In our last article, we discussed the implications of generative AI at all touchpoints of customer experience for contact centers. We also touched upon the importance of human to human interactions. In this article, we will discuss relationship intelligence for improving customer experience (“CX”) in the age of generative AI.
AI large language models (“LLMs”) can be trained to come up with empathetic and emotional verbiage to support people emotionally (sometimes even better than what humans can do). However, in addition to job losses, the danger of humans trusting and relying on AI machine learning for emotional and psychological support is to deepen social isolation among the human community, thus diminishing humanity.
Philosophically and practically, it defeats the social aspect of humanity if and when humans turn to AI for empathy and emotional support, instead of to humans.
On the premises that (a) human happiness is to a large extent based on relationships, social connections, creativity, and other factors, and (b) the purpose of AI is to free humans to better connect and support other humans directly, rather than replacing human-to-human connections, we are going to explore relationship intelligence for improving human-to-human interactions and relationships. We will also discuss using AI “relationship intelligence” to improve CX.
Relationship intelligence is defined very differently for different purposes. There is the verbatim understanding of the two words as “intelligence for relationships”, similar to emotional intelligence (“EQ”) and emotional regulation involving understanding our own and others needs and wants, feelings, beliefs, interests, and values, and “ [the] insight for adjusting your approach to make interactions more effective.” https://www.td.org/atd-blog/what-is-relationship-intelligence
Recently, “relationship intelligence” has been used in association with AI and machine learning, and is described almost like business intelligence: “Relationship Intelligence is using data analytics, machine learning, and other advanced technologies to understand and interpret the complex web of relationships between individuals, groups, or entities. It aims to provide actionable insights into relationship patterns, behaviors, and potential opportunities. Unlike traditional CRM (Customer Relationship Management) systems focusing on transactional data, a Relationship Intelligence tool digs deeper into emotional and behavioral aspects.
For example, suppose you are a private equity investor looking to connect with senior leadership from a particular firm or a VC trying to get in front of a startup CEO. Relationship intelligence data can provide the ‘intelligence’ to instantly find who in your team’s network can facilitate a warm introduction by using a relationship strength score to identify if any of your colleagues know someone at the firm you want to engage with.” “[R]elationship intelligence uses communication data to uncover new opportunities you did not know existed before, making your firm more efficient and competitive.” https://www.4degrees.ai/blog/what-is-relationship-intelligence
For the convenience of analysis in this article, let’s use “relationship intelligence” as its verbatim meaning related to EQ, and use “RQ” when referring to AI related use of the same term.
It takes commitment, training, and practice to increase relationship intelligence.
More than a one-time Powerpoint presentation, companies need to offer programs for coaching, implementation, and constant iteration to ensure what is taught is actually executed in alignment with CX goals. Relentless practice can drill new skills and habits for relationship-building that improves every human-to-human interaction, both within the workplace and externally in dealing with customers.
This relationship intelligence muscle-building is not just a nice thing to have, but the centerpiece of strategies for increasing productivity and revenues: since happy employees create happy customers, CSAT (customer satisfaction) is the result of elevating ESAT (employee satisfaction), teamwork, morale, and EQ.
When the internal workforce is interconnected and supportive of one another as a community, they become more motivated, energized, and productive, resulting in higher quality of customer experience and more customer acquisition, retention, and loyalty.
To achieve these goals, CX leaders and staff first need to learn and practice relationship intelligence skills among themselves, to create a vibrant and thriving work environment that:
Relationship intelligence programs need to focus on the specifics, one step at a time, such as:
CX professionals sometimes face customer confusion and frustration, or worse, their anger and insults. To maintain their mental health and also to retain customers, frontline agents need to learn how to turn negative emotions to positive reactions. It is the responsibility of the company to drill healthy ways of handling frictions and conflicts.
Training to recondition our brain’s automatic and impulsive emotional reactions (stimulus-response behaviors) can save CX staff’s mental health and customer relationships, improve customer experience, increase sales and revenues.
Acquiring and applying the reconditioning skills – to (re) wire our brains by viewing the negative with a positive “spin” – takes education, training, practice, time and commitment.
Empathy is the foundation of communication. Communication is key to building trust. What blocks empathy is often bias and prejudice.
All humans have biases, but that’s not the end of the story. To overcome stereotyping, prejudice, bias, and judgmental tendencies, leadership needs to first instill the principle that everyone deserves to be treated with respect and dignity.
Principles without execution are just talk. Next is to design procedures, processes, and systems for the workforce to carry out human-centered customer experience at every touch point of customer journey.
Designing a system of rewards will reinforce behaviors, habits, and results. Implementation also needs processes and procedures for accountability, in order to achieve measurable CX goals.
As we improve human-to-human interactions with all of the above people skills or soft skills for relationship intelligence, at the same time, we can train AI to facilitate this endeavor by quantifying and measuring it with RQ data.
AI machine learning LLMs can help CX teams identify behavioral patterns, customer friction and paint points as well as opportunities. AI can help humans gain customer relationship insights. (The CX workforce needs to upskill and reskill, to develop technical literacy and data fluency for using AI tools.)
The AI RQ tool is based on human interactions, for the purpose of improving relationship intelligence and customer experience. If done right, AI and the human workforce can form a healthy feedback loop that enables trust building, customer satisfaction, customer loyalty, repeat business, referrals, cross selling, up selling, and profitability.
Internally, there will be better team dynamics, more collaboration, deeper relationships and stronger support – all will improve performance, ROI, creativity, job satisfaction, employee retention, individual and corporate growth.
The art and science of relating to others, is a never ending process.
©Jerry Briggs all rights reserved.
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