As emerging technologies backed by artificial intelligence (AI) make headway, the pressure is on for companies to start implementing AI into daily operations to optimize the customer experience (CX). Amidst the buzz related to emerging AI technologies like ChatGPT, some have made bold claims that solutions like these have the potential to eliminate human workers across industries, including within the contact center. But the reality is that AI alone won’t solve for all CX use cases. To achieve success, organizations need to understand where human intelligence and AI can each have the greatest impact.
AI’s best use case in the contact center is for automating tedious, repetitive tasks
Some companies are investing in flashy AI solutions that aim to interpret conversations for agents while they’re mid-conversation, but given that most agents can understand customer sentiment and pain points on their own, these types of technologies tend to be more disruptive than informative. Instead, where AI can really make a difference is in automating manual, time-consuming tasks.
For example, agents typically are responsible for case management tasks, such as summarizing the purpose of the conversation, specific actions the agent took, the overall resolution of the contact and whether or not the customer was satisfied after every single interaction. AI could take care of these post-contact summaries, saving agents precious seconds or minutes per interaction. This would not only create extra time for agents to spend handling more complex work, but could also potentially minimize some of the human errors that can inevitably take place in manual reporting and analysis processes.
AI tools could also automate any next steps following the call, such as creating a ticket with support if a particular troubleshooting activity needs to take place. Another area where AI shines is in fielding basic requests that don’t need human intervention, such as handling password resets. This could help cut back on contact center requests, allowing agents more time to handle more complicated customer inquiries.
Human intelligence can greatly impact areas that require fostering customer trust, demonstrating empathy and interpreting data and trends
Contact center agents are adept at handling difficult conversations with care, adapting the conversation and their tone based on the needs of the individual — something AI is not yet capable of.
In addition, there are always going to be people who will not fully trust AI and may feel uncomfortable disclosing personal information to AI for certain topics. When it comes to discussing sensitive details, customers will likely prefer speaking with a real person. Research from the Medallia Institute finds that being able to communicate with a human (instead of a bot) is the #1 factor consumers care about when choosing which customer support channel to use.
As it stands now, AI isn’t quite yet at the level where it can always interpret results. The models that are currently in place may not have enough context to understand the global state of the economy or shifts in a company’s goals and corporate focus. We saw this play out as AI-powered systems took time to adapt to how the world changed at the start of the pandemic. That’s why there will always be a need for putting people in charge of these systems, as they will be responsible for updating the models to keep up with these kinds of shifts.
Using AI and digital tools to optimize CX across the entire contact center journey
AI technologies can enable organizations to make the pre-interaction experience more intelligent, which can prevent some outreach to the contact center altogether. They’re also useful in empowering human agents to streamline interactions when customers do need to reach out. For example:
#1: AI-backed text and speech analytics can be used to analyze post interactions at scale to determine the most common reasons customers are reaching out to the contact center in the first place and streamline the pre-interaction experience.
AI-powered speech analytics can instantly transcribe voice conversations and both text and speech analytics can be used to analyze the open-ended text of contact center interactions to uncover the customer’s intent and sentiment when reaching out. These insights can be used to improve website FAQs and self-service tools as well as contact center agent training and scripts, benefiting customer experience overall across the entire enterprise. In turn, implementing these enhancements can decrease the volume of outreach that the contact center receives, ultimately lowering the cost to serve.
#2: Experience orchestration technology helps brands understand why customers are reaching out to dynamically optimize the contact center journey.
As contact centers work to capture insights from every customer interaction with a brand, experience orchestration technology can be used to create dynamic, customer profiles and update them in real-time to containing a user’s preferred method of contact and interaction history and identify moments of friction when customers may need support.
By understanding an individual’s history with a brand, companies can predict customer problems, serve up relevant content and customer support when necessary, and reduce the burden on the contact center. For instance, a Telecom provider could preemptively surface an iPhone chat support session for a web customer whose preferred method of contact is live chat when they’re logged into their account and actively searching for iPhone products.
Experience orchestration technology can also be used to provide recommendations to agents that may solve a customer’s issue based on what the company knows about their history with the brand, whether that’s sharing a knowledge base article or product upsell.
#3: Digital experience analytics help businesses understand what challenges customers are experiencing via digital channels and intervene with support in the moment.
Digital experience tools can be used to monitor individual customer behavior when interacting with a given company’s websites, apps, and forms — to pinpoint moments of frustration, evaluate overall sentiment, and pinpoint when users may be encountering technical issues or not finding what they’re looking for so brands can intervene before any problem escalates.
#4: Smart callback technology can be deployed to avoid long hold times and to allow for more strategic contact center staffing.
Imagine a bank’s digital experience analytics indicates that a customer is experiencing difficulties when trying to open a savings account, if that individual’s preferred method of contact is speaking with an agent over the phone, smart callback technology can be used to display a web prompt that verifies whether the person needs support and guides that user through reserving a time to receive a call from an agent at time that works best for their schedule. This prevents the customer from having to wait on hold and enables the brand to assign the right agent with the right skill sets to handle the call, ensuring a better overall experience.
Ensuring success with AI adoption
Leaders don’t want to fall behind when it comes to adopting the latest technologies, but it’s critical not to rush forward without first validating that a given tool can support the company’s key business objectives. With all the hype about ChatGPT and competing tools from Google and Microsoft, one area of caution is that these open-source generative AI technologies do not adhere to strict security standards and should not be used to analyze sensitive customer data.
Building a change management strategy is a must when introducing any new technology within the contact center. Leaders need to carefully consider whether adopting a given solution affects CX metrics, such as customer satisfaction and first contact resolution, which shape how agents and supervisors are evaluated, compensated, and promoted.
Ultimately, AI tools are most effective when they’re accurate, easy to understand and use, available in the languages employees and customers use to communicate, and scalable and accessible across the entire organization.
Final Thoughts
The contact center is typically considered a cost center, and given the global state of the economy, executives are laser focused on finding ways to reduce spending where possible. The right AI tools can help drive savings and even profitable revenue growth, but without careful vetting organizations could end up investing in solutions that don’t serve a real business need. That’s why gathering requirements and doing due diligence up front are crucial to long-term success.
