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.

AI Vision to Sky-rocket your Marketing Engagement in Retail Stores

With the increasing adoption of digital devices and the internet, the number of digital buyers has been increasing significantly each year. In 2020, more than 2Bn people purchased goods or services online and e-retail sales surpassed $4.2 Tn worldwide. With the lockdowns in place, retail e-commerce sales grew more than 25% globally.

Looking at these statistics, one may argue that online shopping has made customers way too comfortable skimming and buying products from the comfort of their couch – leaving them uninterested in going back to brick-and-mortar stores.

However, the reality isn’t so. Shoppers like seeing the product with their eyes, holding it, and experiencing it before buying it. So, retailers to improve their in-store marketing engagement in order to keep them coming back.

Through innovative AI insights, marketers and store planners can showcase products in places where the consumer is more likely to be compelled to buy it. Wondering how that is done? Read on to find out.

Win hearts with demographic intelligence

Imagine directing first-time visitors to exactly where they want to go without any assistance, to be able to know precisely what part of the store they’ll enjoy visiting the most. With AI Vision, you can gain demographic insights and intelligence to direct customers to the specific parts of the store that their peer group enjoys the most.

 With your cameras, identifying and grouping similar people and behaviors, it becomes extremely easy to predict behavior and leverage it to provide a more nuanced and personalized experience to the shoppers, making them more likely to come back.

Experience ROI with hyperlocal campaigns 

Another advantage is that by identifying the shopper demography and behavior, it is easier to optimize your hyperlocal marketing campaigns store by store in real-time.  This is helpful because ads that may work in a specific area may not be as effective in another. This will ensure hyperlocal messaging specific to your target audience. Identify what else your retail location could offer to better suit a customer segment’s needs with an AI-based analytical approach that leverages person-level metrics. This will allow your business to track profitable customers and their preferences. By determining what these customers prefer and how they behave, your organization will be able to improve its messaging to this segment. As a result, conversions from high-value customers will increase. 

Watch your buyer’s steps

Facial recognition, combined with demographic intelligence, can help you customize in-store advertising based on the audience while also providing valuable insights about what works and what doesn’t.

Similarly, AI Vision can enable footfall tracking to help you trace your customer’s footsteps around the store, picking up critical information. For instance, the dwell time on specific passageways, dwell time on customer engagement with ads and displays, average customer count on weekdays and weekends, the effectiveness of in-store marketing campaigns, etc. Based on this data, recommendations are shared with store managers and visual Merchandisers on the customer type, ad preferences, ad types,  placement, and time of display that will attract and influence shoppers. The effectiveness of these recommendations is measured and by applying continuous learning of AI Vision models, the recommendations are fine-tuned to attain maximum customer engagement and conversions.

Footfall tracking isn’t just a tool to measure and interpret your buyer’s data, it also imparts particulars. These particulars include conversion rates of unique customers, returning customers, customers leaving within 5 minutes (bounce rate), and so forth. All this data is sufficient to polish your in-store marketing efforts and predict stock demands and avoid stock-outs.

Intelligent experience for Intelligent Visitors

Consumers are looking for a smart, swift, and time-saving shopping experience while sellers are looking for buyer conversions or brand impact on a shopper’s mind.

 Improving their in-store marketing engagement and the ability to accurately examine the same can bestow some skyrocketing results. The power needed to kick-start these results reside within the capabilities of the computer vision applications currently being used and the opportunities to bring innovation and enhancements to them.

In some time, AI Vision won’t sound so unreal because it would be everywhere. Stores that take the leap and become early adopters of the technology would not only be striding ahead of the competition. They’ll also have enough real, on-site technology to customize it and innovate as per their unique needs to stay ahead of the competition even when they adopt it.

About Cogniphi

Cogniphi is a technology company that focuses on building next-generation vision intelligence solutions that are outcome-driven and seamlessly integrate into the existing infrastructure. Cogniphi’s AI Vision is a platform that’s built to improve operational efficiency at every level of an organization, across industries and sectors.

If you’re wondering how Cogniphi’s AI Vision can help you transform your business, get in touch with us for a free demo!

Role Of AI Vision In Improving Safety Standards In Manufacturing

Accidents and operational hazards are important concerns in the manufacturing industry. An accident during daily operations can begin with a minor violation, but end up causing severe injuries to the workers involved.

Although health and safety measures at production and manufacturing units have improved a lot over the years, many have still discussed accidents during manufacturing and production. AI Vision-powered manufacturing solutions can lead to immense safety developments in most industries. Artificial Intelligence is a technology that has constantly been growing, making way for new possibilities.

AI Vision plays a vital role in helping manufacturers to prevent accidents, get organized, and enhance the workplace’s safety operations.

