We constantly interact – with people, objects, devices, our cars and within our homes.
User interfaces that we interact with, using modalities such as touch, gestures or voice, are frequently perceived as Natural User Interfaces (NUI).
Our interactions become more meaningful if they are natural to and when provoking emotions.
Maybe the best line to describe NUI comes from Daniel Wigdor: ”Content is the interface”, which suggests to remove a layer of the interface, allowing a more direct and transparent access to the content. As the user is interacting directly with the content, it will be the same content to instruct the user about its functionalities.
We were all witnesses of the hyper-awareness of possible implications of touchable surfaces, resulting in behaviour and attitude changes that arrived with COVID-19. Most of the firms involved in touch-linked business turned to a new approach. ”Touchless” future is imminent, and the pandemic just accelerated the transition.
But how can we design contactless, self service interfaces suitable for future users and new experiences?
The answer is simple: using touchless technologies with Natural User Interface.
If we consider human interactions for a moment, (removing ourselves from the world of computers), we will quickly realize that we utilize a broad range of gestures in our daily communication.
The advantages of NUI technologies begin with the sanitary point of view and including 0 learning curve, give possibility to everybody to interact with the technology and use the services provided by it without necessity to learn any new gesture.
They are accessible to anyone. In NUI, the natural abilities of humans become inspiration and model to generate new modes of interaction.
But, how to design the right kind of interaction?
If users find interaction with an interface difficult, their mental effort or cognitive load is high.
High cognitive load means the users have to keep thinking about how to manipulate the interface instead to focus on achieving a task. Users’ cognitive load should be at minimum in order to ensure less effort in the long run and allow us to target a broader user group.
The user interaction design should start from understanding the objects in the physical world.
NUI should be designed in the way the user primarily applies basic knowledge and simple skills during the interaction. This will ensure that the interface is easy to use and learn.
Simple, frequently used tasks should have equally simple gestures to trigger them.
NUI technologies, especially touchless ones, should be accessible to a wider audience, designed to be understandable for all ages and abilities. They can open up computing to new audiences, such as the very young, the very old, or people with disabilities. Creating a successful NUI means that users will decide in a very short time on accessing and using your design.
Designing good NUI means keeping in mind the identity, needs and context of the users every step of the way.
And the most important: great NUI design is about satisfying needs, not outsmarting users.
Some new key technologies are becoming more and more important in the retail business, and companies investing in this area are getting to the next level.
Driven by the computer vision momentum, machine learning, and artificial intelligence (AI), omnichannel platforms are rapidly evolving and impacting retail business, creating both a valuable opportunity to enhance customer experience and an important crossroad: proactively joining this transformation or establishing a defensive strategy to minimize the damage in the short-term.
Consumer retail shouldn’t disregard the possibility to adapt, transform and evolve, and many leading seller players encourage the transition of corporate processes to a more seamless client experience. As a matter of fact, the implementation of new technologies inside physical stores is rapidly interconnecting the offline and online worlds.
Retail technologies play a key role in this transformation, putting together the large puzzle of multiple retail processes through the omnichannel.
The following article introduces the role of computer vision applied to machine learning in the contest of the new omnichannel retail landscape, giving also an overview of the different technologies involved.
How to enhance client experience through computer vision?
The data is the key.
As for the majority of human activities, the success rate is affected by the quality of the data, so taking decisions should be based on facts and verified patterns.
Our data must satisfy the below attributes:
Significance: data able to represent business relevant scenarios. Except in the specific cases, we need to focus our attention on most relevant KPIs and get a clear overview of potential customers (set aside low value data like the color of subject’s eyes):
- Clicks: what are the flows around my location, what’s my location potential?
- Sessions: how many of these potential subjects are accessing my store?
- Bounce Rate: how many of my in-store subjects interact with the experience?
- Duration: for how long these subjects stay inside my store?
Once we get confident with the mentioned plain KPIs, more elaborated data, as the integration with the cash register, can be processed and included.
Substantial: small data slip is expected and not material, my flow analysis won’t be negatively impacted by small counting errors (e.g., 99 subjects passed by but I revealed only 97, or 64 women passed by but I recognized only 62). Our major concern should be the consistency of my data during a certain period of time, consistency that will help me to identify relevant trends in my flows.
