Over the past year, keeping up and responding to customers has become a feat for businesses. In today’s digital world, contact centres are juggling more conversations than ever before and on an increasing number of channels. Without a doubt, digital customer service is no longer a luxury but a customer expectation.
As the terrain of customer experience (CX) evolves, so should service delivery. This means digital transformation shouldn’t include more of the same outdated, reactionary tactics such as customer surveys or net promoter scores. The pulse of business today requires more effort.
The businesses wanting to differentiate themselves already understood the secret to modern CX lies in interaction analytics. In this article, I discuss the requirements of successful customer interaction analytics implementation in contact centres.
The missing piece of customer insights
Customer interaction analytics refers to the process of uncovering meaningful insights from unstructured customer interaction data – also known as free-form conversations. If you think of modern CX like a puzzle, interaction analytics is the missing piece – the final one you need to bring the picture together. Contact centres have mountains of disorganized customer data in their calls, chats, emails, social media, online reviews, forums and more. These free-form conversations reveal the true voice of the customer and yield important insights.
Nearly 95% of customer feedback today is considered unprocessed data, which means organizations that don’t mine deep into customer conversations have incomplete puzzles and lack holistic views of their CX management. Contact centres need a way to capture, analyze and leverage their treasure troves of customer insights.
The right way of analyzing customer insights
Savvy businesses understand that managing customer interactions has to be proactive. Modern CX, analytics and engaging platforms are required for setting this plan into action. The question is, however, how to start implementing the right solution.
First, contact centres need technology that analyzes the conversations between agents and customers, wherever they’re taking place. The right interaction analytics solution will employ natural language processing (NLP) and natural language understanding (NLU) to automatically surface actionable insights from the dialogue, such as the reason for contact, areas of high effort, empathy issues, or topics that evoke highly negative or positive emotions.
The organizations furthermore need a way to prioritize the insights they’ve collected. The customer interaction analytics offers help to the contact centres by giving them the possibility to distil the chosen criteria into single, unifying measurements through the process of intelligent scoring. The resulting intelligent scores help accelerate decision-making because the businesses themselves determine the criteria of importance. Intelligent scoring taps NLU to ensure the customer interactions are objectively, transparently, and consistently scored.
With interaction analytics, organizations can proactively identify customer issues, determine their root causes, and confidently act to resolve them. Intelligent scoring also surfaces opportunities for the contact centre and the business itself to improve. Examples include agent training, compliance, and sales efficacy.
Modern metrics guiding digital service success measurement
As the terrain of modern CX has evolved, so have the metrics supporting it. Enterprise businesses must determine how they measure the digital customer service they provide. Here are three key metrics known as the “three Es” that customer interaction analytics can evaluate:
- Customer Effort: An effort score evaluates the level of effort a customer has to exert to interact with an organization or its product. This metric matters because research correlates higher effort with higher customer dissatisfaction. Businesses need to understand the factors behind the customer’s effort to meet his or her needs, eradicate points of friction and mitigate the risk of churn.
- Customer Emotion: This key metric reflects the emotional connection customers have formed with a business or a brand. Emotional intensity is important because research indicates emotions inspire customer decisions and impact long-range customer journeys. Brands can design and tailor programs – like marketing or training – when they can identify the emotions expressed in customer interactions and gauge the strength of their intensity.
- Agent Empathy: Front-line customer service teams are an important influencer of customer emotion. How empathetic an agent is can make the difference between a happy customer willing to recommend a product or service and an unhappy customer tweeting to the world about a negative experience. Measuring agent empathy and its relationship to customer satisfaction can have strong impacts on customer retention, loyalty and repeat sales.
Taken individually, these metrics reflect important aspects of the customer journey today. Collectively, they reveal the true voice of the customer and give organizations a framework for continuous improvement and consistent, modern CX. Customers are empowered in today’s digital world, but organizations can be too. The secret lies in their approach to CX. With the right technology, businesses can not only keep pace with the pulse of business today but leverage it to their advantage.