Workplace safety is related to many factors. Moreover, their control is complicated by vast territories that are difficult to follow with the human eye. Automated systems analyze the movement of special equipment and workers on the production site, measure the distance between objects and the weight of the lifted loads, analyze employees’ appearance, and much more.

AI Vision Drives Efficiency And Safety 

AI Vision increases the efficiency of the people in a workplace and ensures their safety. Monitoring workers for wearing protective gear is a huge issue to take care of inside a manufacturing plant. With AI Vision at work, even minor violations like taking off a helmet or gloves are reported in real-time. This automation of detection enables the manufacturers to minimize the risk of accidents that can take place while improving operational efficiency.

While not wearing protective equipment such as a helmet, mask, or gloves could seem like minor disobedience of protocols, it is the first step leading to any workplace accident. 24/7 automated inspections through cameras can act as supervisors for the workplace’s people. With more focus on the safety of the employees and constant supervising, the efficiency of work done gradually increases. 

Moreover, there are several other benefits of including AI Vision in a workplace, these include:

Smart Maintenance

A single equipment failure can result in hours of downtime and repair costs during manufacturing. AI Vision can recognize the imperfections of products on a production line with accuracy and speed. This lowers the cost of quality controls and eliminates waste to optimize the process of manufacturing.

On-Premise Security

As we stated earlier, AI Vision can be beneficial in reducing accidents in the workplace. Other than that, it could be used to monitor the flow of people in industrial sites, warehouses, and other manufacturing units. Entry of unauthorized personnel can be restricted to specific areas with facial recognition in real-time. AI Vision can detect potentially dangerous situations for workers while controlling the access of vehicles and people in the manufacturing unit.

Anomaly Detection

AI Vision can also help you to ensure smooth functioning with Anomaly detection. It can identify unexpected events, technical glitches with its data analysis technique. Anomaly Detection will help you fix those parts that have bad conditions in the production chain by which the manufacturing costs could be reduced.

Predictive Maintenance

Malfunctioning parts or equipment breakdown leads directly to stoppage in the work structure. Businesses that rely on physical components need to do constant maintenance of machinery. With AI Vision, you can optimize equipment usage with a better understanding of its lifetime andnreduced performance. This won’t only save a lot of time, but also a lot of cost reduction would take place if one knows about the condition of machinery beforehand.

Quality Control

With AI Vision, you could easily control the finished product’s quality and the complete production process. Defects in finished products also mean that the production process lacks the needed accuracy. AI Vision can detect a failure during the production process to ensure the quality of produced goods and recommend options to correct the errors made during the production process. It can also analyze employees’ work during the production process and report if they are not adapting correct actions.

AI Vision eliminates the human factor and errors, providing a 24/7 data analysis and surveillance, which results in the production and manufacturing processes becoming more efficient and safer for the employees at the workplace.

About Cogniphi

Cogniphi is a technology company that focuses on building next-generation vision intelligence solutions that are outcome-driven and seamlessly integrate into the existing infrastructure. Cogniphi’s AI Vision is a platform that’s built to improve operational efficiency at every level of an organization, across industries and sectors.

If you’re wondering how Cogniphi’s AI Vision can help you transform your business, get in touch with us for a free demo!

AI in Retail: How it’s Changing Forecasting for the Better

Every retailer is looking for the next big thing in the industry to gain an edge in the current market scenario. With data coming closer to the logistics, consumer goods companies, and retailers – this is where the next storm is brewing.

For decades, the traditional levels of analytics have been used in the data-driven retail industry. But the recent advancement in artificial intelligence and machine learning have brought a new level of data processing that uncovers hidden business insights.  It opens new avenues to business operators in case of anomalies, forecasting, and correlations.

The pulse point of data influx is determining consumer behavior and catering to their actual needs. By mining insights from the global market and buyer data, AI business intelligence systems predict industry moves and make proactive modifications to a company’s marketing, merchandising, and corporate strategy. This can also be defined as demand forecasting.

In short, demand forecasting enables the right product to be at the right time in the right location. It ensures meeting customer demands and manage costs efficiently.

With advancements in AI, demand forecasting can optimize stock levels, increase efficiency and elevate customer experiences to an automated level.

Here are 4 areas that AI Vision has transformed in retail demand forecasting-

Data consolidation

AI Vision corroborates and centralizes internal data such as information on sales, product characteristics, metadata, marketing, and promotional activities; external data such as sales data from distributors and market research reports; contextual data such as insights on demographic or geographic data and seasonal market – all in one place.

AI-powered vision intelligence forecasting systems are capable of using data from multiple locations to derive complex and hidden relationships between them which can be substantial predictors of demand for the future.

