Emotion AI will disrupt your marketing strategy

It’s no secret that our emotions drive our behaviours. But what if brands could leverage those emotions to deliver powerful messages that truly resonate with consumers? Believe it or not, this is already a reality thanks to Artificial Emotional Intelligence (Emotion AI). This technology combines behavioural and sensory data enabling brands to hyper-personalise physical and digital experiences both, online and offline, thus increasing sales. So how will this technology fundamentally change the way we cater to consumers?

Artificial Emotional Intelligence

Emotion AI is a form of emotion detection technology. It enables everyday objects to recognise our verbal and non-verbal behaviour and respond accordingly. Numerous tech giants and startups have been investing in Emotion AI for over a decade using various means such as algorithms, facial recognition and voice analysis to recognise human emotions. This disrupting technology will likely affect all industries from video games to marketing. It has the power to create more personalised user experiences and could help brands achieve real-time empathetic marketing, a concept that was once thought to be impossible. At a time when consumers are demanding a more human approach to marketing, this tech could help accomplish just that.

The Potential Of Emotion AI

Humans still have the upper hand when it comes to reading emotions but machines are gaining more ground using their own strengths: analysing large amounts of data in the blink of an eye. All of this data allows brands to develop a deeper, more nuanced understanding of their customers through recognising and interpreting human emotions.

This technology can also be used to further engage customers and build lasting relationships with them. For instance, marketers could implement chatbots which use AI technology to identify a customer’s personality traits and what drives their emotional responses regarding a company’s product selection or services. Based on an individual’s answers, the chatbot could direct them towards the most appropriate website content or, alternatively, a live customer service agent.

Such a simple tactic can be used by all industries to deliver a more relevant message to consumers. This is particularly important for B2B companies as on average, according to Google research, B2B customers are more emotionally connected to their vendors and service providers than consumers. Because a B2B customer isn’t only buying for himself, but for their entire company, thus a strong emotional affection and connection with their supplier is important.

But it doesn’t stop there, this technology can also be deployed in real-time to analyse consumer behaviour in-store. For example, the retail industry could use Emotion AI to understand how shoppers really feel about what they are buying — or not buying. Small sensors and cameras around product displays could show how people feel about prices, packaging and even branding. If people look at a price tag and frown, it might be good to lower prices. Alternatively, if shoppers analyse a product’s packaging and appear confused, you might want to redesign or simplify that packaging.

Lastly, if emotional responses suggest frustration when it comes to shelf placement and aisle arrangement, a small layout reconfiguration might be in order. So, this technology could also cater to consumer’s needs offline.

The Change Will Be Slow

With the promise to measure and engage consumers based on something once thought to be intangible, real-time empathetic marketing holds great potential for brands. But the adoption of this technology will be gradual given the amount of data it captures and its potentially intrusive nature. Consumers are more and more concerned about their privacy on the internet and many feel very uncomfortable at the thought of a video capturing and analysing their movements and facial expressions. As a result, this will slow down the application of Artificial Emotional Intelligence in marketing.

However, if your company decides to use Emotion AI, a key aspect to winning over consumer trust is to be transparent about what you are doing, how you are doing it, and what exactly you will use this data for. Transparency is crucial given how invasive this technology could be. Additionally, you could offer your customers a value exchange as a way of thanking them for their contribution.

Taking Personalisation To The Next Level

In the near future, businesses will have to shift their focus when trying to understand their customers and move past traditional sales metrics, focusing more on direct and indirect customer feedback. Then, as AI capabilities continue to improve, companies can leverage demographical, behavioural, and emotional data to more accurately reach their desired target audience and give them both a marketing message but also a product that they truly want.

So though this technology is still in the early stages of development, it will allow brands to deliver more relevant messages to highly segmented audiences and give them more meaningful experiences.

Source: https://www.deptagency.com/story/emotional-ai-will-disrupt-your-marketing-strategy/

How IoT is improving the quality of Healthcare

IoT (Internet of Things) technology is penetrating deeply into everyday human life. Cars, kitchen appliances, and even heart rate monitors connected via the Internet into one network where they exchange data. For example, having received data from the alarm clock in your smartphone, an IoT coffee maker will know when you get up for work and brew coffee at your desired time, down to the minute.

However, one of the most promising areas for the implementation of IoT devices is in healthcare. According to a study, six out of ten global healthcare organizations are already using IoT devices.

There are several positive trends observed due to this:

  • Medical staff are becoming more mobile.
  • The process of collecting, transferring, and analyzing patient data, as well as making a diagnosis, is accelerated.
  • The effectiveness of medical care is increasing.

