AI Injects Empathy to Personalized Healthcare

Global healthcare is undergoing a personalization crisis. Overwhelmingly, there is a disconnect between what patients expect from their healthcare providers and what is actually provided. Public healthcare systems are under enormous strain to provide quality service. At the same time, resources are being slashed, while aging patients’ healthcare needs are becoming increasingly more complex.

Primary-care doctors spread too thinly 

A study carried out by Cambridge University and published in BMJ Open found that the average appointment time of UK patients with GPs is only 9.22 minutes. In Lithuania, Belgium, Portugal, Luxembourg, Iceland, Cyprus, and Peru, patients enjoy 15-minute consultations. In contrast, the average appointment ranged from 48 seconds in Bangladesh to 22.5 minutes in Sweden.

With these growing needs, there is an increasing shortage of healthcare resources globally. As a result, patients are being denied personalized healthcare experiences that meet their specific needs and cater to their personality, lifestyle, and medical history.  

Patients are really feeling the pinch. They would like to be heard and that their concerns will be taken seriously. They want tailored treatment plans that fit their individual healthcare needs and lifestyle. They want doctors who do not rush through an appointment, who listen and show they care, and who clearly explain what the patient needs to do next. Unfortunately, many doctors are spread so thinly, and their time is so severely limited that adequate treatment quality is nearly impossible. 

Personality-driven care  

Telehealth solutions are a growing trend that is spurring more personalized care for patients by integrating AI-powered technologies. Patients are empowered to take the lead when it comes to their own health and decision-making. At the same time, telehealth frees up doctors to give the personal care people want and need.

One of the more dramatic impacts that have shifted the conversation about personalized healthcare is INFI’s EmpathAI™. Powered by a humanlike, empathic avatar that integrates AI with validated psychological insights. It also acts as a conversational conduit with patients. This enables the understanding of precise traits, internal motivators, and real-time emotional states of each individual patient. With these insights, medical providers understand how to speak to each patient. As a result, patients will be more motivated to improve their adherence and can hyper-tailor treatment-related recommendations. Additionally, they can realize from real-time monitoring of psychological states the exact emotional and lifestyle issues that may be impeding recovery. 

Machine learning, over time, will continue to empower medical providers, helping them improve the effectiveness of any interaction among medical staff and patients. Care providers will get to know their patients’ personalities and lifestyles. They will be able to provide more accurate and truly personalized care.

People Buy Emotions, Not Things

With the global marketplace becoming ever more crowded and competitive, personalization has emerged as an indispensable tool for companies to stand out above the competition. However, the biggest challenge for brands in this arena is to hit it right with customers and meet their exact needs.

Make e-shoppers feel understood

Customers are weary of being treated like a statistic. They expect companies to treat them as individuals, anticipate their needs and provide relevant offers without even requesting them. When targeted with irrelevant messaging, they get frustrated, which tarnishes brand association. Therefore, to increase brand loyalty, brands need to make customers feel understood.But how can brands truly know what’s relevant for each customer? Which messages and products should they deliver to each customer, and how?

Until now, digital marketers have relied heavily on big data solutions to make broad assumptions about consumers, categorizing them as segments or personas. However, these methods fail to identify the ‘why’ factor – understanding the personality driving consumer behavior.

Why people buy

Personality types have a significant impact on how customers react to different products and services. People like to believe they are rational, intelligent creatures who make decisions through logical deduction. Turns out that we aren’t as savvy as we might want to think, and that people buy emotions, not products. Their purchasing thoughts and feelings are driven primarily by unconscious urges. They part with their hard-earned money to satisfy a desire, driven by hopes to avoid emotional pain, or to refuel illusionary comfort.

People’s needs are exhibited in different ways depending on their personality traits–those stable and consistent elements of our character which influence our behavior. Broadly, we will all experience the same needs, though, with varying intensities and at different intervals. A need for approval, a desire to feel emotionally fulfilled, to solidify an identity, to feel understood or respected–these are all needs and desires that are innate to human nature.

Personality is key

How someone experiences and satisfies these needs depends on each person. Some people have an outgoing personality, which translates into a stronger need for belonging. They would typically be engaged by a commercial message that highlights the social benefit of using the product or shows that other people from their social circle are using it. Others might have a fragile self-esteem, with a stronger need for status and appreciation, and could therefore be drawn to commercial messages that highlight elements of luxury in a product.

A deep understanding of people’s personality traits enables companies to transform how they personalize digital experiences. They can provide a far superior customer experience by powering every interaction with an empathic approach, by knowing how and when to speak to customers, and when to stay away.