Demand anticipation

Demand forecasting is about predicting future sales based on historical sales data of a given product. With AI Vision-based systems, you can use the most sophisticated vision intelligence algorithms to predict demand accurately. These solutions and algorithms are self-evolving, deployed once and improved in accuracy continuously.

AI Vision can moreover provide new products with no historical data, a base to compare characteristics to the particulars of the previous products. Thus, saving costs and providing customers with their utmost needs.

Impact prediction

AI Vision-driven demand forecasting can categorize demand into ‘real’ demand and ‘promotional’ effect. It can catch the difference between when a customer is purchasing a product for a genuine reason or due to an influx in promotions. It can achieve this by measuring dwell time on customer engagement with ads and displays and tracking customer behavior consistently.

These analytical insights can be utilized by decision-makers to plan and target marketing to direct the target audience.  They can assess the impact of a certain campaign on sales and, as a result, choose the best pricing point.

The intelligent vision monitoring solution is also capable of forging different scenarios, such as gauging how a new clothing line will be received by the existing customer base if it is launched in the next season’s fiscal year collection. Essentially, this can aid the retailers in planning new product launches.

Manage demand irregularities

AI Vision solutions equip business operations to precisely analyze and improve results on overstocking and understocking to increase profitability and avoid wastage. The accuracy in AI Vision complements the business intelligence to give you precision in operational management.

It also helps monitor current activities as well. Vision intelligence detects anomalies such as safety hazards and administrations such as storage capacity,  etc. for immediate action by integrating an understanding of object identification and analysis. It enables visualizing the bigger picture of business in real-time and strategizing accordingly.

To conclude, Retailers must rethink their old supply chain in favor of adaptable and flexible ecosystems that can swiftly adjust to consumers’ evolving behaviors to meet a larger range of customer needs that are going from mainstream to niche. They must filter through the noise to translate diverse data sources into consumer-first strategies when confronted with an influx of information from all elements of their organization- from supply chains to stores to consumers. 

How AI Vision is Changing Public Safety for the Better

As we build a better society, one of the most important measures of progress is public safety. Companies around the world are designing innovative technologies to detect and prevent crimes. With AI, it has now become easier to leverage historical data to identify patterns and predict locations where crimes are most likely to happen in order to focus all energies into making the most vulnerable areas safe.

Moreover, with technologies like facial recognition and validation, it has become possible to solve crimes with reduced time and effort. More and more improvements in law enforcement can be seen with the implementation of data-based technologies, especially Artificial Intelligence.

But what’s in store for the future of law enforcement?

Vision Intelligence For Public Safety

Vision intelligence has highly practical applications in surveillance and public safety. With the ability to detect patterns in visual feed – images or videos, it becomes easier to track and identify items, patterns, people, and behaviours to trigger an alarm or warn the responsible security personnel in real-time of impending threats.

Some of the vision intelligence applications that are most useful in public safety are:

1. Facial Recognition and Validation

Facial recognition is currently a relatively commonplace technology where most smartphones are now locked/unlocked with it. However, it’s application in surveillance and public safety is more profound, and paramount. With AI-based visual intelligence, facial recognition can not only identify people behind a disguise but also read emotions and expressions to predict suspicious behaviour if and when a person is intending to commit a crime.
Moreover, with facial validation, it becomes possible to detect and prevent bypassing of facial recognition through identity theft or deep fakes.

 

AI Vision

 2. Behavior Detection

When trained to identify a set pattern of behaviour that people are required to follow, an AI-based camera can detect anomalies from the set pattern and provide alerts or notifications. This can be implemented in controlled public places such as prisons, mental asylums, etc. where a set pattern of behaviour is expected from individuals and any anomaly can be a sign of trouble.

AI Vision

3. Skeletal Construction

Certain movements can be identified in individuals that indicate criminal intent. In surveillance, with video cameras ingrained with vision intelligence, one can identify if there’s a fight that breaks out in an alleyway and whether it’s just a quarrel or it has serious repercussions. This insight could potentially enable the surveillance to make the right decision at the right time to prevent escalation of the situation and possibly prevent a crime from happening.

AI Vision

In addition to all this, the applications of vision intelligence are becoming more pronounced and imperative as we advance in technology and operations.

We, at Cogniphi, are building effective vision intelligence solutions that are outcome-driven and significantly improves the existing cameras in an area to drive insights and ensure improved surveillance and safety.

About Cogniphi

Cogniphi is a technology company that focuses on building next-generation vision intelligence solutions that are outcome-driven and seamlessly integrates into the existing infrastructure. Cogniphi’s AI Vision is a platform that’s built to improve operational efficiency at every level of an organization, across industries and sectors.

