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Changing the customer experience approach with innovative retail concepts

A recent Nielsen research highlights new socio-economic and behavioral patterns that are helping to redefine strategies and retail concept: basket reset, homebody reset, rationale reset and affordability reset. These parameters tell us that people are changing priorities and this evidence will necessarily have to lead retailers to rethink strategies and reshape the purchasing experience.

Online and offline environment merging is an evolutionary necessity for retail and benefits related to this integration have been widely processed during pandemic in many situation and use cases, such as: planning online the store visit, pre-order to arrange the in store pickup or to get a personalized service, and so on.

Online and offline integration allows also to pay attention to the importance of loyalty and bespoke experiences and people are appreciating brands that are addressing their focus in this direction.
1 to 1 marketing is no longer a prerogative of offline contexts but digital humanities and complex algorithm are enabling a deep knowledge of customer and a quite fluid interaction between customers and brands.

People have raised the bar of perception regarding the quality of experience and require to have the possibility to carry out part of the purchase process via mobile or through digital and touch-less tools.

As an effect of the pandemic typical digital ways of interactions have been brought into real life and we finally appreciated the value and usefulness of the technologies which previously had little adoption. The QR code has finally revealed its true value proving to be a perfect and immediate bridge between physical and digital that can facilitate the digitization of all those physical media that can be vectors of contagion (menus, tickets, brochures, guides, etc..)
QR code is also the first point of contact in Burger King’s new touchless concept store that will see its first openings in 2021 in Miami and Latin America.
The new concept was created to meet two important and necessary evolutionary objectives:
- React to customers' behavior changes with an adaptive approach
- Resize shops

Emerging innovative retail concepts

In the new Burger King touchless concept store, touch points and face to face interactions have been replaced with digital and touchless solutions. The new retail concept provides a deep integration between online and offline.

The shop, its spaces, have been entirely redesigned with functional and safe approach,  the kitchens have been placed into the funnel according to a delivery logic perfectly connected with a food locker system that effectively closes the experience with automated orders delivery.

Burger King’s new concept store is 60% smaller than a standard Burger King and therefore allows a significant cost reduction at a time when the change in behavior and consumption is constantly evolving.
The new Burger King will also reduce massively the time spent by the public by improving the perception of safety and probably increasing the efficiency and speed of service deliver.

The retail innovation intersects with a great opportunity related to data economy.
Data mining becomes automated even in physical spaces and there is an appreciable adoption of automatic systems for the analysis of flows and customers' behavior.
The real-time generation of data is increasingly linked to the interaction between man and machine, but the crucial point of this interaction is always the experience offered.
The so-called digital humanities that provide visual and textual analysis and powerful research tools represent the most important evolutionary challenge for all those services that put the experience as their differentiating point.

Omnichannel scenario has brought an evolutionary momentum also in  digital technologies that try to rival the real experience leading to very daring experiments ranging from the use of "avatars" to hyper-real representations of 3D spaces within which it is possible to move room after room as in reality or as in a Minecraft style game.
For example, Diesel has launched its Hyperoom, a virtual space where  vendors and buyers are welcomed and the brand offer an immersive experience that allows them to explore and visualize products in every detail.
At the moment it is a project reserved for the community of operators but could also be extended to customers as a new e-commerce platform.

This is certainly a courageous approach consistent with the commitment declared by the OTB, the group headed by the Diesel brand that in its manifesto focuses on the will to innovate, change people behavior, stimulate creativity contribute to social development and support a sustainable economy.

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What happens when AI reach the tipping point?

In the last few years we have seen that social change and consumption behaviour are often characterised by an extraordinary speed in spreading and are able to turn into global phenomena.
From a behavioural point of view, some trends, supported by powerful marketing strategies, have became viral and this feature is very timely and not casual.

The spread of a trend, whether it is fashion, entertainment or lifestyle, leads to intensify the activity of people in some specific areas, physical or virtual, concurrently increases the demand for products and services  connected  to that trend and also the spreading factor of the trend itself.
As Malcolm Gladwell explains in the book The tipping point, once reached the tipping point, you reach that threshold beyond which you can get an avalanche effect.

This phenomenon is evident in the biological processes of virus spread, but it is quite surprising that the phenomenon can be replicated, in almost identical ways, even in the real world especially if assisted by powerful marketing strategies.
When the demand for a service or product emerges massively, the efficiency of the process to access to those resources and services determines the tipping point of spreading and also determines the perceived quality of the service or product.

