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Home News Media business

EQ: The most powerful skill for customer service

Striking the balance between AI and human empathy in the customer service journey.

by Liezel Jonkheid
July 8, 2024
in Media business
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EQ: The most powerful skill for customer service
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In an era where AI dominates conversations about customer experience, there is a palpable fear among customer service agents about their continued value within contact centres. 

Will AI replace a workforce segment already plagued by high turnover? Imagine securing your first job as a call centre agent, only to learn that company strategies increasingly focus on cost-saving measures, including replacing humans with AI for customer service.

Despite the strong case for AI in customer service, it is unlikely to replace humans entirely, especially in complex service scenarios. The significant cost-saving benefits of using AI for knowledge sharing are undeniable.

However, AI struggles to resolve intricate issues, which underscores the irreplaceable value of human agents who bring empathy, intuition and sincerity to the table – EQ.

The pessimism that AI and tech will make more jobs redundant in the customer contact sector and mark the end of human agents is misplaced. If anything, technological advances massively improve customer experience by facilitating better human connections and more meaningful depth of engagements between customers and agents.

A paradox

In many respects the human vs AI debate is a paradox; the reality is that most job roles have been made fundamentally better, more efficient, and meaningful thanks to technology. The adoption of technology and AI is an irrefutable fact and need in business in achieving operational efficiencies, cost savings and progress.

However, while the case for AI in repetitive and simplistic customer service channels cannot be discounted, if anything the need for human EQ – empathy – in delivering great customer experiences in a tech-driven world, is in fact only heightened.

Customer service and experience with their many complex and nuanced facets, are very unlikely to be delivered using AI only.

Strategic deployment of AI in human-led customer service

To effectively integrate AI in customer service, companies must thoroughly analyse the nature of incoming customer queries. Queries related to information gaps can be clustered for self-service options.

The biggest challenge in current AI deployment is the over-reliance on the tech teams, leading to generic responses that fail to address real customer needs or create the desired experience.

Often, it seems chatbot interfaces are designed by tech teams without consulting customers, or CX teams, and they are often prone to overuse. This results in responses that lack basic UX or content intelligence, requiring significant customer effort to navigate.

This unintuitive user experience frustrates customers across generations, making it difficult to reach a human when needed on more complex queries. If a customer finds themselves locked in a frustrating bot process and unable to get through to a human agent, the door is wide open for an aggravating experience and irate customer.

Such ‘self-help’ options can easily disempower customers, creating more tension and less satisfaction, which does not serve the company’s interests.

Balancing technology and human EQ

The challenge is in striking the balance between both worlds. Purpose and the point of the customer interaction should be well considered when it comes to deploying technology in a customer service journey – timing and purpose are everything.

To leverage technology in customer experience, particularly in customer support, companies should focus on:

  1. Identifying and ringfencing simple queries: Basic knowledge-sharing and repetitive queries can and should be managed through self-help options. This requires analysing categories of queries, complaints, and issues to identify those that can be handled broadly and channeled through self-service channels.
  2. Complex queries for human agents: When a query requires context, interpretation and explanation, it should be handled by well-trained human agents. The right individuals must be recruited and trained to manage these interactions effectively.

Challenges in customer support services

Several fundamental challenges hinder effective humanised customer support:

  • Wrong people: Recruitment strategies often focus on filling seats in contact centres rather than selecting agents as company representatives, according to their attitude and aptitude towards serving and problem-solving. High turnover due to a pressurised work role, lack of support, and inadequate remuneration result in lost collective and institutional knowledge, increased recruitment and retraining costs and negative impact on brand reputation! Outsourced CX, done badly, often lacks an emotional connection to the company, and in turn its customers.
  • Wrong training: Training often focuses too much on products and processes, neglecting the development of hard skills to handle complex issues and human diversity that require empathy and sincerity. This typically leaves agents ill-equipped to handle and resolve the challenging customer conversations.
  • Wrong support: Call centre agents often lack mental resilience, life experience, and business acumen. Without emotional intelligence, experience and mentorship, agents struggle and may dehumanize interactions to cope with stress.
  • Wrong process: Unfiltered queries channeled through call centres will increase volumes, with agents having to handle all issues from the mundane and repetitive, instead of focusing on the higher level, complex ones that demand human intuition, empathy and problem-solving.
  • Wrong measurement: Industry metrics focusing on volume and turn-around times rather than the quality problem-solving lead to wrong outcomes-activity over results.
  • Wrong mindset: Misaligned customer and company ambitions result in efforts to avoid and even ignore rather than solve customer problems and challenges.

