Artificial empathy: the upgrade AI needs to speak to consumers

In a proliferated, multi-channel world, every brand needs to win the heart and mind of the consumer to acquire and retain them. They need to set up a foundation of empathy and connectedness.

Artificial intelligence combined with a human-centric approach to marketing might seem like a contrarian model. But the truth is that machine learning, AI and automation are vital for brands today to transform data into empathetic, customer-centric experiences. For marketers, AI-based solutions serve as a scalable and customizable tool capable of understanding the motive behind consumer interactions. This is the power of artificial empathy: When brands target individual consumer needs and connect with them at a deeper level than mere transactional exchanges. When it comes to empathetic machines, Hollywood may have made us think of the likes of Wall-E: robots with emotions. But artificial empathy is fundamentally about giving technology the ability to discover and respond to human emotions.

Technology provides us with insights about what the customer has done, but also nuggets and nuances that help anticipate future needs. But to mine them means analyzing reams of data to detect wider patterns or evolving preferences. Businesses cannot just rely on research and data teams to glean what customers are throwing back at them. The need right now is to be active listeners with ears on the ground and an ability to respond in real time.

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

• AI can detect patterns of behaviour and alert consumers of price drops or new stock-keeping units for favourite items through notifications.

• Delayed or wrongly addressed packages get an exclusive offer for the next order.

The digital consumer today is always on. Herein lies the opportunity to create exceptional experiences while retaining the hearts of consumers all the while. Many labs are designing software to understand and respond to how what humans say and how they feel. The applications of artificial empathy are wide-ranging, from market research to transportation to advertising to customer service.

Humana Pharmacy, for example, used an empathetic AI service to help its call centre teams handle customers more efficiently through emotion analytics. The solution deciphers the emotions of clients through the mapping of behavioural patterns such as a delayed pause, a rise in speech speed, or tempo. The analysis is relayed to the teams in messages such as “speaking a little fast” or “relate to the customer a bit more”. Such examples of empathetic AI will increase in the future.

Artificial empathy is beneficial to advertisers in understanding how customers emotionally connect to the brand. Insights can be utilized to evolve content and messaging to help optimize campaign performance. Machine learning algorithms combined with consumer behaviour can offer suggestions for improving campaign performance. Such algorithms can be deployed to fine-tune demand forecasting and price sensitivity across target segments along with providing information on purchase behaviour.

But while artificial empathy can help businesses create more effective interactions, it cannot replace human interaction. The primary requisite that makes AI effective is human insight, contextual awareness, nuances and creativity. Businesses must identify appropriate use cases of artificial empathy, and can then strategically implement its use into the services that they provide to customers. The human touch combined with machine intelligence can drive greater return on investment for targeted campaigns.

Marketers need to use artificial empathy to create campaigns that are humanized and not just mass-targeted. Here is where it can be utilized to comprehend business needs and harness data that can be distilled in simple terms. Campaigns can then be focused on providing beneficial content to customers after understanding the pain points and challenges of the customer.

With evolving market conditions and constant disruption, brands must demonstrate empathy. Those who fail to appreciate the consumer 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 by Dassault Systems with independent research firm CITE revealed that younger consumers prefer personalization that enhances the product experience or their quality of life. They are also ready 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 enhanced. It can also automatically differentiate between emotions and attitudes and classify them as positive, negative, or neutral using ML (machine learning) and natural language processing (NLP).

A world where technology adapts to the user is not a distant dream. Already we see digital adoption becoming a crucial part of enterprise digital transformation, allowing chief information officers and business leaders to decode and address gaps in adoption 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 digitized, there also is a clear imperative to ensure it remains fundamentally human.