The gap between supply and demand is no longer an eligible cost as we are now in a time when it is possible to predict how demand will change over time and implement adaptive supply strategies. Predictive business strategies combined with a knowledge of the audience and its behavior are conditions that are determining the success of some realities and the disappearance of others from the market.
Knowing how to grasp, control and respond in a timely and automated way, to emerging questions or to the change in demand behaviour is one of the most important challenges for retail.

The automation of retail processes affects many aspects ranging from the retail and product experience to post-purchase phase and customer care.

Real-time audience analytics, digital shelf strips, interactive surfaces and touch-less interfaces: that’s the way is changing the approach to shape the retail experience.

Automated experiences and retail automation

Automated experiences and retail automation seems to be more and more applied to a wide range of products and services.
Radars, cameras, voice recognition and weight sensors are only some of the solutions adopted to acquire a deep knowledge about context and audiences. This means that control, categorise and analyse is a pattern to generate a chain of events predictable and measurable to perform the retail automation.

This may suggest that, in a daily regime of automated actions and responses,  in order to make the services efficient, there is a risk of making the human experience entangled or filtered though safe and performing.

Artificial intelligence and implications on behaviour and society

We might think that coding  experience in patterns recognisable also for artificial intelligence is leading us to adapt our language to facilitate and support this dialogue with machines. In order to make machine able to recognize and respond to simple or quite complex commands we must somehow transform verbal, gestural and vocal language into metalanguages able to be associated with information and translatable therefore in answers and results.

The integration between the digital and the real world is now fully in place and it is constantly evolving, moreover the training accelerated by the pandemic has produced a vast evangelization of the benefits brought by digitalisation and virtual transposition of some experiences.
It is beyond any doubt that, in emergency situations, digital and virtual are the preferred as well as reasonable way, but before handing over the experience to an automation lived in everyday life it is sensible to make some more reflection.

Pros and cons in experience automation

When the experience is automated by an efficient relationship of dialogue between machine and man the result can be certainly a benefit. These are situations where real-time information is required for efficient management of passenger traffic, situations where it is necessary to preserve specific environmental qualities or situations where it is necessary to reduce the presence of man or his impact on the environment.
Sharing information, acting in a procedural and collaborative way is something that can be reproduced or replicated by a machine and can bring obvious benefits.
Behaving with empathy is a precious attitude that can hardly be attributed to a machine.

When the experience becomes automated without a real pro-social aim presumably we are faced with a controlled and simplified experience moved by disparate purposes ranging from entertainment to pure distraction not properly useful for those who are experiencing it.

Wanting to add a provocative touch but not far from pure reality, we can say that automated experience can also have the purpose of generating data through people.
Such data, as a trace of people involvement become monetizable because these data have the intrinsic power to multiply exponentially on the basis of emotional factors.

And here we are at what may be considered, with discrete and desirable limits, not fully automatizable and that will always have a slight form of resistance to the most efficient prediction strategy: emotions, events, events, real life.

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Artificial Intelligence and Roboethics exercises

Artificial intelligence is a system capable of instructing other systems (software or hardware). Software or machine constitute entities “which are self-instructed on the basis of learned logic”. From this observation we can infer the evidence that in this scenario man is no longer central but a true autonomy of technological systems is appearing. Countless reflections can be made on the principles that guide the design of machines and systems based on machine learning and artificial intelligence. But a digression can also be opened on the ethics of machines

How do ethics regulate the design of technology?

Asimov had already posed this problem by understanding that a system able to educate itself needs to be designed according to ethical principles or very clear laws. In his visionary imagination he formulated the Three Laws of Robotics which were reformed with a Zeroeth Law when he understood the dangerous gap between the public interest and the interest of the individual.

The laws of robotics according to Isaac Asimov read as follows:

Law One – A robot may not injure a human being or, through inaction, allow a human being to come to harm.
Law Two – “A robot must obey orders given to it by human beings except where such orders would conflict with the First Law.”
Law Three – “A robot must protect its own existence, as long as such protection does not conflict with the First or Second Law.”

Isaac Asimov added the “Zeroth Law,” above all the others

Zeroeth Law - A robot may not injure humankind, or, through inaction, allow humankind to come to harm.