Broad: data has to be like puzzle pieces, and the final picture must make sense to my business. The final result is something significant that can help me to take informed relevant decision for my business. It becomes impossible to obtain the mentioned ideal qualitative data, if the system is not able to recognize the number of unique users (for example as per common people counting devices) or the time spent by a subject inside my store or area of interest.
Reliable: often taken for granted, the sensor mechanism must be able to perform in all weather conditions and On Premise in order to minimize TCO; ROI device can work offline, understand and solve possible new issues.
Updated: broader the info receipt and processing, lower will be the reaction capability. Notwithstanding the majority of strategic assessments can be elaborated after weeks or months from the data production, tactical actions require data analysis within few hours.
Data constitutes the puzzle pieces of the customer’s journey map, if these pieces are neither relevant, nor large, nor valuable, it won’t be helpful to put them together since I won’t be able to base my decisions on biased data.
In the next article we will kick off the data analysis method, identifying hands-on KPIs able to produce relevant information for the decision-making process inside-store.
Beauty is in the eye of the beholder, they used to say, but despite this saying, a hymn to freedom of expression and to indisputably of tastes, has always been used in beauty and fashion industry as an excuse for any purchase choice. Today this affirmation seems to be no longer true. Or it is?
The answer is no and the response comes from the color analysis, an image consulting branch that provides a scientific base which defines the concept of beauty in a sector leaded by trends and tastes, drawing up meticulous guidelines for a successful look creation based on the individual chromatic characteristics of every single person.
This theory has its roots in the Bauhaus painting of Johannes Itten, a portrait painter who first realized how the choice of a specific background has a direct influence on the portrait; how the colors of the face in the foreground were enhanced or dull depending on the shades of the season used in the background.
The results of this chromatic research have soon been applied in fashion and beauty field, with the publishing, at the end of 70s, of the book “Color me a Season” of Berenice Kenter, a cosmetologist and image consultant who first formalized the concept of Seasonal Theory, according to which, the colors of the face of a person are in harmony with the typical color of one of the four seasons, which, if used for the choice of garment, accessories or beauty, enhance the incarnate making the face prettier, healthier and more harmonic.
The color analysis, is based on the study of the tones, contrasts and intensity of the colors of the main face elements, which classifies the person in one of the four seasons, each one with associated specific color palettes called friends colors, an actual vademecum for the choice of garment, accessories and makeup.
Despite the principals of the color analysis have long been recognized and used by the field experts, the phenomenon become a trend in Italy just at the end of 2019, thanks to the influencer and image consultant Rossella Migliaccio and the book, published by Villardi, “Armocromia”.
The book, which consists of a manual on the rules governing color harmony and classification by seasons, has become a best seller, creating the term Armofollia.
The phenomenon, which has created numerous image consultants specializing in color analysis to respond to the growing demand, is today a great opportunity for brands in the fashion and beauty sectors to exploit the different potential of the trend to plan marketing capable of attracting consumers, increasing brand retention and expanding the user base with more complete and customized shopping experiences.
The partnership between Munogu with BBC Technologies designed an experience that brings color analysis into the store, using technologies capable of detecting the colors of a face through the acquisition of a photo, guaranteeing a precise and immediate color analysis.
Carrying out an in-store color analysis, as well as constituting an innovative service that responds to a growing demand, represents an ideal drive to store initiative as a starting point for building an omnichannel action that synergically involves the in-store and online experience, with both customer and corporate benefits, by building a new, faster and more personalized shopping experience.
Color analysis would first of all make the customers more aware and autonomous in the decision-making phase, offering a service that, in addition to being engaging, is of effective practical utility, capable of enriching and simplifying the experience in the choice phase and leading to greater post-purchase satisfaction.
The greater awareness of consumers should be followed with a cataloging of products in seasons, facilitating the customer journey both in the store and online, with the possibility of further personalizing the profile, allowing to the users to filter the products according to their “seasons”.
This service, beside constituting, brings an additional value by increasing brand retention and expanding the customer base in the store, influencing both customers loyalty and brand reputation, demonstrating attention and inclusiveness towards all phototypical characteristics, then allowing the company to implement a data collection based on a new objective segmentation criteria and on unchanging data over time, useful for CRM initiatives and personalized advertising.
The theme also acts as a pivot around which to plan communication strategies, involving both influencers and opinion leaders in the sector, and on which to build social events capable of generating content produced independently by consumers, contributing to the trend setting of the phenomenon.
