Artificial empathy: the upgrade AI needs to speak to consumers

Artificial empathy: the upgrade AI needs to speak to consumers
  • Synthetic empathy allows brands to target individual consumer needs.
  • AI can be used to analyze customer behavior at scale to gain customized insights.
  • But artificial empathy still needs human input and explanations to function most effectively.

In a pervasive, multi-channel world, every brand needs to win the heart and mind of the consumer to gain and retain it. They need to create a foundation of empathy and bonding.

AI combined with a human-centred approach to marketing may seem like a paradox. But the truth is that machine learning, artificial intelligence, and automation are vital components for today’s brands to transform data into empathetic customer-centric experiences. For marketers, AI-based solutions act as a scalable and customizable tool that is able to understand the motivation behind consumer interactions. This is the power of artificial empathy: when brands target and connect with individual consumer needs on a level deeper than just transactional exchanges. When it comes to empathetic machines, perhaps Hollywood made us think of their ilk Wall-E: Robots with emotions. But artificial empathy is primarily about giving technology the ability to detect and respond to human emotions.

Artificial Empathy and Data Application

Technology provides us with insights into what the customer has done, but also minute details and nuances that help anticipate future needs. But extracting it means analyzing packets of data to discover broader patterns or evolving preferences. Companies cannot rely solely on research and data teams to extract what customers give them back. The need now is for us to be active listeners, ears on the ground and the ability to respond in real time.

Artificial empathy in marketing begins with a consumer-centric perspective and is embodied in insights that reflect the data collected from the brand’s customers and the meaningful next steps that should be taken. It combines data intelligence, artificial intelligence, and predictive modeling tools for all critical moments, including websites, store visits, social media or customer service. some examples:

• AI can detect patterns of behavior and alert consumers of price drops or new SKUs for favorite items through notifications.

• Late or wrongly routed packages get an exclusive offer for the next order.

Artificial empathy and human touch

Today’s digital consumer is always working. Herein lies the opportunity to create exceptional experiences while retaining consumers’ hearts at all times. Many labs design software to understand and respond to what people say and feel. The applications of artificial empathy are wide-ranging, from market research to transportation to advertising and customer service.

For example, Humana Pharmacy used an empathic artificial intelligence service to help its call center teams engage with customers more efficiently through sentiment analytics. The solution removes customers’ emotions by mapping behavioral patterns such as pausing, increasing speech speed, or cadence. The analysis is conveyed to the teams in messages such as “speak a little faster” or “connect with the customer a little more”. Such examples of empathic AI will increase in the future.

Synthetic empathy is useful for advertisers in understanding how customers emotionally connect to a brand. Insights can be used to develop content and messages to help improve campaign performance. Machine learning algorithms along with consumer behavior can provide suggestions for improving campaign performance. These algorithms can be deployed to adjust demand forecasting and price sensitivity across target segments along with providing information on buying behaviour.

But while artificial empathy can help companies create more effective interactions, it cannot replace human interaction. The prerequisite that makes AI effective is human insight, contextual awareness, nuance, and creativity. Companies must identify appropriate use cases for artificial empathy, and they can then implement its use strategically in the services they provide to customers. Human touch combined with machine intelligence can increase the ROI for targeted campaigns.

Impact on Marketing

Marketers need to use artificial empathy to create campaigns that are humane and not just collectively directed. Here is where it can be used to understand business needs and harness data that can be summed up in simple terms. The campaigns can then focus on providing useful content to customers after understanding the customer’s pain points and challenges.

With evolving market conditions and constant turmoil, brands must show empathy. Those who fail to appreciate a consumer’s predicament can fail to communicate in an appropriate tone and risk entrenching negative perceptions of their brand in the consumer’s mind.

An insightful survey conducted by Dassault Systems with independent research firm CITE reveals that younger consumers prefer personalization that enhances the product experience or quality of life. They are also willing to pay extra and share their data to get it.

It can be difficult to manage large amounts of unstructured data. But this technique allows marketing teams to react accordingly with relative ease. It can also be used to compare product features. Features and features that resonate with the target audience can be introduced or improved. It can also automatically distinguish between feelings and situations and categorize them as positive, negative or neutral using ML (machine learning) and natural language processing (NLP).

The World Economic Forum Center for the Fourth Industrial Revolution, in partnership with the UK government, has developed guidelines for the most ethical and efficient government procurement of artificial intelligence (AI) technology. Governments across Europe, Latin America, and the Middle East are experimenting with these guidelines to improve AI procurement.

Our Guidelines not only serve as a useful reference tool for governments looking to adopt AI technology, but they also define essential standards for effective and responsible public procurement and AI deployment – ​​standards that industries can eventually adopt.

An example of the challenge-based procurement process mentioned in the Guidelines

An example of the challenge-based procurement process mentioned in the Guidelines

We invite organizations interested in the future of artificial intelligence and machine learning to participate in this initiative. Read more about our impact.

A world where technology adapts to the user is not a distant dream. We are already seeing digital adoption become an important part of organizations’ digital transformation, allowing CIOs and business leaders to decipher and address adoption vulnerabilities in real time. As we move into a post-pandemic future where a distributed workforce becomes a business reality, the need for empathetic technology will only increase. But as our world becomes increasingly digital, there is also a clear necessity to ensure that our world remains fundamentally human.


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