Industrial automation, machine learning and artificial intelligence are area of intense research especially moved by the pressing forces of capitalism that aimed at replacing man with the machine or the transformation of man as a user or customer in some form of product.
Without going so far as to prefigure an irretrievably dystopian world, these forces have nourished innovation also moved by a humanistic vision that wants to free man from work replacing human with machines.

We can certainly say that there may be an artificial intelligence that aims to improve human life or reduce the environmental impact of man.
There may also be guiding principles for the design of machines that the major innovators are ready to subscribe as a policy document for the future.

However, some authoritative detractors say that giants of digital technology have implemented what has been called “The Age of Surveillance Capitalism"  (Shoshana Zuboff). In few words, if decades ago the internet and search engines were considered and acclaimed as a democratic medium, a place of freedom, where information flows fast and timely, becomes accessible and global, now clearly emerges the disturbing nature of the rules through which these machines educate themselves.

Web users and more generally people have proved to be inexhaustible generators of what can be considered the new oil: the data.

Privacy, personal data security and anonymity have therefore become a value to be preserved and protected.

The quality of services itself is increasingly attested to its ability to preserve these data and innovation is becoming increasingly oriented to invest in this field. The new real goal for those who deal with artificial intelligence becomes knowing how to collect behavioural data without harming privacy, without threatening the security of personal data and at the same time ensuring  personalised and relevant services.
So many challenges in a single simple purpose that is not so far from an ancient and always valid principle that should regulate the exchange of capital in any manifest form, currency or given. This principle can be very similar to an updated version of Asimov’s previously mentioned robotics law.
Artificial intelligence cannot harm humanity, nor can it allow, because of its own rules, humanity to receive a damage or a false vision of reality.

Shortly, the guiding principle should be a real utility, improved experiences and data security.
Once again, technological innovation can demonstrate that it is capable of overcoming the problem of data breach and can win this challenge simply by ignoring data or anonymising them at source.
Here are two examples that allow us to temporarily identify an active subject, to trace his behaviour but not his identity or his behavioural history. Color mapping and radar imaging allow, for example, to analyse the activity of a user or customer for the purpose of modifying the surrounding environment in which the subject moves or in order to provide him with a relevant experience.
The most appropriate scope for these technologies is the real world, shops, offices and public spaces, places where the real significant contribution in terms of innovation can come mainly from those technologies that are able to not disturb the natural interface of space and therefore of experience.

This kind of technology leads us to imagine a second law for a not dystopian technological world and really guided by an ethics of artificial intelligence.
Artificial intelligence should not disturb natural experience and should tend to have a biometric impact of 0.
From this purpose comes the technology Munogu BIOZERO

Learn more about BIOZERO technology 

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BIOZERO: beyond biometrics

The necessity to overcome biometric data collection techniques is increasingly pressing for legal, social and ethical reasons.
Biometric data are in fact personal data that can lead to the identification or discriminatory use (even in automated way) of such data. The most modern biometric data collection systems can define sex, biological age, physical characteristics, mood and ethnicity.
These parameters can therefore determine forms of identity recognition that contributes in feeding the system that educates artificial intelligence. The assignment of biometric data to specific categories therefore highlights several critical issues: ethics, data security and discriminatory use.

The anonymization of biometric data is a process that is not always conclusive as it is based on forms of data processing and on a temporary storage of this data.
Biometrics can be exceeded in different ways.
Munogu has developed BIOZERO, a biometric zero impact solution based on a range of technologies that includes color mapping and radar imaging.

The color mapping algorithm is based on AI Tensor Flow developed by Munogu’s R&D team. The color mapping technology allows to obtain information typically available only to biometric systems (EG. face detection) through "pseudo-biometric" strategies, without actually accessing data that can be classified as sensitive in terms of GDPR compliance. This allows the emission of a simplified DPIA free of significant hazards.

The innovation driving "Biozero" is the AI algorithm  whose distinctive feature consists in being able to perform the analysis of color picking related to the body track of the user, populate with specific information the icon associated with that specific user and eventually also carry out a check re-identification.
This is the necessary prerequisite to ensure an orderly and reliable flow in the checksum phase (verification). The color mapping technology in fact can be used to manage traffic in public offices and allows to have a queue management system completely immaterial and without physical contact between person and surfaces (contactless).


