AI Vision and the Total Retail Experience

The Retail world knows for sure that a growing number of consumers do their shopping both online and in store. There is mounting evidence that these omni-channel buyers tend to be loyal customers and buy regularly from the same source as long as the retail experience they get stand up to their expectations.

The challenge now for retailers is to create an approach that will provide customers with a seamless, personal and unified buying experience irrespective of the channel they use. This will include sales, marketing, after-sales support and the entire customer journey.

In short, the Retail Experience that shoppers get is what retailers have to now focus on to get their act right. How does one deliver the desired experience to the Customer? How does a Computer Vision platform, such as AI Vision, help in meeting this challenge?

Knowing your Customer and Building Loyalty

You have a head start if you know your customers intimately, which channels they use, what are their preferred products and brands, which promos have influenced them the most and so on.

An artificial intelligence-backed smart store solution is what will get you insights on specific customer preferences. In-store camera systems aligned with AI Vision software and Cloud analytics will provide a comprehensive analysis and feedback on shopper behavior and buying habits.

Apart from operational benefits like optimal product placement and targeted advertising efforts, this AI platform will enable you to not only create a marketing strategy involving a 2-way integration between online and in-store purchases but also personalized strategies for loyalty programs that meet specific preferences.

Loyalty programs are today used strategically in the retail world to deliver experiences that are strongly personalized and connecting with the customer engagingly. It is loyalty initiatives that help the retailer to understand more about the customer and actually drive personal and continuing engagement. Today’s customer also craves for exclusive offers and rewards, even if it features just a free delivery of a small order.

Out of Stock situations

One of the most annoying problems faced by a shopper is to discover that a product he wants is not available. Very likely that that he checked out the product details online and visited the store to take a closer look. But maybe due to unexpectedly high footfalls that day the stocking levels fell short, and resulted in leaving the customer very frustrated.

What AI Vision does is monitor the inventory at the aisles in real time and alert management of shortfalls from threshold levels. This is just a small part of the total business solution that the platform provides. The vision-based monitoring also helps draw up models for stores of a large chain, for example, at different locations to predict peak load hours and store-specific demographics, which will ensure proper staffing. In a restaurant the monitoring can extend to hygiene and sanitary procedures and alerting in real time any issues that can cause customer dis-satisfaction.

Value for money

The best part of AI Vision as a tool for harnessing the capabilities of the technology is that it is easy to deploy, avoids huge capital investments and is cost-effective. It can utilize existing camera networks and become, in quick time, a practical solution for resolving several challenges that a retail business faces in the real world. No need to have an IT department or software personnel at each location.

Cogniphi’s AI Vision is one such ready-to-deploy platform that has a tested record of having enhanced the Customer Experience for many retailers globally. Click here to become part of the smart retail world.

How AI Vision can be critical in making the Mining Industry sustainable

How AI Vision can be critical in making the Mining Industry sustainable

Mining is a strange sort of industry. It is actually a cluster of processes that enables the world to obtain materials and minerals that cannot be created or manufactured or grown through agriculture. By definition it is the extraction and management of minerals from the earth’s surface, and it has been the core industry of most economies in the world.

Sustainability the primary challenge

Sustainability has in recent years become the biggest dilemma the mining industry faces. The most worrying factors are: Environmental regulations and nationalism have created a major impact. Resources are becoming scarce and more costly to access. Shortage of skilled labor is another major concern.

Miners need to Re-Calibrate

The commodity boom peaked just over a decade ago. Since then the headwinds have been growing in strength. The mining industry has been forced to re-calibrate and re-think. Some of the key recalibration action points revolve around these aspects

  • Access to renewable energy sources, reduction in carbon footprint
  • Lower water consumption, lower environmental impact
  • Re-usage of materials, reduction in waste
  • Transparency in operations, reduction in geo-political risks
  • More  R&D, new avenues to increase sustainability
  • More automation, increase in operational efficiency and safety
  • Adoption of technology in several processes.

Cameras are no longer just for security

Cameras are in use today, not just for security but for improving quality of life, anonymously

It seems you just can’t escape a camera these days.

Rewind to the past…the camera pointed at you was, more likely than not, a surveillance camera aimed at detecting crime or for some form of monitoring, or a security camera that was part of a system for ensuring public safety.