IoT Devices for Patients

Patient monitoring sensors are the area where IoT comes the most in handy. Being placed in operating theatres, intensive care units, and post-surgery rooms, these devices will monitor the vitals of patients, and in case of dangerous situations, immediately notify doctors.

Such devices will help not only doctors and patients but also their relatives. For example, if a patient is going to have a difficult operation, an online location sensor can be attached to the patient’s body, to which their family can immediately know when the surgery is finished and receive its results.

A special sensor-based inpatient monitoring platform is being used which reads the patient’s vital signs round the clock and allows the medical staff to instantly respond to deterioration. In the future, there are plans to equip patients with such devices in cardiology and intensive care departments.

Another good example is a wearable device, which can predict a forthcoming epileptic seizure.

In many regions, there is still no easily accessible medical care. The transition to telemedicine has become an effective solution for this situation. A patient far away from any clinic or hospital is able to consult with a doctor in real-time and receive the necessary assistance before going to a medical facility.

Medical Equipment With IoT Technology

Monitoring sensors for hospital equipment can significantly improve the quality of medical services. Due to limited budgets, medical facilities can’t afford frequent replacements of necessary equipment. As a result, outdated equipment is in constant need of repairs.

IoT sensors can assess the state of the equipment and inform engineers about defects. This will allow for a quicker response time to breakdowns.

IoT devices can also help in monitoring the condition of the hospital premises. For instance, the sensor will take temperature readings in laboratories, freezers, and wards. If the temperature deviates from the norm, it will be possible to return it to the desired level remotely via Wi-Fi.

When transporting medicines that require a certain temperature, refrigerators with similar sensors can be useful. They will maintain the necessary temperature independently.

The Role of IoT in Medical Facility Management

IoT can also be deployed in solving the administrative and management challenges of the hospital. For instance, with the help of IoT devices, it is possible to keep track of the number of pharmaceuticals, the condition of the equipment, as well as identify the need to purchase replacements.

The Netherlands is already adopting a similar strategy. One hospital has a network that allows its staff to view available equipment and get quick access to patient data. This helps to avoid confusion and reduces the waiting time for medical procedures.

Navigation in huge hospital complexes is a challenge for patients and their families. A special application can help them find the required doctor’s office or ward by creating a route inside the building.

In Conclusion:

The future of IoT is extremely promising. The recent events have only highlighted the potential of harnessing IoT, Artificial Intelligence and Machine Learning for their improved efficiency and the factor of safety they offer in the field of healthcare — even in times of unimaginable crisis as that of COVID-19.

At NeoSOFT, we empower businesses and healthcare by helping them leverage the right IoT technology that suits their requirement and needs. Our experts work end-to-end on solutions that go beyond the realm of problem-solving and strive to provide meaningful value-addition. Contact us to discuss your ideas and we will realise them with an uncompromising promise of efficiency and safety.

Source: https://dzone.com/articles/iot-in-healthcare-how-this-technology-will-improve

The future of storing and managing data: ETL vs. ELT

The data explosion has put a massive strain on the data warehouse architecture. Organizations handle large volumes and different types of data, including sensor, social media, customer behaviour, and big data.

If your organization has a data warehouse, you’re most likely using either the extract, transform, load (ETL) or the extract, load, transform (ELT) data integration method.

ETL and ELT are two of the most popular methods of collecting data from multiple sources and storing it in a data warehouse which can be accessed by all the users in an organization.

ETL is the traditional method of data warehousing and analytics, but with technology advancements, ELT has now come into the picture. But what exactly happens when “T” and “L” switch places? Let’s discuss.

What is the difference between ETL and ELT?

In ETL, data is extracted from varying sources such as ERP and CRM systems, transformed (calculations are applied, raw data is changed into the required format/type, etc.), and then uploaded to the data warehouse, also called the target database.

In ELT, after extraction, data is first loaded in the target database and then transformed i.e., data transformation happens within the target database.

That said, the difference between these two processes isn’t just confined to the order in which data is integrated. To understand their differences, you also have to consider:

  • The underlying storage technologies
  • The design approach to data warehouse architecture
  • The business use cases for the data warehouse

What Changed and Why ELT Is Way Better?

1. Cloud-Based Computation and Storage of Data

The ETL approach was once necessary because of the high costs of on-premise computation and storage. With the rapid growth of cloud-based data warehouses and the plummeting cost of cloud-based computation and storage, there is little reason to continue transformation before loading at the final destination. Flipping the two enables analysts to do a better job in an autonomous way.