The Biozero solution can also be based on radar imaging technologies that allow to map a space and identify the position of subjects in the environment, to trace their behaviour and understand how to organise an effective flow without the collection or use of biometric data.

How does BIOZero work?

Biozero is the paradigm of Munogu in the development of Kiosk solutions.
The use of radar-doppler technology combined with a platform for artificial intelligence such as Kiosk, allows to obtain a wide range of advantages:

  • protect privacy: the radars, unlike the cameras, are certified “Biozero”. Radars have no impact on privacy, do not have to anonymize sensitive data, nor transmit them, as THEY ARE NOT ABLE TO GENERATE THEM. This allows to skip the complicated compliance verification process that involves the DPO in the drafting of a DPIA, the legal team and all possible repercussions (and costs) for preventive maintenance related to the eventuality of a Breach date.
  • The way BioZero sees the world: the radars see "natively" the world on a Cartesian plane and are able to precisely place people in space, the cameras must otherwise operate hypothetical approximations based on calculations of perspective, "size" and calculation of "escape points". These circumstances impact on the solution delivery process.
  • BIOzero is useful and not disturbing: considering the organizational criticalities it is important that a technology solution has a minimal impact on the so-called "operations", installation, maintenance and monitoring must be kept to a minimum effort and must allow the exclusion of specific areas from monitoring activity (very complex activity with a camera or with wearable devices).
  • Stay Home: the service works even without connectivity, this prevents any malicious attempt of intrusion into the data stream transmitted in cloud solutions-based and reduces the times of inoperativeness of the service with a significant and positive impact on the processes.

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Bio-metric recognition and new patterns of behavioral data collection

Since some time on we have been hearing about bio-metric recognition and this technology has already been adopted in some airports to speed up transit procedures for passengers. In fact Bio-metric data are personal data because allow identity verification.

Bio-metric devices are actually very popular and are widespread in smartphones to enable the Face Unlock
Bio-metric characteristics can be biological but also behavioral and can lead to identification by performing the comparison one by one.
For example, fingerprints are bio-metric trait and allow identification in the comparison one by one and allow exclusion by making the comparison one by many.
Another example of bio-metric trait is the voice. The voice is the result of physical and anatomical characteristics that determine its qualities.
The most widely treated bio-metric trait is surely the face and requires necessarily the acquisition of an image. There are a varied selection of bio-metric sensors and different methods of data acquisition, however the purpose is common and it is to the elaboration of a mathematical representation (bio-metric model).

What are the risks associated with bio-metric recognition?

Social control, discriminatory use of data and bio-metric falsification should be considered critical and controversial matter, especially when such data are associated with the provision of a service.
Ethnicity or race, physical shape or health may, for example, be subject to discriminatory treatment, or may simply lead to categorization which may be considered discriminatory.
Using bio-metric recognition systems therefore requires the adoption of specific security measures that can ensure the temporary storage of data for the declared purposes and the awareness of the processing by the individual concerned.
For permission marketing purposes, this awareness can be assured by informing about the processing, but when marketing strategies are applied to unknown or unaware subjects it is important to adopt behavioral and visual data collection strategies that are absolutely compatible with the GDPR legislation.

Among these techniques are computer graphics and computer vision which, through the collection of color samples or temporary behavioral information, are able to develop a non-bio-metric mathematical model. This model, therefore, in a one-to-one comparison does not allow to be traced back to the individual when it is outside the specific context of the data collection or when it presents a minimal variation of the data.
That is why we talk about aggregated data that are specifically dependent on environmental circumstances. To give a concrete example, a subject who enters a store with red T-shirt and blue jeans is considered a subject, if the same subject is intercepted after a few minutes with a white T-shirt and blue jeans the computer vision will count a different and new one person.
This model of data acquisition and analysis of behavioral data is certainly more useful and more suitable for marketing purposes and can give the possibility to measure and understand your target audience. The data collection and its organized representation is becoming the main tool to make adaptive any strategy applied to the real world (shops, public spaces and places of transit).
The analysis of behavioral data in the real world becomes timely and always updated exactly as in the digital context.
The result is a huge potential for innovation, ranging from pure marketing to security to pure infotainment.