If you’re wondering how Cogniphi’s AI Vision can help you transform your business, get in touch with us for a free demo!

Why AI Vision is Crucial in Quality Inspection

The Fourth Industrial Revolution or Industry 4.0 is here – it’s blurring the lines between the physical, digital, and biological worlds. With a fusion of progressive technology like AI, robotics, the Internet of Things, 3D printing, and more, it’s changing the way the world functions.

We are witnessing the inception of full automation across sectors – manufacturing, retail, pharma, medicine, and more. Data has become instrumental to making this happen and Artificial Intelligence is what’s driving it. As we progress into a more capable, more exciting future, it’s imperative that the quality of production, in all sectors, becomes better and better – it’s called progress for a reason.

AI has been providing the inputs for digital transformation but without the capability to understand context. The AI cameras currently used by most businesses require a human to look at the footage to add context in the detection and have a very low accuracy which makes them ineffective. Without context, there’s little value that these cameras can provide.

The machines that businesses and organizations have setup into their premises to monitor data, especially cameras, only look at the 1s and 0s of the data that’s presented to them – they lack the clarity of context that denies them the opportunity to be precise, accurate, and error-free.

And that’s about to change.

In the last few years, we’ve taken huge leaps in vision intelligence. This prominent technology enables cameras to look at visual feed as a whole – complete in its context. This empowers them to identify, detect, or distinguish between objects with better clarity, precision, and accuracy.

Current advantages of vision intelligence in quality control

With the recent advancement in vision intelligence, we have already seen the benefits in quality control like:

  1. identifying damaged/faulty goods during production
  2. enforcing PPE for workers
  3. checking on vacant shelves in supermarkets
  4. Identifying and eliminating repetitive tasks

Why AI Vision will become crucial for quality inspection

Quality control is fast becoming automated in a lot of companies across sectors.

Such improvements in the process not only improves the productivity of a process but also leads to more efficient production leading to better returns for businesses with a higher production at reduced costs.

For instance, a camera overlooking a production line must have a person sitting behind it, ensuring that no product is damaged or defective. Now, this person could easily miss a few defective products owing to fatigue which could affect the later production. With an AI-enabled camera, the defective products can be instantly and consistently flagged and pulled out of the production line, saving wastage any further in the process.

These intelligent cameras can not only detect imperfections but also enable geometric inspection, packaging control, product classification, and more.

AI Vision

AI Vision

AI Vision

AI Vision

Some of the undeniable advantages of vision intelligence in quality inspection include:

  1. Being precise and accurate in reporting and flagging inefficiencies
  2. Accelerating the production speed through seamless flow of repetitive tasks
  3. Reducing the downtime of a process by eliminating breaks or rest
  4. Lowering the operational costs by cutting down on manual labor and saving on wastage

Cogniphi is accelerating the future of vision intelligence with Cogniphi’s AI Vision by enabling leaders in the manufacturing with specific cognitive intelligence to solve problems. We take a very objective approach to solving business problems – analyzing the challenge to find out the reasons behind any inefficiencies and reaching the root of the cause and solving it from within to ensure that the return on investment is profound.

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.

 

Start-up vs SME – Recognise the Difference and Get Hired Faster

So, you are looking for a job at a start-up, are you? Well, then it will do you good to understand the difference between a Start-up and just another small business, and also appreciate the nuances behind the recruitment strategies of a Start-up. Get a few tips too at the end of it all.

Why is a startup not just another SME (small medium enterprise)?

 

The typical SME is a business concern started primarily for earning a profit. It typically runs on its own steam and is focused on business at hand, how to increase revenues and turnover, how to cut leakages and increase profits, and how to increase efficiency. Strategies are based on market requirements and number of customers.

A start-up, on the other hand, has a different mindset altogether. It’s trying to create a new world with an idea or a succession of ideas. The focus is on innovation, creating value out of the idea, value for the promoters, for the employees, for the investment partners and shareholders, for its collaborators and partners, and for its customers.

And it is not any incremental value jump that a start-up is aiming at. The start-up strongly believes that the world will gain exponentially when the idea is fully baked. And the founder is fully aware that the baking will require tons of dedication and a committed way of life devoted to the idea.

The act of sourcing talent for a Start-up

Start-ups differ most from SMEs in the personnel front. Since it generally embodies a new business idea it requires multiple hands and minds working to develop it. The usual start-up is one where a number of heads do their thing simultaneously. That is also one reason why Building the Team is the most important task at the beginning of the Start-up’s life cycle.

Building a talent pipeline is critical for the company during these early days. And, to this end, creating a compelling employer brand and projecting a modern corporate culture help to yield top candidates. A start-up HR has the opportunity to craft the company story and build processes from scratch. Start-ups are also known to leverage unique sourcing strategies, particularly if they have support of large private equity partners or venture capitalists.