2. ELT Supports Agile Decision-Making for Analysts

When analysts can load data before transforming it, they don’t have to determine the required insights to be generated before deciding on the exact schema. Instead, the underlying source data is directly replicated to a data warehouse, comprising a “single source of truth.” Analysts can then perform transformations on the data as needed, with the flexibility of going back to the original data without compromising on its integrity. This makes the business intelligence process incomparably flexible and safer.

3. ELT Promotes Data Literacy Across the Whole Company

When used in combination with cloud-based business intelligence tools, the ELT approach also broadens access to a common set of analytics across organizations. Business intelligence dashboards become accessible even to relatively non-technical users.

The Bottom Line: Here are Some Final Thoughts About ETL and ELT

ETL is outdated. It works with traditional data center infrastructures, which cloud technologies are already replacing. The loading time takes hours, even for businesses with data sets that are just a few terabytes in size. ELT is the future of data warehousing and efficiently utilizes current cloud technologies. It allows businesses to analyze large data sets with lesser maintenance and offers key insights to help make the right business decisions. With time, the scope of ELT will potentially expand as native data integration tools continue to evolve.


Artificial Intelligence in Modern Learning System

Almost every college and university has moved towards e-learning platforms due to the pandemic. The introduction of learning management systems have made it easier for schools, colleges, and universities to reach out to students.

Stats show that the retention rate for students taking classes online is more compared to traditional classroom learning. The learning management system has proved to be an added advantage. With schools and universities cautious about opening up, it seems like e-learning platforms are only going to be getting more popular.

With the implementation of AI, the education world is about to scale to new heights and transform the learning sector like never before. The education system has already seen some of the impacts that artificial intelligence and machine learning have brought about. The aim is to create a new era where every student can understand their full potential and serve the society in the best way possible. Here are the recent advancements in AI that are reshaping the industry.

1. Content Creation

AI has the potential of creating content that is free from errors and of top-notch quality. It can take the burden of creating accurate and unique source material off the institutions, as well as circulating it securely.

Books need not be in the conventional format. With the implementation of voice recognition, audio-books can be created. It is proven that audio-books are more effective than traditional books. For students suffering from dyslexia or who lack reading prowess, these methods prove to be of great help.

2. Smart Mentoring Systems

It is hard to expect a teacher to give equal attention to every student in a classroom. That is where smart mentoring systems have a significant role to play. Based on the capacity of the student and their ability to grasp things, classes can be handled accordingly. Each student has different learning needs. A mentoring system would work on the student’s abilities and design a course according to their individual capabilities.

Plenty of online educational training institutions have opted for such a mode of teaching. Smart mentoring systems will not only help the students but also assist the teachers in equipping themselves according to the capability of the classroom.

3. Augmented Reality

There is a theory that if you create an experience, it stays with you for a lifetime. Augmented reality is based on a similar concept. Implementing this into the education system can genuinely transform the experience of learning. Students get to experience knowledge in the real world rather than just theoretically learning about it.

From ancient history to complex biology, work continues to convert all the academic knowledge into augmented reality. A future awaits us where students get to relive the World War. The hologram is another such method that uses the same principle.

Augmented reality will not only improve the educational standards but will create a future where students will be better equipped to come up with sophisticated solutions to indefinite problems. A global renaissance can be expected with the implementation of this technology.

4. Personalized Learning

Is it reasonable to expect a student to be good at everything? There are still schools where students are asked to be good at subjects they are not interested in. To eradicate this, a new methodology called personalized learning will likely be introduced. Based on the student’s preferences, a virtual mentor would be assigned to handle classes. Just like while binge-watching Netflix, a recommender engine algorithm will be introduced that will help the student choose their preferred subject. Fuelled by this concept, the world can see a rise in specialised Digital Universities where anyone can learn whatever they want.

5. AI-Based Virtual Assistants

Alexa and Siri have vastly impacted our day-to-day lives. Imagine harnessing something like that solely for education. AI-based virtual assistants, equipped with information, can bring everything at the tip of your fingers. They kickstart a whole new era of modern education, where instead of a teacher, a bot would be training the students. The speed, efficiency, and capacity to handle a vast number of students will increase greatly.

Final Thoughts

The future of education is not to be mistaken with a competition between bots and human teachers. The quest behind all these advancements is to empower human teachers and reimagine the educating experience by assisting them with AI. The objective is to not replace but to enhance the experience of gaining and imparting knowledge in an efficient manner and updated with times.

Source: https://www.kdnuggets.com/2020/12/greatlearning-ai-modern-learning.html