How Predictive and Generative AI are Turning Support Centers into Revenue Streams

Acquiring a new customer is five times more expensive than retaining a current one, which can mean the difference between a thriving enterprise and one forced to close its doors. Even an incremental percentage increase in customer retention produces positive revenue growth, but to accomplish this, companies must be willing to invest in and focus on their customer support experience.

Business leaders must stop viewing customer support as a “cost center” and start thinking about it as a powerful revenue driver. A new era in transformational next-gen customer support is already here, and the key to unlocking this potential lies in ensuring your organization can integrate and harness the latest predictive and generative AI technologies within your existing support ticketing systems.  

By leveraging advanced AI solutions and their ability to sift through every customer interaction, support managers have newfound access to indicators and information previously buried in the avalanche of support cases. Additionally, thanks to rapidly advancing generative AI technologies like ChatGPT, the quality and consistency of every customer interaction can be significantly improved. Generative AI’s data interpretation makes it essential for solving common customer service challenges like siloed customer data, daunting backlogs, and limited visibility into customer churn. These issues also lead to agent attrition and burnout, further impacting customer support operations. 

AI’s enhancements to customer support are not limited to just improving service quality and creating quicker resolutions – they can improve product development and proactively prevent future customer service headaches for both the customer and the agent. This is a significant sea change as AI becomes a critical component for enhancing the agent experience, improving problem-solving capabilities, and the key to building lasting, loyal relationships with existing clientele. 

With AI’s new role in creating faster, better, stronger customer agents, businesses now have the power to reposition customer support as an important revenue-driving asset while unlocking new growth opportunities. Below are a few key ways to take your organization’s customer service departments to the next level with the right AI integration. With these strategies, you can start acting on customer insights right now.

Making Customer Support More Human

At the center of the AI-driven customer support revolution is the real-time ‘observability’ that these new capabilities bring. With the ability to analyze vast customer support data across cases, chat logs, and email interactions, Large Language Models (LLMs) extract what matters most – the voice of the customer. LLMs help agents identify patterns, trends, and customer preferences that might usually be overlooked. Being able to anticipate customer needs, and tailor their products and services, bolsters long-lasting customer relationships.

Today’s AI technology offers centralized platforms that provide companies with a comprehensive view of operational metrics, spanning various systems of record, systems of engagement, and monitoring of both human and virtual agents. This unification empowers support management teams to avoid expensive data migrations caused by integrating multiple ticketing systems and ensures that the support experience delivery is consistent. By emphasizing both the customer and agent experience equally, AI-driven technology enhances the human element of customer support, making it more responsive, personalized, and ultimately more successful. 

Predicting and Preventing Escalations

To truly scale, support organizations must start by reducing costly customer escalations – the fire drills that pull teams from their priorities and take up precious resources. Of course, escalations also negatively impact the customer experience and put a strain on account relationships. So, how can AI help?

AI, specifically machine learning and natural language processing (NLP), can comprehensively assess the risk of a customer escalating by analyzing warning signs from recent and prior support interactions to predict future ones. Escalation prediction software is like having each support manager trained as a highly-sensitive detective and then turning them loose on your entire case queue every hour. With AI’s help in identifying potential escalations before they start, businesses can more proactively resolve the issues and allow customer service managers to allocate resources more efficiently. The customers benefit directly, as their perhaps subtle signals get the attention they deserve and a faster resolution.

Enhancing the Agent Experience

Inflation is increasing at the fastest pace in 40 years, and hiking interest rates are prompting businesses to prepare for a possible recession in conjunction with record-level quitting, leaving many in the lurch to find and retain quality talent. The customer support experience is becoming more important than ever in attracting and maintaining a strong customer service team. For example, by leveraging automatic routing, tedious and often basic Tier 1 issues can be directed to generative AI chatbots so customer agents can manage and focus on more serious Tier 2 and 3 issues that often require a human touch. Not only do these AI-support tools decrease agent burnout and increase productivity, but they have also been shown to improve job satisfaction and staff retention, which is especially vital as businesses traverse the current labor crunch.

We’re also seeing generative AI play a key role in boosting efficiency with tasks such as agent training and getting up to speed on unique customer support cases. Generative AI can also aid in coaching soft skills and language translation, ensuring that each support team member is equipped to provide efficient and consistent quality service regardless of language barriers. 

On top of the proactive layers of support AI brings, AI can synthesize massive amounts of customer data and generate comprehensive case summaries – providing agents with an intelligent overview of customer activity and trends without needing a support rep to create custom reports. In embracing these strategies, businesses elevate the agent experience, preserve their valuable time and resources, and stay agile during economic shifts.

Both predictive and generative AI technologies are currently revolutionizing customer support operations by unlocking valuable insights, enhancing personalization, enabling proactive support, informing decision-making, and optimizing resource allocation.

With these capabilities, businesses can not only protect and grow revenue to gain a competitive edge in the market, but they can also reposition their customer support departments as a critical revenue driver. By unlocking these new growth opportunities, and increasing employee retention while strengthening customer relationships, businesses are preventing escalations and cutting through the backlog to increase customer retention and revenue like never before. 

About SupportLogic

SupportLogic delivers the world’s first support experience (SX) management platform that enables companies to proactively understand and act on the voice of the customer to build healthy relationships and maximize customer lifetime value. SupportLogic SX uses predictive and generative AI to extract and analyze customer sentiment signals from both structured and unstructured data and provides recommendations, content and collaborative workflows. SupportLogic is helping global enterprises like Databricks, Qlik, Nutanix, Rubrik, and Snowflake to prevent customer escalations, reduce churn and elevate the customer support experience. To learn more, visit supportlogic.com.

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Contact:

Matt Maurel
matt.maurel@anthonybarnum.com
225-933-0123