Learn more about solutions for Customer Data Intelligence

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Body language and computer vision: how the User experience evolves

Facial expressions have been deeply studied and are often the primary source of information related to a person who is being observed. But what changes when a computer observes humans?
The human eye is a perfect machine for analyzing images from a technical, semiotic and emotional point of view, as it is the perfect tool for analyzing body language.
Body language represents first-level information captured by the sense of sight and then translated into rational judgment or emotion by the brain. Let’s try to replace eyes and brain with the corresponding digital technology and we will have a taste of the near future at its bright and dark side.
When we look at an image we can assign it to a category, when we look at a gesture or an expression we can assign a meaning. Sometimes the meaning of a gesture represents a cultural sediment but it can be traced back to a language that is practiced daily and that has now been codified as universal also thanks to digital and media.
The technical analysis of images has long been the domain of machines, but gestures and body movements have become a central point of research for computer vision.
Recognizing the body language through a computer, attributing a meaning to a specific movement means to be able to put in relation and communication the man with the computer, an instance able to process the information, aggregate them, analyze them in real time and manage them to elaborate feedback, specific actions, responses and information.

Re-shaping Prossemic zones with computer vision

Computer vision has also managed in some way to reshape the so-called proxemic zones. To give a few examples, what is defined as an intimate area, closeness, can correspond, in the relationship between man and device, to the recognition and the possibility of unlocking an action or a content. When a proximity relationship occurs in this area we are likely faced with a real interest or a relationship between man and object that can be interpreted as “ownership”.
The intimate space, personal space, the social space, and public space become more and more matter of analysis especially in this recent scenario dominated by the fear of pandemic. People tracking and social distancing measurement are now a prerequisite for public safety and health.

If before the personal and social spaces were to be understood as the distance that we "choose" to put between us and others, now these spaces often become subject to regulation by machines that can technically analyze images.
Undoubtedly if we look at this reality from a perspective marked by the pandemic emergency, what follows is a dystopian reality worthy of the apocalyptic visions of Huxley or Orwell.
If instead we adopt a perspective guided by the light of innovation, the scenario can be the Utopian one in which the processing and technical analysis of images allows to reach high safety standards and high quality standards in services, we think for example of applications of computer vision in the automotive sector, home automation, transport, health and also education.

Natural User Interface and Touchless User Interface

Body recognition, voice, gestures and position detection allow the development of natural interfaces that cancel out any technological interference in the experience.
This leads us to open an in-depth study on the concept of Natural User Interface and Touchless User Interface.
A gesture is a movement of the body that contains information and this is the premise of human language (and animal language in the broad sense) but on this premise is also based the design of services that take an approach that focuses on the Natural User Interface.

The prerogative of this approach is to allow a "seamless" interaction between man and machine by making the interface disappear and leaving only the experience as a form of content to surface.

The recognition of the body and gestures can be based on the use of cameras, sensors or other devices capable of detecting data to which a value is attributed.
This technical analysis of the images or of the movement carried out naturally by the human eye, can be carried out by the machines according to two distinct approaches. An approach is based on the collection of images, which compared to a comparison database allows to attribute a given and a meaning to the image collected. The second approach is based on the identification of the skeleton and therefore is faster and more precise because it is based on points and coordinates that correspond to a gestural encoding well recognizable. This approach is in fact adopted by the gaming industry that can not disregard the speed of response, precision and allows you to capture and interpret a wide range of gestures.

The Touchless User Interface (TUI) is based on the premise that, with the use of cameras, 3D sensors and computer vision, there is an understanding of movement or gestural or vocal actions. This means that no device contact is required but a gesture or voice input can be enough to activate a feedback response of any kind.
Human behavior recognition techniques can be used variously to improve services, make them more accessible and certainly safer from a health point of view.
Learn how using space sensors can improve queue management

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Queue management and impact on retail performance

Queue management now is a crucial issue, it consists in controlling and organizing the traffic flow. Adopting a queue management system also means improving an experience that is generally considered frustrating for the customer and that can have a significant impact on the efficiency of services, the perceived quality and finally affect the sales performance of a store.
A proper queue management contributes to customer satisfaction, improves the efficiency of operations, increases in-store traffic because a lean and efficient queue does not discourage customers.

