Category: Automation

How Internet of Things Is Redefining The Retail Experience

How Internet of Things Is Redefining The Retail Experience

While most of us have remained busy discussing how quickly online shopping has gone mainstream, a quiet revolution is growing in the retail sector across the world. Internet of Things is breathing life into dying retail spaces while invigorating newer and more creative retail units. IoT-enabled shopping is taking online e-Commerce space by storm too, enhancing logistics, delivery, and even the shopping experience. With more than 30 billion connected devices available by 2020, IoT is leading all technological innovation in the retail sector. From improving products to reducing energy consumption, and from enhancing marketing outcomes to improving customer experience, IoT is practically all over the place. Most importantly, all the accumulation of data is helping companies to gain new insights, and enhance products and customer experience, while witnessing double-digit growth rate. Amazon Go is a great example of this revolution. In this article, let’s take a look at how IoT is helping both offline retailers. Let us also briefly look at some of the top trends in retail with IoT devices in mind. How Internet of Things is helping brick and mortar stores as well Thousands of stores are shutting down, malls are going out of business, and retail stores simply aren’t able to catch up with the speed of digital shopping. In addition, people themselves have begun to prefer ordering products online than making a trip to the nearest mall or supermarket. Retail sector all around the world has much to worry about and resent. Yet, there is a silver lining in every cloud. IoT is helping retailers across the world to not only thrive but also attract more customers than ever to their stores. Vending machines are being revolutionised across malls and public places as customised orders and products can now be placed. Interactive displays and digital signage are helping customers to shop better and reach out right counter or shelf, depending on the in-store choices they make. Few retailers may offer virtual and smart mirrors, which provide information about the clothes they are trying. If the particular shirt a man is trying is green when compared to the one he just tried earlier, why not urge him to buy that automatically? Beacons and RFID tags can be further enhanced with sensors. IoT-enabled beacons can be used to recognize facial expressions, customer behavior across shopping aisles, and other such information. This can be used to enhance customer experience. IoT most importantly hastens the checkout process. Both retailers and customers can bid goodbye to lengthy queues at the billing counter, thanks to self-checkouts. Hottest trends in the retail sector depend on IoT If there is one thing that is going to sustain retail, it is IoT. Let us take a look at few situations where IoT is helping retail to innovate, sustain, and thrive. Marketing is easier than ever IoT is responsible for making marketing easier than ever. It provides the tools required for making both omnichannel and multichannel marketing successful. Sensors are increasingly being used by retailers to help customers. IoT sensors also help stores to engage in in-store marketing. Coordinate with customers quickly One of the factors that set IoT apart is its ability to communicate not just between devices or sensors, but also enhance communication between the retailer/manufacturer and the user. This helps store owners to coordinate with customers quickly in case products need maintenance services, or if there is an update to be installed. Download our case study on Konvergence’s K-Wallet, which revolutionized retail shopping some time ago. Customising customer experience There are sensors for tracking virtually every behaviour of a customer. When done ethically, sensors can provide valuable data that help manufacturers to enhance customer experience. Whether it is about enhancing certain product features or bringing better customer service, IoT can do it all with an ease and pomp. Create better product ecosystems Manufacturers and retailers have begun to tie up to provide better customer experience, using sensors. This is helping create new opportunities for better product ecosystems. Customers have options for maintenance, servicing, updating, or choosing from related products post-sales as well. Automated orders of spare parts when they need to be replaced is just one example of this ecosystem. Optimise logistics and inventory handling IoT’s is creating improved efficiency inventory handling and logistics management. Businesses are literally growing because they can deliver products quickly, and replenish stocks. IoT is helping businesses to ensure retail never faces a hitch due to product unavailability or delayed shipments. Data-derived insights IoT, as we all know, gathers and processes enormous amounts of data. All this data is fodder for analytics and insight deriving, and that’s exactly how businesses are using IoT data. Insights derived from product usage, product malfunctioning, customer behaviour, and other such situations continually help retailers and manufacturers to enhance customer experience and product enhancement. We had written an article a little while ago, describing how data analytics and AI both are going to influence IoT in the coming months and years. Read More about How to Manage Your Online Store in 2019? IoT-enabled retail is here to stay As you can see, IoT is quietly bringing formidable changes to both online and offline retail spaces. It is also changing the way retail manufacturers manage their business. Considering how quickly IoT is taking over retail, and how it is sustaining all the players in the space, it is worth observing the technology more keenly. In the near future, IoT enabled sensors will help retailers improve marketing, bring better customer experience, and enhance product support to users. Security may seem like an issue with all the IoT related data being generated, but we recently wrote about how to handle those issues. While we are at it, do take a look at some of the most valuable programming languages to learn, if you wish to develop for IoT yourself. Last but not the least, IoT will help businesses of all types to derive useful insights which will help improve products and customer experience at the same time.

