Artificial Empathy: The Upgrade AI Needs to Talk to Consumers

  • Artificial empathy allows brands to target individual consumer needs.
  • AI can be used to analyze customer behavior at scale to gain personalized insights.
  • But artificial empathy still needs human input and interpretation to work most effectively.

In a proliferating multi-channel world, every brand must win the hearts and minds of consumers to acquire them and retain them. They need to establish a foundation of empathy and connection.

Artificial intelligence combined with a human-centric marketing approach may seem like a contrarian model. But the truth is that machine learning, AI, and automation are vital for brands today to turn data into empathetic, customer-centric experiences. For marketers, AI-powered solutions are a scalable and customizable tool that can understand the pattern of consumer interactions. That’s the power of artificial empathy: when brands target and connect with individual consumer needs on a deeper level than just transactional exchanges. When it comes to empathic machines, Hollywood may have made us think of people like Wall-E: robots with emotions. But artificial empathy is fundamentally about giving technology the ability to discover and respond to human emotions.

Artificial empathy and the application of data

Technology provides us with information about what the customer has done, but also nuggets and nuances that help anticipate future needs. But exploiting them means analyzing tons of data to detect larger patterns or changing preferences. Companies can’t just rely on research and data teams to glean what customers are returning to them. The need right now is to be active listeners with ears on the ground and an ability to react in real time.

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

• AI can detect behavior patterns and alert consumers to price drops or new stocking units for favorite items through notifications.

• Delayed or incorrectly addressed parcels benefit from an exclusive offer for the next order.

Artificial empathy and human contact

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

Human Pharmacyfor example, used an empathetic artificial intelligence service to help its call center teams manage customers more effectively through emotion analysis. The solution deciphers customers’ emotions through the mapping of behavioral patterns such as a delayed pause, increased speech speed or tempo. The analysis is relayed to the teams in messages such as “speak a little fast” or “address the customer a little more”. Such examples of empathetic AI will multiply in the future.

Artificial empathy is beneficial for advertisers to understand how customers emotionally connect with the brand. The information may be used to evolve content and messaging to optimize campaign performance. Machine learning algorithms combined with consumer behavior can offer suggestions to improve campaign performance. These algorithms can be deployed to refine demand forecasts and price sensitivity across target segments, while providing insights into buying behavior.

But while artificial empathy can help companies create more effective interactions, it cannot replace human interaction. The main requirement for making AI effective is human insight, contextual awareness, nuance and creativity. Businesses need to identify appropriate use cases for artificial empathy, and can then strategically implement its use in the services they provide to customers. The human touch combined with artificial intelligence can generate a better return on investment for targeted campaigns.

The impact on marketing

Marketers need to use artificial empathy to create campaigns that are humanized and not just mass-targeted. This is where it can be used to understand business needs and leverage data that can be distilled into simple terms. Campaigns can then be focused on delivering beneficial content to customers after understanding the pain points and challenges of the customer.

With ever-changing market conditions and constant disruption, brands need to empathize. Those who resent the consumer’s plight may fail to communicate in an appropriate tone and risk ingraining negative perceptions of their brand in the consumer’s mind.

A discerning survey by Dassault Systems with independent research firm CITE revealed that young consumers prefer personalization that improves the product experience or their quality of life. They are also willing to pay extra and share their data to get it.

Large volumes of unstructured data can be difficult to manage. But this technique allows marketing teams to react accordingly with relative ease. It can also be used to compare product features. Features and attributes that resonate with the target audience can be introduced or improved. It can also automatically differentiate emotions and attitudes and classify them as positive, negative or neutral using ML (machine learning) and natural language processing (NLP).

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

Our guidelines not only serve as a practical reference tool for governments seeking to adopt AI technology, but they also set baseline standards for effective and responsible public procurement and deployment of AI – from standards that may eventually be adopted by industries.

Example of a challenge-based procurement process referenced in the guidelines

Example of a challenge-based procurement process referenced in the guidelines

We invite organizations interested in the future of AI and machine learning to get involved in this initiative. Learn more about our impact.

A world where technology adapts to the user is not a distant dream. We are already seeing digital adoption becoming a crucial part of enterprise digital transformation, empowering CIOs and business leaders to decode and address adoption gaps in real time. As we move into the post-pandemic future where the distributed workforce becomes a business reality, the need for empathetic technology will only increase. But as our world becomes increasingly digital, it is also imperative to ensure that it remains fundamentally human.

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