Come to the contemporary world…the camera is more likely to be collecting data that will end up being used anonymously in multiple ways to make your life simpler and more enjoyable.

Anonymised Data

“Anonymously” might sound negative, but here it actually refers to the fact neither the system nor the camera has to know who you are or what you do. When it is serving a good purpose and things are done in compliance to data privacy laws, what matters is that such data capture can be immensely society-friendly if the intent is good.

Take a simple example. A metro rail system may be using Cameras, powered by Artificial Intelligence and Computer Vision, to analyse traffic congestion on the platforms. The video analytics run on the data captured by the cameras may help the system adjust schedules or make operational changes that will enhance customer service. Data can be collected in such a way that it can never be linked to an individual, even if the software identifies the gender or age-group or the kind of dress he or she is wearing.

Elsewhere, the camera network on a factory floor may be simply helping to keep workers out of danger around active machinery or collecting data on their movement patterns. Today, by studying people’s behavior in several related situations, Computer Vision and AI help understand and predict human-machine interaction more accurately than ever before. Pro-active measures based on such data helps eliminate unsafe practices or work flow bottlenecks.

To demonstrate how cameras can be used to enhance productivity in factory floor
Cogniphi AI Vision used for enhancing productivity in factory floor

Technologies like Cogniphi AI Vision have enabled leveraging an existing security camera system to create dedicated video analytics platforms that benefit a wide range of industries, from manufacturing to retail to transportation to health to smart cities. If they are designed for Data privacy compliance and runs within a private and secure environment, these technologies can produce highly accurate and protected data that is committed to maintain anonymity. And they require very little hardware investment to deploy.

It’s the demography that matters

When a Video Analytics platform, say, tracks a Retail shopper, it can filter out personal data like facial features or how they walk, and focus on collecting and processing information like age and gender, buying patterns, time spent on comparing products, behavior and emotions at point of sale, and so on.

For the retailer too it is user behavior at a demographical level, more than unique identification, which will provide insights that matter to him. The store, for example, may want specific information on the type of shoppers usually passing through Aisles 5 and 6 so that it can plan targeted advertisements there aimed at a particular type of clientele.(For more info : AI Vision for Retail industry)

In the end, it is a win-win for both the retailer and the visitor. The retailer gets to understand customer behavior so that he can design better and more relevant promotions, marketing initiatives, A/B testing and performance tracking. The visitor gets overall a more interesting, pleasant and engaging experience.

Impact on RoI

Users of technologies such as Cogniphi AI Vision are often able to make decisive and impactful moves soon after they realize that the data thrown up by the software is consistent, reliable and accurate. Some of these insights might actually challenge several assumptions but they eventually lead to big gains, particularly when these products get to be used in multiple locations.

 Ideally the platform must be fully software defined so that capabilities can be added on later and data can be collected on a rolling basis when needed. It is when the customer gets this sort of flexibility that he will start relying on data for most of his decisions and feel the impact on RoI. 

Be aware of the practical side of AI implementations

Overcoming the Hype

Accessibility of useful data, heavier computing power and advanced algorithms have in recent years resulted in companies looking at AI to help drive efficiency, cut costs, increase revenues, automate routine tasks, improve employee experiences and understand their customers better. More and more use cases were also being conceptualized for strategy and innovation by a large number of corporates globally.

Major investments were made in the past across multiple industries to try and utilize data and AI strategically. However, several companies who initially scrambled to implement AI in their organizations did not eventually get to enjoy the benefits they had envisaged at the start. This lead to fears, somewhat justifiably, that AI is over-hyped. Of course it was over-hyped then.

AI-Ups and Downs

AI went though many ups and downs. It took several case studies and analysis of companies, people and systems deployed in AI projects to understand that the problem in most implementations was a basic lack of understanding of what AI is capable of, how to practically leverage data, and what the dangers are that need to be side-stepped to ensure real value for the business.

The fact that AI was hyped and why it was so has now created an appreciation of the need to implement it properly, but also a fresh awareness of its huge potential and how it can be a real value driver if done properly. Businesses today widely accept the fact that they must adopt AI strategies in order to compete. But they also need to beware of the pitfalls in going ahead without a clear cut plan or process.

How you Approach AI is the key

AI has proven its value across various sectors in multiple industries. While more and more use cases are being addressed by AI, an Accenture survey in 2021 revealed that most organizations are barely scratching the surface.

