retrieve qualitative and subjective information about users who visited its e-commerce and newsletter, to ensure an optimal customer experience in one-to-one logic.

Solution - Neosperience User Insight

We then used the Neosperience User Insight Solution on e-commerce and other digital touchpoints of the brand.

By analysing the browsing behaviour of users - through Advanced Analytics and Machine Learning techniques - we were able to derive their subjective characteristics, such as their psychographic profile.

Impact - Deep customization of the experience

This new qualitative information allows Benetton to enrich its Customer Database and to customize communication based on the propensities and subjective characteristics of each customer, both current and potential

We have therefore achieved the ambitious goal of improving the customer experience and increasing their involvement as well as their propensity to purchase.

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Alisea Remotair® - Machine Learning & IoT

Challenge - Improve customer service

Alisea is the number one company in Italy in the management of air handling systems. As a highly innovative company in its sector, Alisea has seized the opportunities offered by technologies such as IoT and Machine Learning to guarantee its customers a more effective, safe and timely service, improving the quality and efficiency of interventions by its technicians

Solution - Remotair®

Thanks to Neosperience technology, Alisea has developed a new product line, with the aim of innovating the maintenance and cleaning of ventilation systems. Remotair® allows Alisea customers to implement methods of remote control of ducts and air handling units.

Architecture

Data acquired from an engineered IoT board, made together with Coherency, Neosperience partner for hardware development and prototyping, are sent to the AWS cloud, where they are analyzed and made available as alarms and notifications.

IoT firmware and backend components, using Neosperience Industrial IoT technology, are able to provide a synthetic view of filter status, air quality, and the presence of microbiological threats. In addition, the analysis model through deep learning allows the system to automatically determine the cleanliness status of the pipelines.

Impact - IoT and Machine Learning for smarter management

Remotair® is a clear example of the potential that modern Machine Learning and IoT techniques can allow in the industrial field. Real-time data analysis and the dashboard shared between technicians and customers allow Alisea to:
01

Control

Implement effective monitoring of plants;

02

Timeliness

Proactively intervene in the deterioration of ventilation conditions, to minimize health risks;

03

Intelligence

Schedule maintenance of the systems only when necessary;

04

Savings

Reduce the costs of inspecting air handling systems;

05

Satisfaction

Improve customer and employee satisfaction;

06

Safety

Ensure the best safety and health standards;

Thanks to Remotair®, Alisea is now at the forefront in the development of innovative products and represents an Italian excellence in the application of IoT technologies in the industrial field. Remotair®, unique in its kind, is now a differentiating asset that allows Alisea to stand out from its competitors.

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Intesa Sanpaolo - Insurance Styles

Challenge - Understand the clients

Intesa Sanpaolo Assicura, part of the Intesa Sanpaolo Vita Insurance Group, needed to optimize the use of the information contained within its Customer Database to increase the effectiveness of communication with Intesa Sanpaolo and Intesa Sanpaolo Assicura customers, identifying the insurance products most in line with the needs of each customer and the most suitable relational methods to interact with each other.

Solution - Create new Buyer Personas

To this end, we have started research and Customer Analytics aimed at a sample of Intesa Sanpaolo's customer base, with particular reference to policyholders, aimed to enrich the description of Intesa Sanpaolo's "buyer personas” through qualitative information, in addition to traditional socio-demographic and behavioural information, and to create predictive Machine Learning models for a set of subjective customer characteristics, such as personality and lifestyle, based on the analysis of data already in the Bank's possession within its Customer Database.

The analysis was carried out through a structured questionnaire, implemented on the Cawi detection channel of the Voice of Customer NeosVoc platform, and allowed the identification of the following information:
01

Interests

Lifestyle and interests of customer in specific areas, such as sport, travel, art, health, and well-being.

02

Protection

The customer's propensity to take out an insurance policy to protect themselves in areas of life that are important to them.

03

Communicative Approach

Some traits of the personality of customers use in defining the most suitable communicative and relational approach for each one, such as friendship, locus of control, and attitude towards uncertainty.

04

Insurance
Products

Some personality traits useful in identifying the most suitable insurance products for each customer, such as openness to experiences and sensation seeking.

Impact - Personalised insurance

Intesa Sanpaolo Assicura, thanks to the Stili di Tutela project, has been able to acquire a new layer of customer knowledge, which takes into account their individual differences in lifestyle, personality, and predispositions.

This knowledge has allowed Intesa Sanpaolo Assicura to customise communication according to the “style of protection” of each individual, increasing the value of the relationship with its customers and at the same time favoring the adoption of insurance policies more in line with the needs and peculiar characteristics of each one.

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BNP Paribas Cardif - Voice of Customer

Challenge - Soft Data of customers and prospects

BNP Paribas Cardif, a leading global insurance company, wanted to raise awareness of the brand and, at the same time, wanted to know more about the characteristics of its audience, to improve the effectiveness of its commercial communications.

Until then, Cardif knew customers and prospects exclusively through socio-demographic and behavioural information, linked to the possession of products or the interest shown by users in its offers. Cardif, therefore, did not have qualitative information that would identify the real insurance needs of customers and the type of communication best suited to interacting with them.

Solution - Behavioral and attitudinal analysis

We have created for Cardif the Emotional Check-Up, which consists of a survey aimed at their current and potential customers to understand some of their subjective characteristics. At the end of the compilation, each participant could view their personality profile processed in real-time, and the insurance products suggested according to their distinctive characteristics.

In particular, the Emotional Check-Up has allowed the following characteristics to be obtained on each user:
01

Locus of Control

The perception of the "place" where the causes of the events of one's life reside.

02

Sensation Seeking

The propensity for adventure and the desire to experience new and intense experiences from an emotional point of view.

03

Extroversion

The strong propensity for sociality and group visibility.

04

Consciousness

The tendency to plan one's behaviours and pursue long-term goals with determination.

05

Openness
to the Experience

Curiosity and openness to news and changes.

Impact - Customer-friendly insurance

Thanks to the Emotional Check-Up, Cardif was able to:
01

Personalise
the Offer

Offer each user the most suitable product, based on their lifestyle, their attitude and propensity towards different types of policy, and their level of Sensation seeking.

02

Personalise
the Communication

Identify the most effective message for each user, in line with their fundamental psychographic traits (Locus of control, Extroversion, Consciousness, Openness to experience).

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