The application of color harmony to the retail world therefore constitutes a fertile ground, still not sufficiently explored by companies, on which to design cross actions capable of making a difference in a period in which the consumer needs a valid reason to return to the store after a year that has upset the buying habits of many, shifting them online.
Therefore, if we have already answered the initial question, highlighting how the purchasing choices are now governed by a new concept of “beauty” regulated by precise scientific rules, another one appears:
“Which brand will be the first to exploit the potential of this trend, making it an important opportunity to grow its business? “
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“Retail apocalypse”, or the end of retail in its current form: it’s a buzzword scaring many decision makers around the world since a few years now.
Statistics and numbers seem to speak for themselves: according to the Osservatorio del Politecnico di Milano, in Italy alone, around 61,789 points of sale disappeared between 2010 and 2018.
A real carnage able to re-shape urban spaces and re-design accessibility to services.
The dramatic crisis linked to the pandemic, moreover, seems to have given a further acceleration to all the processes of disruption already generated by the digitalization of commerce and services.
The New Normal, as the post-pandemic consumption scenario is defined, suggests the affirmation of the paradigm of the “distanced consumption” as the only safe consumption model. Consumers can buy products protected from risks, in the peace of their homes. Especially those with greater economic means and better access to technology seem to prefer this way of shopping and this is why I derived the concept from the “conspicuous consumption” theory introduced by Veblen.
Which other instrument guarantees better remote access to products and services, if not the web?
That’s it. Period. Traditional (physical) retail to have entered a process of irreversible decline.
But is this really the case?
A recent research by Kearney has shown that about 81% of GenZ still prefer to shop in physical stores, even though e-commerce remains the most selected channel. According to the results of this research, traditional shopping allows young people to discover other products more effectively than the digital world and enable GenZ to disconnect, at least temporarily, from social media. Brand flagship stores stand out in the ranking of the most loved shopping formats.
McKinsey, too, through a recent survey focused on grocery sector, explains how consumers have massively turned to online shopping driven by the COVID emergency. Online sales scored record growth rates, in Italy, even by up 100%. But the trend is momentary and return to physical shopping is expected, with negative outlooks for the percentage of online sales in almost all EU-5 countries.
The record shows, therefore, that the next big real thing will be omnichannel shopping, in which online and offline shopping experiences merge into an “infinite customer journey”. The consumer will move fluidly between digital and physical shopping formats. Likely, the conclusion of the purchasing process will progressively move online, but the level of service guaranteed to shoppers will have to be structured in such a way to replicate the physical experience online, while the in-store experience will have to be totally integrated with the digital one.
@Munogu we believe that the near future of retail will be the Omniexperience, well beyond pure omnichannel.
Omniexperience represents a “frictionless, unified and highly engaging” shopping experience, designed around consumer’s needs, where all the “touch-points” are connected thanks to Technology, Marketing and CRM.
“The store” will be transformed into an “agorà”, i.e., an open platform, within which all consumers may experience and discover products and then buy where they prefer. The flagship store must also turn the values of the Brand it represents into tangible experiences.
The final objective on the omniexperience strategy is the creation of a greater value for Companies, through the maximization of the Customer Lifetime Value (on-life customer).
To cope with the requirements of Omniexperience, the physical retail space will have to take on the connotation of a “deeply experiential context”.
By no means should this experiential context simply become a space filled with technologies that are an end in themselves and unconnected, as if they were a pure divertissement to provide interesting ideas for PR offices.
Following the “hidden technology” paradigm, a theory that has always inspired Munogu’s solutions, to be successful technology must be put at the service of the consumer without ever becoming invasive. Overwhelming and not user-centric approaches will otherwise create an over-complex environment that goes against the logic of a fluid shopping experience, that is required by the omni-experience business model. To be effective, the “wow effect” must be conceived with the only objective of converting, not of merely surprising our customers.
Unfortunately, little time is left to companies to re-model their obsolete customer journeys. The market environment has now become impervious and totally unpredictable.
Already back in 2019, taking only the Fashion Industry as an example, customer retention rate was close to 91% for those retailers with effective omnichannel strategies while it stopped at 39% for players without an omnichannel approach.
The “new normal” will open a further furrow between companies that are able to meet consumers’ changing habits and those that will simply sit and watch the number of their stores and their market shares shrink.
To speed up the transformation process, it is necessary to quickly acquire the tools and the knowledge to ensure a transition toward the “omni-experience” model, while maintaining a positive ROI.