Even before the pandemic hit it was evident that many businesses were achieving significant RoI by rolling out AI beyond the pilot stage. During the last couple of years AI transformation became the very means of survival for many, whereas for others it became a catalyst for growth.

But what was the secret to these superior performances that have set new standards in AI implementation?

What set them apart is how these companies approached AI. They did not just adopt the Cloud and start using AI and data solutions. It is more about how they put a lot of thought into it, analysed the organization and the business environment and the pitfalls, and strategized before they actually tapped into any of the widely available AI technologies. The successful AI achievers were those that put people and systems first(digital transformation strategy), and technology later, and who looked at AI as a differentiator to stay ahead of the game.

The Strategy

First, do a holistic research and determine what AI can and cannot do for you. What exactly do you want to achieve? Is it to solve a problem, or to tap an opportunity, or get new insights, or is it for a total reinvention of your business? How and where to start, and what are the difficulties? Pick the brain of a data scientist if you can associate with one.

Draw up a list of potential use cases and a roadmap including a long term vision. Priority could be the low hanging fruits, the easy wins. Most importantly, understand what type of data is available and where, and what are the additional types of information that needs to be tracked to implement the chosen use cases.

The Team

You may not have all the required skills in-house to implement AI. Building a team or finding an AI partner with the desired capabilities is another important step. In fact, building the right team with the same mindset and personal skills to work with the rest of the organization can be the most critical factor in the long run. Businesses need to understand that this is not an isolated project but an integration of a new and soon-to-be-scaled AI platform into an existing IT eco-system.

The quick MVP and Roll-out

Develop the solution to your first business problem quickly, ideally within 2 to 3 months. This MVP (Minimum Viable Product) should have enough functionality, value and benefit for the user to sustain its usage and also a feedback loop to enable further development. Engage an expert who is savvy both technically and in the business sense. Sit with him and define the key performance parameters over the initial roadmap period. Review these regularly and modify them if necessary down the line.

After the MVP has demonstrated its value and been evaluated, prepare to rollout on a broader scale. Utilize your AI partner’s expertise and experience to keep in perspective both the technical and business factors during the implementation stage.

Addressing some typical problems

Organizations heading for AI implementations must give due consideration to these important issues they will face for sure.

Reluctance to change – This is an age-old management problem, but for AI implementation it refers to changing your decision making process into a data-driven one and not just based on instincts. To overcome this, some visible and measurable benefits have to be revealed early. That is where a quick MVP in a particularly relevant use case will help.

Lack of involvement – The users need to feel they are part of the solution and not being forced to adopt something that is being imposed on them. The environment has to be such that they are well taught and feel themselves to be joint architects of the project. Set realistic expectation levels and a roadmap for achieving results. Support of key management personnel and stakeholders are also critical for creating the right environment.

Quality and availability of data –No doubt that clean data is a key factor. So, centralized monitoring and control to obtain incoming data in a standardized format is absolutely necessary. There is also the challenge to locate and keep track of the right data and how and where it is stored. Do not go for complex machine learning models and stick to simpler solutions, if you do not have enough good data or sufficient labeled data that can be used to train the system.

Skillsets and Infra for implementing AI – It may be less challenging and cheaper to outsource than form a huge in-house team. In any case you need to do an evaluation study of what’s available internally and also define the costs going forward, keeping scalability also in mind.

About Cogniphi

Cogniphi is a technology company that enables customers to achieve transformational outcomes through cognitive digital solutions.  Cogniphi’s Vision Intelligence platform AI Vision integrates Computer Vision, Machine Learning, and AI to extract precise and meaningful data from visual footage. These are further converted into actionable insights and notifications.


Your surveillance system might be the chink in your armour. Make it fool-proof with AI Vision

Dozens of digital eyes peer at us today – guarding us from the moment we step out of our homes, and sometimes even before. We have surveillance cameras watching over our gates, our roads, and our offices, and even overseeing us in shops, malls, and ATMs.

Between Chennai, Hyderabad, and Delhi being among the top ten cities in the world with the highest number of CCTV cameras per square kilometre, and video surveillance buttressing Indian investigative agencies as they crack violent cases – these cameras have already proven themselves to be indispensable. It is, therefore, imperative to have cameras surveying your company’s premises, and to use them as the bedrock of your business’ security structure.