It has also been shown that good queue management reduces waiting times and brings many benefits, including an increase in average store spending and savings in resource management.
During the days when the epidemic was running fast and relentless we have seen in the world improbable images of endless lines and countless theories on the choice of the best day and time for shopping.
During the pandemic home delivery services were jammed several times and waiting time in some cases exceeded the two weeks.
Anyway, on the one hand lockdown in its drama was also a period of intense training for people who have overcome any reticence in the adoption of online services and on the other hand it was a period of intense innovation with the most disparate solutions and creative technology for queue management.
For example, the observation of queues nearby supermarkets during the lockdown brought virtuous real-time monitoring experiments based on geolocation and the active contribution of users.

These systems, although still in an experimental phase, can provide an estimate of waiting times and based on this evaluation users can choose the point of sale that is more convenient for position and waiting time.
People queuing can provide information and feed the monitoring system and thus contributein provisioning this service to others.
Some shops and public offices adopted queue management systems that implied a necessary reshaping of traffic management. That has means that moments of control, sanitation and have been introduced to maintain saturation levels of spaces within standards and to ensure safety and public health.

How you can measure the health safety standard

The saturation of space and  social distancing are two new values that determine the safety standard but the conservation and control of these standards should be regulated by a correct information flow with respect to the input flows and management of the experience within the store.
With the onset of the health emergency these two standards have been guaranteed by the staff in charge that through solutions of communication between operators exchanged information on the flows of entry and exit to regulate the saturation and adequate spacing in the public space, shop or office.
The door was a passage shared by those who leave and those who enter, now the entrance and exit are different and distant passages. After approximately 4 months of experimentation, retailer have adopted automated temperature checking systems, sensor systems to facilitate proper hand sanitation and systems capable of detecting saturation of spaces that can provide real-time measurement of the safety standard.
This seems to be the new normal in the management of shops but so much remains to explore. This change has opened a scenario for retail technology that can offer new and interesting opportunities.

Discover more about our solution for health care and security

Retail technology: opportunities and benefits

Waiting time in the queue can be an opportunity for retailers to operate efficiently on different levels: traffic segmentation, infotainment, advertising or digital signage in waiting spaces environment.
These opportunities must be understood within a technological framework that allows real-time performance monitoring and measurement of the potential related to physical space and store,
Introducing technology and innovation in retail strategy means easy and centralized data management, targeted management of content and strategies for point of sales or offices, possibility to isolate criticality and correct in a timely manner.

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The key to fight the spread: Behavioral change and behavioral data

Probably the coronavirus will be in the chronicles for a long time but the total closure of shops, schools and offices, limitations on gatherings will not be long protracted without having alternatives. Surely the closing periods will be shorter and the isolation will be targeted.
In recent months there have been many opportunities to experiment with different and disparate solutions to manage the containment of contagion spread , from a total closure approach to the management of a restricted inflow.
What is certain is that restrictions on people’s movements were crucial to curb the emergency.

It cannot be said that it was not a creative period but also dramatic. Many attempts were made to recover a normality that probably has to find a new set-up, a normality that will surely have to be remodelled according to new parameters. We will need a behavioral change that we must hope is evolutionary.
Making predictions on the wave of an emergency is never a simple exercise but now the scenario begins to emerge and after this experience the most effective solutions begin to reveal themselves. What undoubtedly proved most decisive in the absence of treatment was behavioral change.

As Marc Lipsitch, professor of epidemiology and director of the Center for Communicable Disease Dynamics at Harvard School said, there are similarities between weather forecasts spread of contagion forecast and social change forecasts, nevertheless there’s a silver line: "we cannot change the weather but we can change the course of the pandemic with our behavior, balancing psychological, sociological, economic and political factors".
While technology and digital have contributed to changing the course of the pandemic, the resulting behavioral change has also been driven by the re-design of many services.

The key to this technological approach is behavioral data. Let’s see how they can be used
Digital has endured a fast growth in terms of adoption and the ecommerce has become the primary purchase channel for many, recording a physiological increase favored by the lockdown, this means performing a deep traceability of the consumption habits.
Machine learning and artificial intelligence are finding an application in everyday life and are effective tools to make context analysis useful to have a clear view of the changes in place

For example, during the pandemic, some language analysis systems have contributed in providing geo-localized data to identify the critical areas and spread of the contagion.
By isolating strategic keywords in social conversations it was possible to do spatial analysis to create maps and visual representations. This process of collecting Covid-related hot topic data combined with geolocation has led to identify critical areas or define spread dynamics.
Behavioral tracking has always had a dark side but in this case it has become essential.