Building an efficient customer support team

Once basic knowledge-sharing is automated, focus on building a team that truly represents your company. This begins with recruiting the right personalities. Candidates should embody the company’s customer promises and undergo thorough onboarding to align with desired experiences.

Joey Coleman’s Never Lose an Employee Again highlights key principles for developing a strong team:

  • Craft job descriptions to attract suitable candidates
  • Develop strategies to counter new hire remorse
  • Make onboarding memorable
  • Accelerate acclimation to enhance satisfaction and productivity
  • Re-engage existing employees to foster loyalty and commitment

Incorporating emotional intelligence as a hard skill in the onboarding program is essential. Practical exposure through simulated scenarios prepares agents for real interactions.

Continuous quality improvement is supported by engaging experienced staff to mentor new hires and providing real-time on-the-job quality assurance and training.

Providing the right tools

A thorough assessment of what service agents need to effectively perform their tasks, and thrive, is crucial. This includes investments in CRM systems that provide a single view of the customer at any point in time, thorough training to understand products and services, and processes that support customer solutions. Empowerment to make decisions is also key.

Agents should have the authority to go the extra mile and ensure customers leave satisfied – this is exemplified by Ritz Carlton’s policy of giving staff $2000 to resolve guest issues without prior approval, and Zappos’ commitment to passionate customer service.

The most successful customer service contact centres are staffed with specially trained agents who are able to focus on handling complex queries, by separating simple knowledge-sharing and repetitive functions through self-help channels.

Using AI technology for basic tasks while deploying emotionally intelligent, empowered agents for complex issues ensures customers receive exceptional problem-solving and empathetic support.

On more complex customer service needs, even the most intelligent chatbot is not going to deliver on your customer needs and experience as effectively as a well-trained agent.

While AI fulfils a supportive role to streamline processes in simple transactional and informational conversations where it makes sense to do so, it simply is not a replacement for the EQ of an well-trained, professional customer service agent.

Ultimately, it’s about fully understanding every touchpoint in your customer’s journey, deploying the right interventions, the right technology and the right agents at the right time.

 

 

Liezel Jonkheid is director and founder of the Consumer Psychology Lab.

 

 


 

Tags: AIartificial intelligenceConsumer Psychology Labcustomer serviceCXemotional quotientEQLiezel Jonkheidretail

Liezel Jonkheid

About Liezel Jonkheid (CCXP) Liezel Jonkheid is a CX specialist and seasoned CX and qualitative researcher. She is passionate about consumer behaviour, in particular the role of emotion and the subconscious in customer experience, buying behaviour and loyalty. She pursues the dream of creating better experiences for consumers by humanising customer experience. Her training and experience in the social sciences, communications, marketing, qualitative research, public relations, business and customer experience management have provided her with a deeper understanding of the complexities of human (and consumer) behaviour and emotions. She helps brand owners to design their customers’ response to engagement with the aim of retaining and growing the business. Liezel is the owner of The Consumer Psychology Lab. She holds degrees in Social Work (BA Cum Laude) from the University of Pretoria, Marketing Management (Cum Laude) at University of Johannesburg and is an accredited Public Relations Practitioner (APR, PRISA) and a Certified Customer Experience Professional (CCXP, CXPA) and member of CXPA. Liezel is a regular a guest lecturer on marketing, research and customer experience management and research at UJ.

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