But these digital eyes are only as good as their human counterparts monitoring a feed. CCTVs’ watchful presence might prove to be a powerful deterrent, but their passivity results in complete reliance on external forces for intervention. These days, law enforcement too depends on captured footage to solve crime.

Things are changing, however, with  AI Vision (Artificially Intelligent Vision) – the tool that effectively marries computer vision algorithms with data-driven learning of Artificial Intelligence. Installing vision intelligence technology amplifies a company’s video surveillance system, transforming billions of hours of footage from an overwhelming wave of monotony into an organized database to apprehend perpetrators.

Here are six ways in which computer vision can help your company reduce security risks:


Cameras with AI Vision are significantly more adept at recognising and labelling objects – whether human, vehicle, or weapon. Installing this technology is an easy investment, especially considering most facilities are equipped with CCTV cameras.

This intelligence elevates an average camera, making it accurately identify a human presence even in the case of a partial capture. This process can even be widened to study people’s proportions and gaits, and can be trained to identify people based on these traits – even during less than ideal circumstances.

Automated identity recognition

The specificity that computer vision-powered cameras allow for, based in the technology’s pattern-recognition techniques, enables them to verify the identity of individuals based on extremely distinct features – like biometric identification through iris and retina scans. By extension, this technology allows for digitising all company documents since signatories can be corroborated through this highly precise process. These modes of biometric authorisation simplify and solidify security processes, and consequently reduce the scope for fraudulent activities.

Future forward

With the possibility of analysing movements and recognizing suspicious behavior in real time, and immediately notify authorities. Something as minute as a deceitful glance can be captured. From ringing alarms exactly when an item is shoplifted, to alerting authorities, vision intelligence turns CCTV cameras into a proactive part of cracking crime. Computer vision can also identify contextually dangerous behavior – such as a worker showing signs of fatigue and dozing off while operating high-risk equipment.

Outside of security concerns, these AI Vision capabilities can track behavior to provide detailed insights into what stakeholders and business partners respond to positively and negatively on company premises. Just tap into the data AI Vision gathers on your organisation’s performance indicators – from customer satisfaction to client retention rates.

Omnipresence: Computer vision can monitor all visitors on the premises, and alert security teams in a fraction of a second if an attempted robbery or security breach is occurring. The response – such as locking down the area – can be immediate. This promptness, along with hyper-specific discernment, enables security teams to share access privileges on an individual level, and allows them to even track miscreants through vision intelligence.

Furthermore, critical assets can be surveilled in real time – whether they are highly valued technologies or cash. Cogniphi’s AI Vision collection of historical data and pattern-learning capabilities can even offer a guide to where human resources need to be focused to strengthen the company’s security structure. And in case the crime has already occurred, security personnel can rely on the database to sift out relevant information within seconds – whether that detail is a man in a blue shirt, or a license plate. Computer vision – through a technique called “generative adversarial networks” – even offers the ability to enhance and recreate images, providing security teams more valuable visual details around critical incidents.

Safety measures: The midst of a raging pandemic, Vision Intelligence-enabled cameras can ensure that employees and workers socially distance on the premises. This technology can also alert workers who are dangerously close to hazardous equipment, or toxic substances.

Computer vision’s deep learning faculties can also understand manufacturing and standard operating procedures, and make sure materials and processes are being handled safely on the factory floor.

Similarly, Cogniphi AI Vision can track statutory compliance and make sure the company adheres to rules and regulations including the Factories Act, Shops and Establishment Act, and even Sexual Harassment of Women at Workplace (Prevention, Prohibition, and Redressal) Act.

Quick training: Newly hired employees can receive access privileges based on their scope of work. AI Vision’s expanding database can also serve as an exhaustive resource when it comes to training workers on standard operating procedures, and areas that need the focus of increased human resources – for instance, deploying more security personnel at risk-points.

Computer vision capabilities don’t replace human resources, rather they enhance and augment manned security systems. AI Vision’s surveillance offerings can predict critical security instances before they occur, prevent them from happening through a real time warning system, and protect you and your company’s valuable assets. This is an irrefutably reliable way to make your security systems proactive and fortified.

A new era for Retail Stores

A new era for Retail Stores

Retail is probably the one business that has undergone the most transformation and faced most challenges in the past few years. At the same time it is also the business where the most opportunities have opened up for the months ahead.