Many proximity measurement solutions have been developed and the adoption of a wearable device or proximity and contagion risk tracking app has become spontaneous.
To sum up, the awareness that the data on behavior can somehow be the key to fight the spread of contagion is increasingly evident and people are more and more inclined to give these data also because anonymity can be widely guaranteed.

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Shaping a smart connected environment with computer vision

The current ambition shared by those who deal with innovation and new technologies is certainly that of being able to shape the environment in such a way as to make it intelligent, data-rich, interactive, fluid and user-friendly.
The environment we are talking about here is a field in which virtual and real are not separated but totally integrated.

When technology connects virtual environment and real environment

This ideal environment, shaped by technology, is conceived as a space within which human behavior is interpreted according to models related to neuroscience and cognitive psychology.

Let us talk about a concept already known in 2005 as Ambient Intelligence, which then found its natural evolution in the Internet of Things and Computer Vision.
Can we summarize all this with the concept of Context Awareness?
Surely, the ultimate goal is to comprehend the environment, identify specific events and generate contextual content and experience.

Event detection and contextual content.

Algorithms that will be able to establish a relationship between object, environmental situations, space and person can interpret properly encoded (real or virtual) events.
These events can be of extreme simplicity, such as detecting the presence of a person or object in a specific space or their absence at a particular time and under a particular condition.

Computer vision allows to design scalable information architectures that have the advantage of being able to monitor and manage events in an automated but at the same time personalized way.

This is possible because computer vision and Iot are based not only on the knowledge of the environment but also on the knowledge of the dynamics of interaction between man, environment and objects and are aimed at determining systems compatible with natural forms of behavior.

The technology that connects objects and people

The key point remains the way in which man processes information from the environment and also from objects and how its representations turn into reactions to stimuli or interactions.

Computer vision and IoT cannot disregard the way humans perceive spaces and objects, the way they store information, takes decisions or responds to a specific problem but to access this knowledge, technology should be integrated with natural experience.

AI and IoT are based on miniaturized technologies and hardware that can be perfectly integrated with objects and furnishings, and are therefore particularly suitable for environments such as showrooms and shops. The fact that technology is not visible (technology Hidden approach) means that people do not necessarily have to be aware of it or learn how it works. This point becomes very important to preserve the natural experience.

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How Artificial Intelligence can improve marketing strategies

Artificial intelligence is seeing its application in multiple contexts and at different stage of the customer journey or life cycle of a product or service. The AI finds its specific application in both digital and retail making the strategic approach based on the customization of the service more and more effective.

Artificial intelligence makes possible to analyse the context in which users or consumers act.
Behavior Interpretation can be a useful tool to manage targeted marketing actions with a segmented approach. Constant measurements and evaluations permit to act in real time or to make corrective action in the sales or communication strategy.

Let’s see some areas of application of AI

Artificial intelligence as a tool for marketing automation

Social media marketing and web marketing can take several advantages from using AI.
In fact AI can help in
- isolating and segmenting high-value micro-audiences, leading A/B testing or look-alike testing
- carrying out automated implementation of specific promotion initiatives in high conversion potential clusters
- optimizing investment management and avoiding non-strategic audiences

The use of AI in web marketing represents an approach that definitively archives a modus operandi now anachronistic, an approach that we could define "spray and pray" and that is based on a massive and repeated exposure of the message. Today we are talking more and more about ROAS because the control of spending and the measurement of each marketing action are now fundamental because the behavior of the audience is increasingly omnichannel and multichannel.

Artificial intelligence as a retail tool

If the adoption of AI in the digital field helps to segment audiences and to refine marketing strategies, AI in retail can be a tool to improve the service and reduce costs. The adoption of AI-based technologies for retail is among the most concrete strategies in those sectors that see an advantage as a direct return on investment and as an innovation applied to processes.
The adoption of AI in Retail can help in
- identifying the products more attractive or which may be related to other products on the basis of customer interests, events or behavior
- optimizing warehouse management
- Understanding the most effective promotion strategies and increasing margins
- identifying patterns of consumption or correlations between products and carrying out automated marketing actions in real time
- reducing fraud cases and increasing security levels of payments.

The large-scale adoption of AI in retail must therefore be inscribed in a broad vision and integrated with the business strategy. On the contrary, artificial intelligence as a pure tool for improving experience or engagement is a strategy that can hardly be adopted on a large-scale because there is no direct and immediate impact on ROI.

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