This innovation process must start with the implementation of new technologies for retail analytics.
As for digital also for retail “data” are becoming the cornerstone of every strategic decision: advanced retail analytics must be quickly integrated into the infrastructure to obtain irrefutable information about the target, its purchase funnel inside the store and about the performance of retail spaces and their layout.
Thanks to its ability to combine in a single AI-tool advanced retail analytics services (biometric and non-biometric) and unique, simple and innovative in-store experiences, that put in constant relation the physical with the digital, Kiosk, the omni-experience enabling technology suite by Munogu, has earned a prominent place in the Microsoft Technology Center in Milan and a prestigious clientele that includes, among others, FCA, Scavolini, Breil, Porsche US and Poste Italiane.
Start your omniexperience revolution today, as tomorrow it will be too late.
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In 2020, e-commerce sales accounted over 15.5% of retail sales worldwide. In terms of purchases 1 in 4 occurred online, in 2021 is estimated the year-over-year increase at 4,4% (source: Statista).
A growing number of commentators and studies agree on the downsizing of the “Retail Apocalypse” scenario in favor of a radical paradigm change, already underway, which redefines some basic concepts, as Luca Innocenzi effectively analyzed in the article “Retail e COVID – speranze e strategie“.
The reality is that, in any case, even in the worst and least probable scenario, Retail will still represent the most important slice of turnover for most brands. It will remain at the center of business strategies and if anything trying to “unite per osmosis ”online, through cultural reconversion projects within the company and sensible investments in the context of omnichannel-oriented integration.
Retail is not over, it just needs to be rethought.
Starting from this assumption, the most shrewd Retailer can only choose to start a path of knowledge and awareness, first of all wondering what are the practices and tools that can be “borrowed” from online and specific benefits that can derive from them.
Now let’s try to ask ourselves this question: is it permissible in 2021 that any ecommerce site can do without an Analytics Data Driven system? (for example Google Analytics just to name one of the most popular).
Clearly not, not even the most irrelevant ecommerce site would consider it an option.
An analytics system provides increasingly in-depth and articulated metrics: number of accesses to the site, content seen, days, hours, locations, devices, gender, age group and other relevant characteristics of the audience. These tools became part of our daily life, explaining to us in detail who our customers are, what they expect and if they appreciate our initiatives and our products.
Why do we consider them fundamental to develop 15.5% (on average) of turnover and for the remaining 84.5% we perhaps just aggregate statistics on sales or use trivial instruments?
Logically (and depending on a budget), we should first of all worry about overseeing that 84.5%, studying it, protecting it, understanding it if possible and developing it in a “customer oriented” perspective, as we normally do on the e-commerce site.
So why does it still happen so timidly among large retailers? Leaving aside all the secondary reasons, it happens for two kinds of reasons.
1 – implementing an analytics system on an ecommerce site is relatively cheap
It is a simple calculation: if to implement an online data driven strategy it is necessary to spend a lot, hire specialists, consultants, invest in platforms etc, the cost is unique, its impact on ROI compares entirely with that 15.5% in revenues, presumably growing.
On the other side, the monitoring of each individual physical store cannot be centralized, has internal costs and the overall investment is, at least, the sum of those of each individual store. For this reason, it is essential that the cost of adoption and possession for a single store is sufficiently low to be comparable. Once aggregated, with the online one, on the basis of a proportion that compares the levels of overall turnover and does not neglect to consider the additional advantages deriving from the union of the two datasets within a single omnichannel Business Intelligence ecosystem.
Let’s take an example:
If total turnover is 100, and Google Analytics contributes in a decisive way to produce an average increase of 4.4% per year on the online, the utility threshold of the investment will have to remain as widely as possible below 2-3%. of that 15.5% of online turnover, to ensure a positive ROI.
The rational retailer will be willing to invest a maximum amount between 0.31 and 0.465.
2 – the data production tools have not proven themselves
Once the relevance and value perimeter of this instruments has been clarified, the topic shifts to availability: Are there any instruments that can guarantee data consistency, total costs of ownership below the ROI threshold levels, low impact on processes and infrastructure costs while ensuring data readability, protection of customer privacy, opening up to different technological ecosystems, extending the scope of intervention to contexts such as Smart Digital Signage and user experience, all integrated into a single platform?
Well, I’m not going to answer this question, because I guess you did it yourself.