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Disruptive Innovation in Payments

We could have written paeans about FinTech a couple of years ago, but to do so now would be to sing praises about what is already the norm. FinTech, the inevitable result of finance services making use of technology to enhance solutions and services, is the single largest disruptor in the world of finance. In addition to being a disruptive development, FinTech has evolved into becoming almost conventional, replacing legacy methods and making them seem archaic. Yet, a closer observation reveals that there is a lot of disruption taking place even within contemporary FinTech. Technology has driven FinTech to continuously evolve itself, and newer players continue to give a run for their competitors’ money almost every day. In this article, we briefly recap the growth of FinTech and contextually place this growth in a situation that continues to bring disruptive innovation in payments. We shall also take a look at certain trends driving this disruption, and what we can expect from this exciting development in the near future. The growth of FinTech While it may sound like a fancy term, FinTech isn’t actually very new. Using technology to drive financial procedures has been around since the 1900s in various forms. From being able to wire money to someone in a different part of the world to modern peer-to-peer payments, FinTech has come a long way. Barclays opened the first ATM in the world in 1967, and Wells Fargo kick-started the world’s first online checking account in 1995. PayPal came to being in 1998, and online transactions and payments have grown exponentially ever since. Apple Pay, which was announced in 2016, was another watershed moment, as it heralded a new smartphone-based payments solution. Finally, blockchain-based payment technology gave rise not only to cryptocurrency, but also to smarter payments, seamless insurance claims processing, loan disbursals, and contactless payments. We had recently written an article about how Blockchain is bringing winds of change to the insurance sector. Drivers of the change As we can see, FinTech has evolved dramatically in the last few years due to rapidly evolving technology. However, market behavior and changes within finance sector have also been major drivers of change. In this section, let us take a look at three aspects of this disruptive innovation in payments. Technological development It goes without saying that technology is a big reason for disruptive changes in FinTech. In particular, artificial intelligence and blockchain have caused tremendous changes in the finance sector, propelling drastic changes that have taken even FinTech players by surprise. For example, PayPal and other peer-to-peer payments solutions were taken by surprise when cryptocurrency came to being. Blockchain in fintech is the single-most disruptive situation at the moment. Cryptocurrency players like Bitcoin etc. were taken by surprise when Ethereum-based legal peer-to-peer payments application started to be launched. For instance, blockchain-based claims processing, stock purchase, and Ethereum-based P2P payments solutions are quickly taking over traditional smartphone-based payments applications. Smart contracts have enabled seamless and secure transactions, making financial procedures more reliable than they ever were. In fact, it wouldn’t be an exaggeration to call blockchain a cultural phenomenon. For an industry that focuses much of its energy on building and maintaining trust, blockchain and smart contracts-enabled applications are almost a godsend. It wouldn’t be an exaggeration to state that technology itself is driving change and causing more disruptive innovation in the field of FinTech. Those who aren’t part of this exciting evolution will quickly be left behind. In-store mobile payments are touted to exceed $503 billion by 2020. Just in the US, a whopping 150 million people are expected to use in-store mobile payments. The spending ability of mobile payments users is very high. They spend twice as much as non-users do, and earn at least $70,000 a year. Security-related doubts have been a hurdle for mobile payments adoption. 47% of cybersecurity professionals felt mobile payments weren’t secure enough at the moment, as opposed to just 23% feeling confident. Public Wi-Fi is the greatest vulnerability with respect to mobile payments, with a threat figure of 26%. This is closely followed by stolen devices, a situation whose threat figure is 21%. Market trends Increasingly, users have come to expect a lot more than what technology can offer at the moment. We can describe this as a market that’s so spoiled by choices that even the most disruptive technology no longer feels like disruption. Consumer behavior has shifted from being awestruck by disruption to expecting innovation by default. In other words, services that do not seem innovative enough for consumers simply get ignored. This has forced most industry players to closely study consumer behavior and surpass their expectations. This isn’t usually possible because users have come to expect a lot more than what technology realistically allows us to do. Yet, FinTech companies and solutions providers have to work harder to keep pace with market expectations ad and focus on driving change. Adopting innovation and complex technologies such as artificial intelligence, data analytics, and blockchain will help FinTech companies to surpass market expectations and bring value to the services they launch. Data analytics, in particular, can help FinTech entities to study consumer behavior closely and launch FinTech products that match market expectations. Industry changes There are a number of changes within the industry that are propelling disruptive changes within FinTech sector. Banks are desperate to retain their roles in the finance space, and payments intermediaries may simply vanish, because of smart contracts and distributed ledger technology. The same distributed ledger technology is helping FinTech organizations to make cross-border payments instantaneous, giving rise to new corporate and consumer solutions that will enable instant international payments a reality. Fintech companies have also begun to make use of open APIs, machine learning, and robotic process automation to enhance the experience. Most importantly, a lot of FinTech activity currently is focused on thwarting cyber-attacks, ensuring data privacy and safety, secure financial transactions, and eliminating payment frauds. Blockchain, smart contracts, artificial intelligence and machine learning are currently top