The recruiter for a start-up is generally on the look-out for versatile people since, in a small office, all hands on deck is a daily event. Hence, someone with a varied skill-set and who can be a team player will be in great demand. In the start-up environment one certainly gets to know everyone else well and definitely needs to learn to work with everyone quickly.

Tips for the Start-up Job applicant

Tip 1 is that the Recruiter is actually on a sales mission. He is not just trying to match CVs with profiles, but also to project the company in the right manner. He is more likely to be looking for flashes of brilliant thinking, drive and a positive attitude, and for people who fit in with the company’s culture.

Tip 2 is to demonstrate that you possess adequate communication skills and ease of working with others in a team. If you have genuine stories of how you have solved problems in business or real life, nothing like it.

Tip 3 is to be ready to make a pitch. The start-up recruiter is bound to ask the candidate to make his own sales pitch to determine the extent of passion and ideas in him, which often also reveals if he is a right fit or not. Convey your passion, motivation and convictions precisely. It’s very likely that the pitch can make it swing either way.

Tip 4 is to be Aware and Visible. Awareness is about the company, its product or mission, its culture and the industry in general. Visibility is about yourself, your LinkedIn profile and your online presence. Your professional connections and endorsements of your skills by others will count very much.

Tip 5 is to remember to be respectfully curious. You are interviewing the company as much as they are interviewing you, but do not make assumptions. Ask questions with a genuine interest to know more.

And, finally, Don’t pretend to be someone you’re Not.

How Predictive Insights Can Help You Reduce Operational Waste

Predictive analytics refers to a category of advanced analytics that can predict future outcomes with the help of historical data as well as data mining techniques, statistical modeling, and machine learning. Businesses use predictive analytics to detect patterns in their data to recognize opportunities or threats.

As interesting as this might sound, there is a vast ocean of unchartered territories and unclaimed knowledge that takes possibilities of predictive insights beyond tomorrow. Learn more about how companies can benefit from streamlining their operations to reduce waste with the help of this ingenious technology.

Ready to dive in? Let’s get right into it!

What is meant by Predictive Insights?

Predictive analytics is generally correlated with data science and big data. Businesses at present have heaps of data across equipment log files, transactional databases, video, media images, sensors, or various sources of data. To achieve actionable insights using this data, analysts and scientists take the aid of machine learning and deep learning algorithms to determine patterns for predictions regarding future trends and events.

These can include nonlinear and linear regression, support vector systems, neural networks, and decision trees. The findings obtained using predictive analytics can then be applied to prescriptive analytics with the goal of driving operations depending upon these predictive insights.

The History and Present Milestones of Predictive Analytics

Even though predictive analytics has been used by businesses for decades, the time to exploit it correctly has just begun. An increasing number of companies are adopting the use of predictive analytics as a way to boost their bottom line and reap the benefits of a competitive edge.

The question that arises is – why is it starting to peak now?

There are several answers to this question:

  1.  Increasing quantity and types of data, or maybe, an increasing interest to utilize data to extract actionable insights.
  2. Quicker and more economical computers are available today with huge computing power.
  3. User-friendly software.
  4. More challenging market scenarios present the requirement for competitive segregation of products and services.

With the rise of interactive and user-friendly software in all markets and industries, predictive analytics is not just a domain for mathematicians or statisticians anymore. This niche is now free of complexities and can be used by business analysts or business experts with ease.

What Makes Predictive Analytics Vital to Reducing Operational Waste?

Companies are rapidly adopting predictive analytics to sort out their existing problems and reveal better opportunities. The common benefits of predictive insights to operations include:

– Fraud Detection: Gathering various methods of analytics can boost the detection of trends and patterns to prevent criminal conduct. With cybersecurity being at the forefront of businesses’ main concerns, the help of high-quality behavioral analytics reviews all the transactions and processes undertaken with suppliers and quality control in real-time. This helps them to find any irregularities that could point towards fraud, advanced threats, or zero-day vulnerabilities.

–  Improving Production Strategies: Predictive analytics are employed to understand the demand and supply chain of their production process. By monitoring their suppliers’ inflow of raw material, they can place orders well in advance, avoiding idle time or resorting to last-minute supplies that compromise quality.

– Efficient Production Operations: Many businesses employ predictive models to project inventory and control their resources. Predictive analytics helps businesses to maximize their operational efficiency and reduce rejects or sub-standard production by figuring out discrepancies in processes or equipment much before these breakdowns occur.