Whether it is super market chains, convenience stores, restaurants, electronic stores or food delivery service, the need of the hour is to be prepared for disruptions, and equip yourself to be able to pivot quickly to new ways of delivering products, services and customer experiences.

And, for that you must ensure you have the right technology to adapt to change. The time to think fresh, accept new concepts and experiment is Now.

Changed consumer behaviour has driven a multi channel approach

Shopping online has created a whole new world of shopping habits. The routine and practices of shoppers have clearly changed a great deal. Many customer habits have in fact changed forever. This has created the need for a major transformation in how retailers respond to an evolving situation.

An online shopping platform has become unavoidable to any large or medium retail business. But it has several challenges in cyber safety, infrastructure and supply-chain management, sporadic peaks and lows in demand, and the enormous issues involved in home delivery services.

Those who have weathered the storm are typically the retailers who have taken the hybrid route, being able to meet consumer needs irrespective of where the shopper is, whether it is in the physical store or online. Not that this approach is devoid of practical problems. It is not rare that an online sale has happened and the product ordered is out of stock.

An integrated technology solution is what successful retailers have adopted to manage critical operational functions in a hybrid model: tracking overall inventory in real time, keeping tab on the customer journey and preferences, making personalized offers and communications.

Click & Collect models (ordering online and pick-up at the store) are not only popular but also encourage more in-store visits and larger baskets.

Promoting and selling specific products based on preferences through social media is also a booming trend since it helps you find new customers.

Alibaba’s Hema supermarkets in China now run as a combination of a physical store, a restaurant and a fulfillment centre, with more than half the sales done via the app and picked up from the store.

Hence, the name of the game is to Go Hybrid. Technology and Artificial Intelligence will help you work with the right data and keep alive a connected software solution to seamlessly drive the multiple-channel business and transform your profitability.

Retail experiences will mostly be at a safe distance

While personalised experiences and engagements will continue to be key elements in retail, self-service concepts like contact-less check out will become the norm increasingly. Latest advances in Point of Sale technologies, like mobile PoS that can close transactions at wherever in the Store the customer is, are replacing traditional billing counters.

Vision Intelligence will play a huge part as the most popular technology in cashier-less outlets. You will soon see ceiling-mounted cameras and shelf sensors enabling the shopper to buy and leave without having to scan and pay. Contactless payment, being quick and convenient for the shopper as well as saving space for the retailer, is expected to become common sooner than later.

Retail processes will, without doubt, in the near future be driven by adoption of more and more technology.


Streamlining product lines will make for an easy shopping experience

The number of product options in a retail store is bound to reduce, which may be a boon for the shopper who may have got used to the search and filter service in online browsing and would prefer to walk around less and take quicker decisions. This would also be a welcome move for the retailer who can look now at a smaller and selected inventory.

Understanding the customer becomes a crucial factor in determining the choice of inventory. Garnering contextual data and utilizing artificial intelligence solutions will be key to keeping pace with customers’ wants.

Real time Data and Analytics will aid in finding new opportunities

Retailers must invest in technologies to move ahead with digital transformation to upgrade their capabilities and stay ahead of competition. Many retail businesses would have closed down during the pandemic if not for running their IT in the Cloud. By helping them make full use of data to get invaluable and actionable insights, advanced analytical tools in the Cloud also proved more than just useful in understanding clients and predicting demand.

Demand forecasting technologies using AI becomes absolutely essential to spot trends and patterns. Predictive tools that use AI and ML will be the most widely used ones to keep pace with change. The most accurate predictions though will come with a combination of the machine’s analytical abilities and human ingenuity and the awareness of external factors.

Do not look at digital transformation as a technology driven change

More than changes in technology, it is the innovations in the overall business model, products and business processes that will have a lasting and meaningful impact for companies that are looking at digitalisation to meet new challenges.

Digital transformation itself is aptly defined as “Reimagining of business in the digital age”. Change is primarily in the creation or alteration of, say, your manufacturing operations, or your retail customer’s shopping experience or your business culture and style. So, mapping your digital transformation strategy is most important. The biggest mistake you can make is to fall for shiny promises that surround new technologies. The attention to the technology side of the transformation process can come later.