Psychology-driven personalization

The entire journey can be customized to match the exact needs of customers, carefully designed to speak to elements of their personalities that they respond to best, including:

  • Content themes, e.g., emphasizing trendy vs. unique
  • Content types, e.g., more images vs. verbal messages
  • Content length, e.g., many details vs. bottom lines
  • Volume of messaging
  • Content turnover, e.g., rapidly changing and novel vs. stable content
  • Visual design and user interface

This psychology-based personalization can significantly contribute to maximizing the appeal, engagement, retention, and conversion rates of marketing platforms for numerous customer types. Find out how INFI is using psych-tech to help companies deliver flawless, hyper-personalized customer experience here.

Can personality insights yield a deeper level of personalization?


With the global marketplace becoming ever more crowded and competitive, personalization has emerged as an indispensable tool for standing out and rising above the competition.

Consumers are tired of being treated like numbers and expect to be treated as individuals. They often align their brand loyalty with the extent to which they feel understood. Consumers expect that companies will anticipate their needs and make relevant suggestions before they even make contact. When targeted with irrelevant messaging, users grow quickly frustrated and this kind of experience tarnishes –  sometimes irrevocably – brand association.

But how exactly are we supposed to know what is relevant for each customer? Which messages and products are we supposed to deliver to each customer, and in which way?

Until now, digital marketers have relied heavily on big data solutions to make broad assumptions about consumers, categorizing them as segments or personas. These methods fail to identify the ‘why’ factor – understanding the psychological factors driving consumers’ behaviors.

But why is this so important?

The constitution of personality types has a significant impact on how customers digest and are reactive to different products and services. Because although we all like to believe we are rational, intelligent creatures who make decisions through logical deduction, we aren’t as savvy as we might like to believe. Purchasing thoughts and feelings are largely driven by unconscious urges. People buy feelings, not products. They part with their hard-earned money to satisfy a desire, driven by hopes or to avoid emotional pain or to refuel illusionary comfort.

Our needs are manifested and articulated in different ways depending on the constitution of our personality traits – that is, stable and consistent elements of our personality that influence our behavior. Broadly, we will all experience the same needs, albeit at different intervals and, importantly, with varying intensities. A need for approval, a desire to feel emotionally fulfilled, to solidify an identity, to feel understood, to feel respected – these are all needs and desires that are innate to the human experience. But how strong and influential this needs is depends on the person. For example, some people with an outgoing personality have a stronger need for a sense of belonging, and would respond best to messages that highlight the social benefits reaped from using the product, or by showing social proof from their peers. Others may have a stronger need for status and appreciation, based on a fragile self-esteem dominating their personality, and would be drawn to commercial messages that highlight the high-status features of the product accordingly.

By understanding how these needs, emotions, motivators, and personality traits are holistically integrated in each person would allow us to entirely transform how we set about personalizing the digital experience. We can provide a far superior customer experience by powering our every interaction with empathy – knowing how and when to speak to customers, and when to stay away. The entire journey can be customized to fit the exact needs of customers, carefully designed to speak to elements of their personalities that they respond to best:

  • Content themes (e.g. emphasizing uniqueness vs. trendiness)
  • Content types (e.g. images vs verbal messages)
  • Content quantity (e.g. many details vs. bottom lines)
  • Volume of messaging
  • Content turnover (e.g. rapidly changing and novel vs. stable content)
  • Visual design & User Interface

This kind of psychology-based personalization can significantly contribute to maximization of appeal, engagement, retention and conversion rates of marketing platforms for various customer types.

Find out how INFI is using psych-tech to help clients deliver flawless, hyper-personalized customer experience here.

Why Buying Emotions Means More Than Buying Products in E-Commerce?

With the global marketplace becoming ever more crowded and competitive, personalization has emerged as an indispensable tool for standing out and rising above the competition.

Consumers are tired of being treated like numbers and expect to be treated as individuals. They often align their brand loyalty with the extent to which they feel understood. Consumers expect that companies will anticipate their needs and make relevant suggestions before they even make contact. When targeted with irrelevant messaging, users get frustrated, and this kind of experience tarnishes – sometimes irrevocably – brand association.

But how exactly are we supposed to know what is relevant for each customer? Which messages and products are we supposed to deliver to each customer, and in which way?

Until now, digital marketers have relied heavily on big data solutions to make broad assumptions about consumers, categorizing them as segments or personas. These methods fail to identify the ‘why’ factor – understanding the psychological factors driving consumers’ behaviors.

But why is this so important?