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Next-level Data Analytics and AI to Unlock IoT’s True Potential

To imagine that physical objects could be connected to the Internet and that they could communicate with each other at the same time seemed ludicrous even a decade ago to most people. However, Internet of Things (IoT) is real, and it is here. This system of connected devices connected to the Internet via sensors and churn out a large amount of data. IoT-enabled devices are no longer mysterious. They are used in the health sector, smart homes, vehicles, gadgets, and just about everywhere else. It shouldn’t come to us as a surprise that all these devices result in large volumes of data, adding to what is often called the Big Data. While this data may seem insurmountable, and sometimes even redundant, artificial intelligence and data analytics can empower users, manufacturers, and businesses to venture into unchartered territories. In this article, let us take a look at how artificial intelligence and next-level data analytics are helping to unlock the potential of IoT. What’s the problem with IoT today? While most devices manufactured today have some level of IoT enabled in them, there is a lacuna of sorts, when it comes to the actual utilization of the technology. This is because, at its simplest, IoT connects devices using sensors and Internet, but there is no way to really understand the data that is produced or to enhance features that already exist. While IoT has helped millions of people to communicate with their cars, homes, machines in factories, etc right from the smartphones, a lot of data that is churned out by these IoT-enabled devices is simply ignored. Artificial intelligence and advanced data analytics can help to put IoT data into perspective. Whether it is data from medical devices or from IoT-enabled cars, analyzing this deluge of data is humanely impossible. Next-level data analytics use predictive analysis, advanced statistics, and other methods to provide insights from both structured and unstructured data. Most importantly, ignoring all this valuable data can prove to be disastrous to the society as a whole. Data is too large and complex It is not humanly possible to derive useful insights from so much of data When data isn’t analyzed or understood, valuable opportunities are missed Underutilization of data may also result in disastrous outcomes The answer lies in next-level data analytics and artificial intelligence How can data analytics and artificial intelligence take IoT to the next level? Data Analytics derives meaningful conclusions by examining data sets of various sizes. Conclusions can be used to identify patterns, trends or even predict certain outcomes. These conclusions help businesses to improve their products and services, come up with better business strategies, and make effective decisions. In addition, deriving useful conclusions from datasets will help businesses to drive revenue and profits, and gain a competitive edge. Datasets that can be used from different sensors include: Data from video and audio streams Data from geo-location sensors Data related to product usage. This may or may not be linked to sensors. Data from social media System log files There are different types of data analytics that can be used with IoT-enabled devices. Some of those are: Streaming Analytics: This uses real-time data streams to track traffic, transactions, etc. This is most helpful to understand situations where immediate action is required. Spatial Analytics: As the name might suggest, this kind of analytics uses location-based data to understand trends in usage. Time-based Analytics: Using time-based data is important too, and provides valuable information about health, weather, product usage patterns, etc. Prescriptive Analytics: This uses predictive analysis, and sometimes includes descriptive analytics. This helps companies to improve products and services and has wide-reaching commercial uses. There are a number of ways businesses can take IoT to the next level by using Data Analytics. Data insights can be used for the purpose of marketing and product usage analysis. The insights can help not only consumers but also businesses. Video and audio analytics, social analytics, etc. are opening doors to analyzing emotions and behaviors of people. This can be particularly useful to avert emergencies in crowded places or to improve products. Turbo-charging IoT with Artificial Intelligence A Gartner study predicts that more than 80% of IoT projects will involve an AI element, and that is a whopping 70% increase from today’s situation. Most organizations are looking at machine learning and deep learning to unlock the potential of IoT. Machine learning identifies trends and patterns within data sets, and also pinpoints anomalies if any. Machine learning makes identification of patterns more accurate as it does not depend only on numbers, but also on other aspects. Speech and facial recognition, emotion and behavior analysis, and predictive maintenance are all aspects of AI that will help take IoT to the next level. Imagine being able to predict the time for servicing a gadget based on an individual’s frowning patterns? This can happen. Artificial Intelligence is also being used in risk management, and avert disasters and emergencies from occurring. Machine learning enables a software “agent” to identify patterns in a dataset and use those patterns to learn how to adjust the way it further analyses data. The best example would be movie recommendations on Netflix or playlists on Spotify and Apple Music. Machine Learning can identify usage patterns in IoT and help manufacturers to improve customer experience. On the other hand, businesses can benefit from the competitive edge, improved products and services, and enhanced revenue-making potential. Need for implementing AI and Data Analytics quickly As you can see, you cannot remove artificial intelligence or data analytics from IoT. IoT without these two important technologies will simply enable devices to communicate with other and there is no room for improvement of products and services or opportunities to identifies usage patterns and trends. Both Artificial intelligence and Machine Learning take IoT to the next level and help customers and businesses to unlock experiences and opportunities they never knew existed. The future of IoT certainly vested in the implementation of Artificial Intelligence and Data Analytics. Sooner

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