First, look at innovation required in your business model, operational processes and customer experiences. Don’t just follow the Tech hype. Make sure that Change will leave a lasting impression on how you do your business.

Put in simple terms, you need to envision technology in the right context, and understand what measurable changes it can bring to your business. Look closely at these three changes in your business.

1.Transforming Business Models

This could even mean redefining the boundaries and activities of your firm. It could be digitally modifying your business, or adding a new digital line of business or simply using digital capability to access a wider market globally.

Examples are several. A sportswear company diversifying into digital devices that track and report on the workout, a grocery store developing an app that enables customers to pre-order, a super market chain introducing self check out to reduce human contact, an apparel company using digital design-sharing with production partners and avoiding having to frequently ship prototypes back and forth, a software company going global by changing its nature of business into a licensing model with a digital support network, and so on.

2.Transforming Internal Processes

Companies reap huge benefits by automation that usually results in freeing human resources that can then be utilized for more strategic tasks. It often enables a refocus on creativity and superior management by leaving repetitive efforts to the automated process. A typical example is of a manufacturing concern adopting Vision-enabled Artificial Intelligence to increase productivity by automating an Inspection Line.

Worker enablement is another visible mode of transformation. We all are aware of how Work from Home has altered the very fabric of individual and collaborative work. Rest assured that we have hardly seen the last of this transformation. Companies will certainly be looking for collaborative and networking tools that enhance both individual outputs as well knowledge sharing. Decision making at the top will also be benefited by being more informed.

3.Transforming Customer Experiences

This is the most exciting aspect of Transformation. Companies are finding that the two most important topics are What makes a Customer happy, and What leads to his dissatisfaction.

Building analytical abilities in understanding customers in more detail is now seen as a guiding light for brand loyalty, targeted promotions, market segmented pricing and several other marketing elements that lead to personalized sales and service. Perhaps the area that can be best served by digital initiatives is Customer after-sales service. The use of social media, messaging apps and other digital tools is changing the face of customer touch points.

Digital Technology

Once you are clear on what parts of your business need change and what will drive the changes in the three major aspects of your business, as above, you will be able to gauge how and which technologies can help you. A good digital transformation partner will also be able to help identify new ways to take advantage of the digital era.

Digital Technology will give you the best opportunities to change; not necessarily in all the areas at once, but one by one. However, the success of digital transformation projects depends not only on investing in the right technologies, but also also on the parallel organizational changes that are required for these technologies to be used effectively. Managing the transformation is also a major challenge, particularly for the not-so-large enterprises.

Whoever said that Digital Transformation is similar to conducting an orchestra rather than just buying the latest instruments hit the nail right on its head. If you want Digitalisation to be truly transformative, stay focused on the impacts it is making on your business and not just on the marvels of technology.

Retailers Must Adapt and Leverage their Data Better

Data has become the driving force and the stimulus of the retail world in these modern times. It is now the most essential constituent of any Digital Transformation strategy aimed at moving ahead to keep pace with customers’ demands and preferences. Without real-time data and analytics, Retail will be dead and gone.

More data are being generated in Retail businesses than ever before. The key is to make contextual sense out of this data and how to put it to the best use.

Investing in and adopting technology to upgrade your Data analytical capabilities is proving to be the best way to discover not only new opportunities but also to improve and change your business processes for a better bottom line.

Personalised experience

A Forrester report has revealed that shoppers today will not mind sharing personal information if they get convinced that it will result in their getting personalized products or promotions. This is confirmation of how important a personalized experience has become to a shopper. For the Retailer the message is simple. If you don’t invest in Data analytics you don’t get to deliver personalized service. And that is just one part of the story.

Data-driven Decision making

Artificial Intelligence AI), Machine Learning (ML), Computer Vision (CV) and Cloud technologies are some of the popular routes to making data driven decisions. What in essence Retail businesses need is software that gives you the capability to adapt quickly to new ways of delivering products and services based on the data you generate, whether it be on Sales trends, Inventory movement or Visual images and videos thrown up by your CCTV infrastructure.

The ultimate software is the one that can convert huge amount of data into logical, meaningful and consistent insights that can be instantly displayed on an integrated dashboard. If this software can link up to multiple data sources and collate them in a manner that is easily comprehensible, nothing like it.