– Risk Reduction: The integrity and competency of the shop-floor staff matter a lot in manufacturing. With predictive analytics and insights, one can look up the reasons for the continual reject causes in their production jobs and batches. If human error is responsible for these wastes, they can be promptly addressed. If the insights rule out human error, it also gives manufacturers the chance to improve accountability, thereby lowering the risk of equipment malfunction or external factors like raw material quality.

How are Predictive Insights Used in the Manufacturing Operations

In the manufacturing industry, it’s crucial to find the factors that cause poor quality and failure in production processes. It is also important to optimize elements, services, and logistics. One of the most successful manufacturers that use predictive analytics to improve their grasp of warranty claims is Lenovo; their step forward led them to reduce 10 to 15 percent in warranty charges. Another benefit of using predictive analytics in manufacturing is that monitoring the equipment performance and yield quality can help track inconsistencies much before the quality checks fail.

Optimizing complex production networks

Predictive maintenance studies are devised to boost the operations and profitability of each production machine and process. Additionally, PPH maximization can streamline the interaction of the processes and machines used. Including all the processes, be it from the purchase of raw materials to the production process and sales, this superior technique of modeling exponentially improves the revenue in complex production operations and supply chains.

Unlike manual planning, advanced analytics generally considers about a thousand different variables and 10,000 constraints to assist the manufacturers to understand what to buy, what to manufacture, and how to manufacture in order to generate great profits throughout the year.

Achieving abundant profits with less

Just like predictive maintenance helps to enhance the uptime of any given asset, predictive analysis can improve its productivity and OEE. Even minute improvement in the overall operational efficiency (OEE) can dramatically boost profits before interest and tax (PBIT). This is achieved by enhancing the production output, material costs, and throughput to boost the profitability of every process involved.

Reduction in downtime in a busy environment

With the help of advanced analytics, manufacturers can boil down the causes of their equipment breaking down and control the input metrics so that they can fix an issue before the breakdown occurs or be prepared to quickly fix issues in order to minimize total downtime. Predictive maintenance can help to increase the equipment lifespan by 20 to 40 percent and reduce downtime by 30 to 50 percent.

Operations are linked closely with the metrics of production, reject (waste), and downtime, which can now be monitored and controlled better with the aid of predictive analytics. By projecting the future demands, manufacturers can be prepared for market shifts, optimize their processes and improve the overall efficiency of their sites using this sophisticated technology. We hope that this blog gave you valuable insight into the world of predictive intelligence and its link to operational efficiency.

What Is AI Vision and Why Is It Here to Stay?

Artificial Intelligence is one of the most misunderstood and overused buzzwords of our generation. We hear so many organizations bragging about their use of AI without really understanding what they are doing with it. In this blog post, our experts share how Artificial Intelligence is used in Cameras to improve business operations. Also, learn why it will become the future of how we do business.

Computer Vision is the application of Artificial Intelligence (“AI”) through a visual medium, like a live camera feed or an image. It essentially aims to replicate human perception and visual cognition. You must have already encountered computer vision without even realizing it, for example, the face-lock on your phone screen, to some level, is a simple application of computer vision or the Instagram or Snapchat filters that alter your hairstyle or turn your face into an animal on the screen, are all made possible with Computer Vision.

Any device that can comprehend a visual feed like a human being is a computer vision system, however, Computers have the ability to process more than humans can. Think about yourself reading these words. It’s likely that you’re focusing on one word at a time while you are reading, and recognizing the words around these words without fully processing them. Using Computer Vision, a computer would be able to see and read all the words on the page at the same time, drawing immediate meaning from the entire page

This principle also applies in a CCTV control room. Normally you would have people monitoring the live camera feeds on multiple screens, but how many live feeds can one person accurately monitor at a time? That’s where Computer Vision shines. It’s able to continuously and accurately monitor the feeds from all cameras simultaneously.

Automation integrated with AI Vision enables the workforce to overcome typical challenges of humans, like fatigue. It provides unseen insights that humans find difficult to access or comprehend in real-time. While human perception has its own share of limitations, a camera can gather every second of visual data from your premises that can be further analyzed to identify areas typically missed by humans.

Computer vision is the most natural next step in machine evolution. The purpose of AI is not to replace humans but to assist them. For that to happen, it needs to command similar cognitive abilities with enhanced capabilities. However, the underlying science behind AI Vision is not as complex or overwhelming as it might appear. Here’s a brief understanding of how AI Vision functions:

Capture Metadata from Camera Feeds

Content feed from a camera is analyzed by trained models to recognize objects, their actions, specific characteristics, and interactions in space and time. Typically, in a retail store, a camera equipped with Cogniphi’s AI Vision can detect shoppers, analyze footfall, recognize customers with face recognition, and evaluate customer expressions like anger with emotion recognition. Similarly in manufacturing, AI Vision can do myriad tasks such as identifying quality for inspection, counting warehouse inventory, etc.