The spread of COVID-19 has led researchers and companies around the world to speed up innovation and exploration of areas with a huge potential for technological evolution.
The areas of challenge are mainly oriented to mitigate transmission, facilitate the detection of the virus, understand the social and economic impact and define new behavioural patterns, new systems to regulate transactions, to deliver products and to improve efficiency of services.
The number of scientist and researchers active today in every part of the world to face the pandemic is very consistent. It is noteworthy that many scientific papers on the topic Covid have numerous and interesting connections with topics such as “machine learning“, “artificial intelligence“, “deep learning“, and “neural network“.
COVID-19: The fields of application of AI in medicine
Artificial intelligence finds its applications both in medical and social field. We should not forget that the main factor of spreading for COVID-19 is represented by sociality and contact with other people.
In medical field, for example, machine learning is used to understand the level of infectivity of SARS-Cov-2
- parts of coronavirus’ protein sequences that are most associated with high case fatality rate (high-CFR) are identified
- machine learning is used to implement an interpretive technique that will allow the identification of similar cases with a high "potential".
Another example is the monitoring techniques that makes use of Computer Imaging techniques.
Medical images of COVID-19 cases (x-rays such as x-rays chest or kidney function test charts) are classified and used to identify other cases, help doctors to interpret the course of the infection and act in a preventive manner.
This information is also a further source of research and learning that can easily be pooled to develop new strategies to combat the pandemic.
Infodemic: a threat that comes from the web
Artificial intelligence can also be applied to assess virus containment models and public policy choices.
For example, we can identify similarities or differences in the evolution of the pandemic between different regions and the connections with the propagation of disinformation, antisocial behaviour or hate campaigns.
These interpretative strategies based on information and language monitoring have made it possible to detect another type of social virus linked to language and information. Let’s talk about what has been called “infodemic*"
The experts have identified an Infodemic Risk Index (IRI), to quantify and understand the exposure rate of a country or region to messages associated with the phenomena of hatred and infodemic conveyed through the main social platforms. The identification of trends in conversations and the identification and classification of the main sources (verified users, reliable or institutional sources, bots or users that, in relation to the high number of posts and type of content, can be considered as unreliable) allows to contain the risks of a further expansion of COVID-19 linked to negative behaviour and misinformation.
The World Health Organization is proactively observing the phenomenon of infodemic because it is closely linked to the course of the pandemic and has important implications for the spread of the COVID-19 virus.
COVID-19 and Infodemic can advance proportionally and with close correlations and for this reason once again the role of Tech Giant becomes crucial and controversial.
*Infodemic: an over-abundance of information – some accurate and some not – that makes it hard for people to find trustworthy sources and reliable guidance when they need it” and deems it a second “disease” which needs fighting (WHO)
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Human-computer interfaces are changing the way real-world experiences take place.
When we want to establish an interaction between man and machine, we see cognitive questions taking place on both sides: machine and man. On the one hand the machine is required to understand on the basis of what previously learned (machine learning), on the other hand man is required to limit and simplify the language and interactions using voice commands, tactile and gestural without any interpretative variant. Smart speakers, which have now became very popular, or other ASR (Automatic Speech Recognition) are based on grammar, lexical terms and acoustic recognition modules, these systems have taught us to express ourselves in a simplified way.
The success of these ASR tools is due to the fact that users can interact directly with the computer without using an intermediate device (eg, mouse, keyboard), without particular technological expertise, actually reducing the grammatical structure of language and lexical quality to the absolute essentials.
It is not a coincidence that even babies, just one year old, can interact with these tools and from different fronts has raised the doubt that these tools can give rise to cognitive or behavioural distortions. Others wonder how children interact with this type of technology, how these tools can affect baby’s development and the quality of their interactions with people, others study the way children try to conceptualise these tools, for example by imagining that there are small people inside or that they are objects with a personality.
But let’s leave this discussion to psychologists and educationalist and let’s go back to the center of our theme: how natural users interfaces can improve the way we experience the real world?
The naturalness with which children are able to interact with these systems actually leads us to reflect on a critical success factor that characterises the systems based on NUI design, this bring us to an assumption that we can formulate as follows: The more the interface looks natural, the more you can hope that there is a spontaneous adoption or a fruition without unexpected or friction.