Predictive Analytics

AI-based software solutions, such as the ones based on Vision Intelligence, are today capable of analyzing past events, current happenings and estimating what is likely to happen in the future. Predictive analytics is the name of the game. For example, Cogniphi’s AI Vision platform uses CV and ML-based learning capabilities to understand data, analyse patterns in that data, link them with several potential scenarios, and make predictions that will reduce the gap between what is needed by the market and what is actually delivered.

Successful Retailer of Tomorrow

The two most essential components of the Retail business today are Understanding your customer better and Improving your supply chain, to be able to deliver the right product to the right customer at the right time and at the right price. The successful retailer of tomorrow will be the one who acquires these capabilities by using technology that turns his Data into useful business intelligence, which enables him to meet customer needs and to run his operations efficiently.

About Cogniphi

Cogniphi is a technology company that enables customers to achieve transformational outcomes through cognitive digital solutions. It believes in a 360-degree problem-solving approach, building solutions that can scale and adapt to changing business demands for continuous improvement.

Become actively responsive with predictive analysis

Our world today is in the midst of its fifth industrial revolution. It is an era that is pushing the boundaries of science and technology to harness its best possible potential for the benefit of mankind. To have a deeper understanding of what Industry 5.0 is all about and how it is transforming our lives today, we need to delve into what constituted its predecessor – Industry 4.0. The fourth industrial revolution was all about introducing the basics of automation to the world and applying it heavily in the manufacturing space. 4.0 essentially brought together robots and other interconnected devices to execute repetitive and routine tasks that are best done by machines. Industry 4.0, like most other industrial revolutions, was a giant leap for human innovation, but it also brought to the fore, fears about machines replacing humans and this gave rise to a lot of negative sentiments that led to robots and technology being cast as the enemy. Industry 5.0 is dispelling all such notions and showing us how man and robot are not rivals and in fact can work together as partners.

Industry 5.0 takes the founding pillars of 4.0 – automation and efficiency – and adds a human touch to it via artificial intelligence and smart machines. And if Industry 4.0 was all about by automation, then Industry 5.0 will be about a sort of synergy and harmony between humans and machines. Industry 5.0 is constantly demonstrating to us that pairing humans and machines to further utilize human brain power and creativity is the way to go in the future. Take for example Cobots or collaborative robots that are specially designed to share space with humans. They are one of the best examples of Industry 5.0 because they are designed to integrate with humans; a good example of this would be surgery cobots or co-pilot cobots that assist humans to perform highly specialized tasks during surgery and flying respectively.

Another fascinating and remarkable leap made by Industry 5.0 is vision intelligence. At its core, vision intelligence is a subset of artificial intelligence that works towards making computers and machines visually enabled – it very literally is the process of giving machines the very human ability to see. Through vision intelligence, machines can be given the ability to see and process visuals the same way humans do. Computers don’t subjectively react to visuals the way humans do and hence lack decision making capabilities. However, through programming a photo recognition software or cobots and robots, machines can be taught to mimic ­­­human qualities and thus enable us to live enhanced lives.

Vision Intelligence and the Smart Factory


A pertinent example of vision intelligence’s uses would be its applications on a factory floor. Manufacturers today have the ability to run smart factory floors with the vast applications of vision intelligence technology. CCTV cameras can be programmed to do much more than just capture moving grainy images, instead, they can be programmed to perform cognitive functions, for e.g., segregating damaged goods from good food produce. Picture hundreds of ears of corn moving on a conveyor belt as workers sort the good ones from the bad as fast as humanly possible. Now imagine a vision-enabled machine aiding human workers to spot the poor-quality corn ears through their AI enabled vision technology. Aiding in quality checks of corn produce is just one of the myriad examples of vision intelligence applications in factories.

CCTV infrastructures can be further adapted to build intelligence into factory designs. A surveillance system at a chemical factory for example can be taught to gauge distance between a worker and a vat of dangerous chemicals, thereby sounding a real-time warning alarm and reducing the risk of industrial accidents. Similarly, vision AI tech can be useful at construction sites where each and every process can be monitored real time and chances of mishaps are thereby reduced.

The human decision-making process is steeped in context and analysis. Our brains interpret visuals, contextualize the situation and make a prediction or decision based on a number of variables. Up until now, machines only had the capacity to perform repetitive pre-programmed tasks because they lacked the ability to see and process visuals. However, with vision intelligence, machines can now observe human patterns and make predictive decisions by learning from the big data they collect, thereby becoming almost-apprentices to workers in factories.