Pattern Recognition and Anomaly Detection

Computer Vision derives relevant insights from unstructured data through contexts and occurrences of patterns along with their co-relations. In a retail store, AI Vision can analyze shopper dwell time, shopper interaction with products, alert anomalies such as misplaced objects in the wrong area, water spillage, and identifying reasons for inventory shrinkage, etc.

Recommendations and Predictive Analytics

Smart Vision equipped with actionable insights provides recommendations in the form of real-time alerts, analytics, and also integrates with existing business systems.

Cogniphi’s AI Vision is a pioneer in providing hyper-local computer vision solutions to retailers and manufacturers. Different components of the solution cater to different aspects of visual data and analytics to

– detect objects and their interaction in space and time.

– detect human body parts, their movement, interactions with real-world objects, their transformations, and other associated patterns.

– detect human faces and recognize people in 1:1 (Verification) and 1:N (Identification) mode.

– detect attention, emotions, and expressions on the faces

– identify and detect textures of objects.

– extract data from several documents and categorize data to train the model to interpret and analyze this data.

AI Vision is Here to Stay

Vision Intelligence technology is a cost-effective upgrade to existing data feeding cameras. On top of being a non-disruptive installation, Cogniphi’s AI Vision can help an enterprise reduce human error and experience overall increased productivity.

The Grand View Research states the growing valuation of the global computer vision market is expected to go up from $11 billion in 2020 to reach $19 billion by 2027. Manufacturing, Energy, Retail, Transportation, and Healthcare are the industries identified as best positioned to capitalize on this technology in the coming years.

The 2020 McKinsey Global Survey on AI has concluded that 50% of companies have adopted AI in one or other business functions and that the majority of use cases are aimed at optimizing operations or at product development or at customer service improvement. As companies increasingly look at AI to solve real-world challenges that depend a great deal on visual inputs, computer vision will have a huge role to play in achieving these objectives.

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.

Reimagining Brick & Mortar Retail: How AI Vision can help

As the world recovers from the disastrous global pandemic, we are witnessing the revival and renewal of brick-and-mortar retail stores. eCommerce giants such as Amazon, are investing in innovative physical stores, which is reassuring for the traditional brick-and-mortar retail format.

For physical stores to remain competitive against these online behemoths, it is imperative that they stay up to date with the latest technologies. Modern technology can revolutionize the customer shopping experience and the efficiency of retailers’ operations. For example, Amazon stores are contactless, which means shoppers can walk in, select products, and walk out without stopping to pay. Customers are immediately charged for their goods as they leave the store. While this is convenient, an upgrade to this extent is not practical for most retailers, especially those outside the grocery style format, where customer service is key.

While innovation at Amazon’s scale is cost-prohibitive and inaccessible, there are other, more cost-effective, methods that most retailers can benefit immensely from currently.

Cogniphi’s AI Vision technology upgrades the retailer’s existing security cameras, enabling these cameras to understand what they see and send actionable insights to staff for action. These cameras become intelligent eyes that collect data 24/7 and improve store operations, revenue generation, efficiency, and safety.

The use cases of the data that could be collected using AI Vision are endless. Here are a few questions to demonstrate how beneficial this technology can be:

    • How does a retailer know when a product is out of stock on the shelf?
    • How long does it take a retailer to replenish that stock or place an order?
    • How does a retailer know what kind of customer is purchasing that product?
    • How does a retailer know how long it took a customer to decide on a product?
    • How does a retailer gather this information across all their stores?
    • How does the head office group know that the individual store is correctly displaying the products at all times?

These questions go deeper and deeper to demonstrate the depth there is for improvement in the retail space.

Enhancing existing security cameras with AI means that a camera can see that stock levels are low, can check the system to see if there is stock available in the stockroom, and can send a notification to staff to replenish immediately. This is a far greater outcome than the current model of waiting hours or until the next day for the product to be replenished, causing the store to miss out on sales.

Furthermore, the AI cameras can collect data on how many shoppers were interested in that product, provide information on how long it took the shopper to decide on that product or detect if a product was stolen and trigger a response for staff or security. This data is all anonymized so no shopper is identified.

These are only a few applications of many, that Cogniphi’s AI Vision can achieve. Below we explore applications that Cogniphi has executed at retailers around the world.

Heat Maps

Retail heat maps can help understand individual shop functionality and identify customer behavior at and around aisles. Retail heat map technology uses real-time imaging to detect movement and assign colors to each floor area based on traffic volume, frequency of visits, or dwell time in those areas to understand customer activity, test new merchandising strategies, and experiment with layouts.

