
With all of the buzz about AI in the contact center, it is easy to feel like your contact center is falling behind. However, what you are reading and seeing is not the reality for most contact centers in the US. Innovation has largely outpaced adoption in this field.
One of the major reasons is that the accelerated pace of innovation leaves contact center leaders wondering if making a move today will render them out of date tomorrow. We have created this guide to help alleviate the frustration and confusion that has accompanied innovation in the contact center, while also clarifying what AI is and is NOT capable of doing for your contact center.
Key Areas for AI Integration
Before we dive in, we would like to quickly run down the areas where AI is providing the largest lift for customer experience, efficiency and cost savings in contact centers. This should give you a brief understanding of how companies are utilizing the power, without all of the buzz.
Self-Service
Implementing AI-driven self-service options like intelligent FAQs and interactive voice response (IVR) systems to handle routine inquiries efficiently. This is where most companies start and it provides the largest lift to morale, customer satisfaction, and the bottom line.
QA (Quality Assurance)
AI can automate quality monitoring, providing real-time feedback and analytics to improve agent performance and customer satisfaction. If your QA team is using a manual process then you can help them by implementing AI to handle the x’s and o’s of calls. Their team can be used more effectively for proactive coaching and CX strategy versus playing Monday morning QB.
Chatbots and Virtual Agents
These tools can handle a significant volume of basic customer interactions, freeing up human agents for more complex issues. The majority of first-time calls or contacts can be handled via these channels.
IVR (Interactive Voice Response)
Enhance your IVR system with AI to make it more intuitive and responsive. Traditional IVR solutions are simplistic and require programming, they ask for answers, rinse and repeat. With the added power of AI, logic, trends, agent input into the CRM, and a lot more can factor into the response, reducing customer frustration and call handling times.
WFM (Workforce Management)
Taking all of the staffing and traffic trends into consideration, AI can accurately predict current and future needs based on your historical data and thousands of other data points that could factor into the equation. What once took weeks of manual input is now able to be automated, resulting in efficiency at scale.
Knowledge Management
Knowledge sharing has always been a key component of a successful contact center. With AI you can share information in real time across multiple channels and locations, using this information to suggest the best answer for simple or complex questions, for agents and self-service solutions alike.
Start With Conversational Data In Your Contact Center
Now that we have an understanding of the basics, let’s focus on your contact center. With all of the noise, it is easy to experience paralysis by analysis and be unsure of where to begin.
Let’s keep it simple. Every step in the process of becoming a contact center that embraces AI should be data-driven. It is important to justify the spend and the ROI as well. Without data, it will prove difficult to provide a business case for the technology you need.
The first question to answer is very simple: “Do you have conversational data?” If the answer is yes, then feel free to skip ahead past the conversational analytics section to “Now That You Have The Data”. If the answer is NO, then you have found your starting point.
Conversational Analytics and Data
In a data-driven world, knowing what your customers are talking about is truly half of the equation with AI, automation or outsourcing. Conversation Analytic tools enable you to capture insights from every conversation. When we say every conversation, we mean phone, email, SMS, chat and surveys.
That is the data collection, the analytics allow you to identify trends, common themes, frequently asked questions, customer sentiment, behavior, and much more. You can analyze the data by date, geographic location, number of interactions…. You get the idea.
While agents are great at what they do, they are not perfect at identifying trends because we are human, our memory of what happened sometimes (oftentimes) does not align with what actually happened. Conversational Analytics cuts through the noise and provides valuable insights into your business from the customer’s perspective while also highlighting inefficiencies and opportunities like never before.
Now That You Have The Conversational Data
What is that data telling you? This is where it is important to understand and categorize the data. We suggest the following:
- What Can Be Automated (Self Service, AI, Automation)
- What Can Be Fixed (Training, More Explanation Etc.)
- What Can Be Handled Later (Not A Priority Now)
What Can Be Automated: The data is telling you a story, and you get to choose how it ends for the customer. Below are some symptoms and AI (or automation) fueled cures for those symptoms.
Symptom: Frequently Asked or Repetitive Questions
AI-Enabled ChatBots: Having an intuitive AI ChatBot that learns from within and outside of your organization is a cost-effective way to begin with AI. These solutions vary from simple to more robust.
IVR (Interactive Voice Response): If a significant portion of your call volume derives from questions that could be answered via self service like IVR, then it is time to either implement or upgrade that IVR to one backed by AI.
IVA (Interactive Virtual Agent): Depending on what company you research, this term is fluid in its definition. A virtual agent is more sophisticated than a traditional IVR, although IVRs are blending or evolving into IVAs. At the heart of the technology, it understands sentiment, tone, natural language, and intent, while offering a personalized experience to that user. IVAs can be implemented as a multichannel solution.
Symptom: Low Customer Satisfaction Scores
What are the CSAT scores telling you? Are they unhappy with the product? If that is the case, no amount of AI or agent help can fix that but communication can help people understand your product better. Maybe you need AI to help you understand, through automated surveys, what the customers don’t like about your product.
Other than products, there are a variety of AI tools that can help you identify and remedy those problems. Is it hold times? Queue callbacks or automated callbacks can be offered as part of your IVR. Is it the amount of dead air and the customer not knowing what is going on? Is it AHT (Average Handling Time)?
Having a solution like Level.AI helps you understand and remedy the situations that are causing low CSAT. Dashboards are front and center in real-time for your QA team and can be customized to show data by category, region, division, agent team and so much more. Information is power, and the real power is knowing.
Layered Approach vs Rip and Replace
There are two primary strategies for implementing AI: a layered approach or a complete overhaul (“rip and replace”). While our industry is famous for taking a rip-and-replace approach to platforms, that is not the best approach for AI (or any technology for that matter).
A layered approach is often more practical, allowing for gradual integration and minimal disruption. Implementing one solution such as conversational analytics is a good first step, followed by layering in knowledge management or agent-assist AI solutions based on the data.
How InflowCX Can Help
Being a company that has one goal in mind, to help our customers deliver the ultimate customer experience in the contact center, we do not have one solution or partnership that we push. Our process starts with your company, your objectives, your goals and then work with you to find the best possible outcome.
Integrating AI into your contact center doesn’t have to be overwhelming. By understanding where to start, leveraging your data effectively, and choosing the right AI solutions, you can significantly enhance your customer service operations. Remember, the journey towards AI integration is a progressive one, with each step building upon the last to create a more efficient, responsive, and intelligent contact center.