In a factory setup, vision intelligence is thus a game-changing development that can be used to streamline complex processes and aid human beings to perform better.

Harnessing Business Intelligence to Do Wonders in Retail

The retail market is fast-paced and super competitive with continuous evolution taking place worldwide. Various retail business firms come up with advanced technologies to ensure that customer retention and customer engagement concerns are addressed.

Gone are the days when we saw the customers’ data as records and evidence of the purchase. Today, you can transform the customer’s data, sales data, and other qualitative purchase information into useful marketing or business growth strategies with Business Intelligence.

Read further to know how Business Intelligence can track shopper behaviour, enable personalised experiences and enhance customer loyalty in the retail segment.

Challenges faced by Traditional Loyalty Programs

The traditional concept of a customer loyalty scheme is no more a cup of tea for retail businesses. Though the customers appreciate points-based loyalty programs, the chances of them redeem the points are very less.

The Customer Relationship Programs that many businesses run still fail to maintain an appreciable pace with the changing mindset of the customers. Buyers expect timely and relevant experiences, with modern science and technology, where they rate businesses based on the ability to read their minds.

People now prefer stores that deploy Business Intelligence-driven solutions to reap the best retail shopping experience.

Business Intelligence will Transform Retail

Elements like relevance, customer satisfaction, and personalization key contributors to brand loyalty. Retailers choose to capitalize on innovative technologies such as Computer Vision and Artificial Intelligence to enhance the customer experience.

Vision Intelligence helps retailers to tackle their retail store pain points and transform the customer experiences by providing critical insights obtained from visual data that CCTV cameras throw up. By capturing, understanding and analysing the environment in real time it empowers quick decision making as well as a collection of contexts, meaningful data that can be invaluable in retaining customers and gaining an edge over competition.

Business intelligence can monitor how the users interact with the stores, and the data can help the businesses to stimulate the customer shopping experience. For instance, a customer might gain suggestions based on the items they viewed recently, or how much time they spent on gauging an advertisement.

Business intelligence practices can let businesses find relevant information and insights about consumers to make refined business decisions.

Expanding Outreach to Customers

E-commerce lets retailers implement efficient decisions that rely on customer behaviors with business intelligence. Businesses can adjust the prices, or the merchandise they offer, to allow real-time data monitoring.

Brick-and-mortar stores can also use Business Intelligence to maintain a balance between both in-store and online stock to offer affordable shipping options, like buy online or pick up from the store.

Nowadays, most physical stores expand their outreach to customers across all channels to improve the brand experience. Business intelligence methods can also predict when the products might run out of stock so that the retailers can order the items in advance and make location-based decisions for merchandising.

A Range of Benefits

The AI vision gives customers a personalized shipping experience with effective marketing campaigns, customer behavioral analysis, customer service analytics, customer product interaction, demographic intelligence, and many other features.

Here are the benefits of using Business Intelligence in the retail segment:

  • Demographic Intelligence

Businesses can analyze the physical locations of the buyers, find the products, websites, etc. through email campaigns or referrals. Location intelligence also helps businesses to make recommendations as per the locations and user preferences, to facilitate better audience targeting.

  • Monitor Customer Spending Habits and Buying Behavior

Customer loyalty programs can help retailers track customer behavior and spending patterns. As per the research, 52% of customers will join a customer loyalty program once it is offered. Loyalty programs can retain customers easily and help businesses generate user reviews. For instance, the loyalty program of Marriott includes benefits like VIP upgrades, members-only rates, free mobile app check-in, etc.

  • Provide Personalized Shopping Experiences

About 89% of businesses say that the customer experience is a key aspect to drive customer loyalty and retention. With retail intelligence, retailers get insights to improve purchasing experience, packaging, organizing, and the complete delivery of the products. Retailers can also track dwell time, ie. the time the user spends and interacts with your store.

  • Track Social Media Behavior

With business intelligence, companies can use the information to analyze sales and brand performance. Retail businesses can assess the Social media sentiments to track how the products score in the minds of consumers.

Business Intelligence is an effective tool you can use to recommend the products or the product promotions to the buyers based on their social sentiment and past purchase behavior. It helps your business drive profitability, with the personalization and precise customer analytics model.