The heat maps can be filtered by different metrics and by different customers, for example, by demographics, or by whether a shopper is alone, is a couple or a part of a group. This data is captured at a statistical population level so retailers can now make decisions off population-size data which includes all the available data sets as opposed to traditionally limited sample sizes.

The data can be used to re-design a store layout, product layout, and optimise category positioning by understanding which areas in a store have high traffic and by who, to achieve growth in basket size and value of purchase.

AI-based Loss Prevention

With AI Vision, theft can be prevented by identifying concealment of products, products that are not scanned at checkouts or products that are incorrectly scanned at checkouts. The cameras detect suspicious activity and behavior in real-time, giving retail stores enough time to respond proactively before the product leaves the store, as opposed to reactively spending time searching through footage to find evidence after the product is long gone.

Some retailers have opted to integrate notifications into point-of-sale devices for staff at checkouts, who can stop the offender before they leave or make sure products are scanned correctly. In other stores, a notification is immediately sent to security personnel with an image of the offender. An added advantage of AI Vision is that each incident is recorded and cataloged for later reference, flexible to your requirements.

AI Vision can also prevent staff from stealing by tracking each product across the store in real-time. Reducing such instances in the store can significantly reduce the losses faced by retailers on a regular basis.

Shopper Analytics

Conventional sensor-based, customer analytics apps can detect in-store traffic in limited detail and without contextual information, for example, they cannot tell the difference between a staff member and a shopper, so the data is always inaccurate. They also do not understand when a shopper is shopping in a group so when calculating store conversion rate, the data shows a lower conversion as not all members of a group, for example, a family will be expected to make a purchase. Cogniphi’s AI Vision can help retailers analyze and observe buyer behavior very closely by providing contextual data about shoppers.

Use cases include:

    • Notifying staff if a customer has not been approached for assistance within 30 seconds of entering the store.
    • Notifying staff if a customer is displaying expressions of confusion, frustration or is upset.
    • Collecting data on how many shoppers come into the store each day and ensuring accurate staff resource planning to meet demand.
    • Collecting data on localized shopper demographics for a more personalized product range and marketing messages.
    • Analyzing queue length and alerting staff to open more checkouts or close checkouts.
    • Providing accurate conversion rates and statistics.

Stock Management

AI Vision can monitor shelves and aisles to check if any of the shelves are out of stock or out of place.  This ensures timely adjustments so no customer misses out on purchasing products. It also ensures products are ordered on time so there are no out of stocks.

This data can be collected across all stores and shared with suppliers to hold them accountable for out of stocks or so that retailers can increase their negotiating power by proving they are fulfilling their trading terms and conditions.

Compliance Management

For stores that have multiple locations, there are many requirements imposed on them by their centralized head office. The challenge for head offices to manage is: how do they ensure all their stores are consistently meeting the many compliance conditions imposed on them?

Conditions include (among many):

    • Correct staff uniform
    • Opening and closing on time
    • Correct display of marketing materials and point of sale
    • Adherence to planogram requirements
    • Appropriate cleanliness and cleaning method
    • No out of stocks on the shelf

Using Cogniphi’s AI Vision, each store can receive an accurate rating out of 100%, calculated in real-time, on how they are performing against these KPIs. This will prioritize the efforts of Area Managers whose role is to ensure each store in their area is up to standard. When a store starts to drop its compliance, immediate notifications can be sent to managers to obtain remedies.

Occupational Health and Safety (OH&S)

Retail stores have many risk factors that can endanger the safety of staff and shoppers. In some stores, there are heavy machines that require trained operators. In other stores, a slippery surface could cause an individual to trip and hurt themselves.

Cogniphi’s AI Vision can monitor a store 24/7 for hazards that can impose an OH&S risk. If a spill or slippery surface is detected. Staff will be notified immediately to clean the area. If the process is for staff to wear protective clothing, like a mask, any breach of this will result in a notification to a supervisor and the overall OH&S rating of the store will decrease. 

Looking at a new dawn in retail

Cogniphi’s AI Vision is a plug-and-play solution that layers AI on top of retailers’ existing video/CCTV infrastructure.  It is pre-loaded with functionality features that enable deployment with faster returns.

The solution is highly flexible with retailers globally, progressively adding more features to their cameras every year. We find that typically retailers will tackle 1 to 3 problems in their first year, and after they see results and a positive return on investment, they add more features.

Cogniphi empowers companies with tools, people, and hyper-local solutions to rapidly innovate and adapt in a hyper-competitive business landscape. If your business is interested in finding out more, please see our website for more information [Click here] or reach out to our team, and one of our friendly consultants will be in touch with you [Reach us].

About Cogniphi

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