The first question to be asked in the design of these NUI-based instruments is the nature of these interactions (vocal or gesture): which interactions can be considered natural? The "naturalness" of gesture-based interfaces very often configures and manifests itself effectively when interpreting actions that the individual naturally performs to manipulate an object physically (e.g.: swipe). Then there are gestures that we can define arbitrary but used widely (e.g.: like, thumbs up).
These are just some of the aspects that compete in the design of a system based on AI and NUI but for all the real test remains linked to the ability to trigger a fluid experience, correct and without cognitive efforts. This scenario brings us back to the possibility of reducing the behavioural exceptions in the experiences offered in a store or in a public space and thus reducing the management costs of these exceptions.
We use the body as a tool to generate basic information: presence or our absence for instance. This simple information produces an automated reaction (for example opening, closing, switching on, switching off, etc…). But when the body, movements and gestures generate more complex and comprehensible information for NUI and AI-based systems, we can talk about language, that language that no longer produces simple automated reactions but real collaborative interactions with machines. Systems based on AI and NUI applied to the real context allow to promote virtuous changes especially in situations such as the one we are living in where individual responsibility must be accompanied by a constant behavioural education. AI and NUI based systems also allow to detect, correct and discipline behavioural anomalies.
Interacting with the world now also means interacting with the digital world, it paradoxically means being present simultaneously in two spaces, the real and the digital one where our presence and our interactions, appropriately codified, can be observed and interpreted.
Without venturing into the daring undertaking of combining quantum mechanics with digital, we can be satisfied with a clear perception that derives from new experiences induced by the speed of communications, from accessibility to information, the need to reduce contact and presence in the physical world. It is clear that we are increasingly inclined to interact and use multiple and different dimensions, we are increasingly accustomed to omni-channel and multilevel experiences, and we are experiencing dimensions that need to be understood, coded and "exploited".
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The pandemic has redefined countless parameters that previously regulated quality standards of service or experience. What is effectively a tough challenge for companies is also a unique opportunity for retailers to reconnect with consumers in new ways.
– enabling omnichannel technologies in store
– apply measurement criteria to the environment within which the experience takes place.
In this scenario Munogu designed Space Saver, a technology that helps to manage in store social distance and at the same time analyzes quality and performance of the environment.
The Business Intelligence system integrated in Space Saver is aimed at achieving the following objectives:
collect actionable data: data collected by space sensors placed in the environment (office or shop) are pre-processed and then sent to the aggregator which in turn, on a daily basis, makes them available as Json like data source for BI system.
The data source is then analyzed by BI to provide a "dashboard" from which you can quickly obtain key information selecting geographic clusters, tags of groups of stores, individual shops and/or specific time ranges.
extendibility and integrability: the information structure of data sources and the Json like approach allow the use of data sources also in external contexts, for example in other BI systems (Kibana, Data Studio, Klipfolio, Tableau, etc...).
decoupling of the BI system from the data production platform: the infrastructural separation of the system that produces aggregated data sources and the data production process mitigate the entropy. This approach allow to modify the adapters system without impacting the service delivery system.
TCO containment and scalability: the pre-processing activity allows the efficiency of the data aggregation process, this means a peer-to-peer-inspired design that allows a reduction of the central processing costs and an improvement of the fault tolerance even if one of the nodes (office or shop) is temporarily unavailable.
creation of a proactive reporting system: in addition to the BI system for specific and extemporaneous investigations, it is possible to set up a system of "triggers" (cd. "dynamic reporting") that allows the BI system to send, periodically and independently, specific notices on the most significant trends associated with KPIs and to suggest coded "next best actions".
Let’s look at the "value" elements of the Space Saver suite in terms of significant and measurable contribution to the improvement of business activities, with reference to:
- environmental productivity indicators (informative contribution).
- efficiency of service and support staff (process contribution).
- moral suasion strategies (cognitive contribution).
Space saver’s Indicators design is driven by the goal of providing practical and relevant tools for making critical decisions in a data-driven context.
Instantaneous and periodic generation of environmental productivity indices
The Business Intelligence system integrated in the Space Saver suite provides retailers with the following indicators:
TUI productivity index (Utilization Rate): identify environments ( e.g., shops or offices) with differential performance (best/worst) in terms of the ability to manage the inflow and journey of customers and to standardise an assessment process of the economic exploitation of spaces.
What decisions help us to make?
TUI informs us, with a "journey centred" approach of which shops are most under pressure in terms of inflow.