The constitution of personality types has a significant impact on how customers digest and are reactive to different products and services. Because although we all like to believe we are rational, intelligent creatures who make decisions through logical deduction, we aren’t as savvy as we might want to think. Purchasing thoughts and feelings are primarily driven by unconscious urges. People buy emotions, not products. They part with their hard-earned money to satisfy a desire, driven by hopes or to avoid emotional pain or to refuel illusionary comfort.

Our needs are manifested and articulated in different ways depending on the constitution of our personality traits – that is, stable and consistent elements of our personality that influence our behavior. Broadly, we will all experience the same needs, albeit at different intervals and, importantly, with varying intensities. A need for approval, a desire to feel emotionally fulfilled, to solidify an identity, to feel understood, to feel respected – these are all needs and desires that are innate to the human experience.

But how someone experiences and resolves these needs depend on the person. For example, some people have an outgoing personality and there for a stronger need for belonging, and they would benefit from a commercial message that highlights the social benefit from using the product or show that other people from their social circle have used it. Other people might have a stronger need for status and appreciation based on fragile self-esteem constructing their personality. They would be drawn to commercial messages that highlight the luxurious parts of the product accordingly.

By understanding how these needs, emotions, motivators, and personality traits are holistically integrated into each person would allow us to transform how we set about personalizing the digital experience entirely. We can provide a far superior customer experience by powering our every interaction with empathy – knowing how and when to speak to customers, and when to stay away.

 

The entire journey can be customized to fit the exact needs of customers, carefully designed to speak to elements of their personalities that they respond to best:

  • Content themes (e.g., emphasizing uniqueness vs. trendiness)
  • Content types (e.g., images vs. verbal messages)
  • Content quantity (e.g., many details vs. bottom lines)
  • Volume of messaging
  • Content turnover (e.g., rapidly changing and novel vs. stable content)
  • Visual design & User Interface

This psychology-based personalization can significantly contribute to the maximization of appeal, engagement, retention, and conversion rates of marketing platforms for various customer types.

Find out how INFI is using psych-tech to help clients deliver flawless, hyper-personalized customer experience here.

NLU and NLG — Going Deeper into NLP

By Gedalyah Reback
Reading Time: 2 minutes

Natural language processing is a wide and deepening field related to making AI more adept at working with human language. Inevitably, the field will spin off news disciplines for interacting with natural language in ways that are currently impossible.  

In order to fully comprehend and use language for itself, AI exploits NLP for several subprocesses to mimic how humans process language.

Two core stages of NLP – natural language understanding (NLU) and natural language generation (NLG) cover how AI digests and responds to human language. But this is only a very brief overview of a sophisticated, merely seconds-long process. 

These processes of understanding and reacting to language happen virtually simultaneously when humans converse with one another. Achieving a new fluent listening-and-response mechanism in a machine might be the holy grail of artificial intelligence in general, not just NLP. Known as the Turing Test, a machine whose language is so fluent it fools a human should be indisputably considered ‘artificially intelligent.’ 

Natural Language Understanding

Meeting the Turing standard is tough. No programmer is satisfied yet they have met 100 percent of the test’s criteria. But don’t worry, because INFI and a host of other teams are making rapid progress.

To reach this goal, machines must recognize, analyze, and respond to language input (what you might ask Siri or Alexa). The recognition of text dovetails tightly with NLU’s analysis, recognizing the correct words. NLU then parses input sentences and categorizes data or generates text summaries.

Many factors go into generating as deep an understanding of text or speech as possible. The context, user’s body language, semantic analysis, sentiment analysis, and opinion mining are critical to generating a deep understanding of text (or speech). 

Natural Language Generation

NLG is even more difficult – weighing these factors in order to come up with an acceptable response to the original input. Technologies you use everyday, open software like Google Translate, apply similar methods to other NLP apps. Phrase-based analysis and statistical models both contribute to various combo approaches to hatch suitable conversation responses.

Machine responses approximate or complement a user’s lexicon, speech patterns, tones, and attitudes in order to create as natural a conversation as possible. NLG thus involves lexical choices that prioritizes certain information over others. Subtasks like document structuringcontent determination, and referring expression generation (REG) make up a pretty intricate process. 

The Next Phase of NLP

Most systems today fail to adequately factor in user sentiment (much less fluctuating attitudes) into their NLG-backed responses. This is the case from machine translation to avatar-based customer service. By calculating personality, user sentiment, and short-term moods, INFI Avatars constitute an advanced application of NLG. As a result, our approach to generation that is more fluid, depending on context and the timing of user interactions. 

As the field develops, system updates will integrate new language models. AI’s next major hurdle might be a better sense of nuance and cogently incorporating that skills for itself in NLG.