IDS Security Index (Social Distance Index): identify environments with criticality (best/worst) related to social distance policies.
What decisions help us to make?
TUI IDS informs us, with a "journey centred" approach of which UP have the most critical issues in terms of compliance with the policies on physical distance and the relative degree of such violations, enabling us to intervene specifically in the areas where risk occurred.
Safety productivity index TUI-IDS
Identify environments with critical performance in terms of the balance between store performance and the ability to manage social distancing policies.
What decisions help us to make?
TUI-IDS informs us, with a "journey centred" approach, of which store record the highest/lowest number of violations of the rules on distance and whether these are attributable to an underdimensioning of the store compared to potential users or other factors (poor care of care staff, poor cultural propensity to follow the rules, etc.).
Efficient contribution to service and service value
With the adoption of Space Saver services, the aim is to encourage the work of service or assistance staff in the shop and to equip themselves with the tools to assess their effectiveness without impacting on the prerogatives and procedures that are already implemented at the point of sale.
The optimization levers are:
evaluation: to create a tool for assessing the efficiency and effectiveness of the operator’s action.
motivation: the operator, aware of the monitoring programme, is likely to be pushed to improve his performance, the possible use of moral and/or economic gratification programs could also add elements of gamification capable of triggering further virtuous patterns in terms of impact on the operator’s commitment.
tools: equipping the operator with new intervention tools and support to his activity
automation: the partial automation in hazards reporting processes and access rules introduced with Space Saver allow a lightening of the pressure on the operator, an objectification of his intervention and the partial elimination of a series of interventions that expose the operator to proximity to customers.
Strategies of moral suasion (cognitive contribution)
Space saver is a system that can implement moral suasion or behavioral change strategies.
The presence, explicit and communicated, of a automated system that detects violations of the rules on social distancing, can trigger a preventive behaviours of self-censorship, meaning a natural propensity to observe the rules.
Discover more about Space Saver
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Minimize physical contact and maximize contactless intraction is the main objective of organizations.
This priority concerns many sectors and we are experiencing a deep change never seen before with linked implications at all levels.
The rising attention on risks about privacy and cybersecurity for instance are consequences of a massive transition from actions based on physical contact and presence to touchless and digitized actions, such as voice recognition and face recognition through computer vision.
This forced transition has brought a huge evangelization about advantages due to the adoption of touchless technologies, we can count a large party of enthusiastic adopters and an equal large party of individuals worried about data protection and privacy.
Technologies based on computer vision and AI collect images, interactions and voices from real world, and transform them into data, therefore the data processing is always under the critical question: will the data be processed according to honesty principles, lawfulness and transparency for the protection of privacy?
In Italy for instance despite of a good willingness to adopt touchless practices and technologies in the future, it keep on lasting a strong opposition toward facial recognition, unless strictly necessary for identification process.
A recent research by Capgemini attests that 55% of consumer consumers would avoid a store if it was using facial recognition to identify them and 66% of consumer prefer to use mobile apps at physical locations such as stores and bank branches instead of touch-based alternatives.
To keep users satisfied with technologies over time and to undermine understandable distrust of computer vision-based recognition technologies, it is important that companies are committed to maintaining high quality and relevant experiences, in few words companies should work to offer a tangible value to the customer.
The pandemic has been the main catalyst for all the technological changes we are seeing in retail and many behavioural changes induced by an unprecedented mindset that gives absolute priority to safety and health.
The pandemic is undoubtedly the main accelerator in the adoption of touchless technologies:
77% of consumers expect to be able to use touchless technologies on a daily basis to avoid interactions that generally require physical contact*.
Another interesting fact is that the behavior based on non-touch practices will remain even after the pandemic emergency because the advantages of these solutions have been grasped (vocal interfaces, facial recognition, mobile-based applications).
Implementing and adopting large-scale technologies that meet this public demand requires a long-term vision and strategic plan with two imperatives:
- adopt a test and learn approach
- adopt a data-driven approach
The real change that is expected is therefore in the organizations.
Monitoring the experience and learning and collecting data is as crucial as observation of people’s behavior, the way in which people welcome new interaction solutions can be measured and analyzed and, on the basis of this constant practice, it is possible to gather insights to guide future choices and improvements to be implemented in the adoption strategy of these technologies.
*Capgemini Research Institute, Consumer Survey, April 2020, N=4,818 consumers
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