Love it or hate it, artificial intelligence (AI) is having a major moment right now, and emerging technologies like Generative AI are taking the customer service world by storm. But to avoid getting caught up in the hype, CX leaders should take an outcome-led approach to implementing contact center automation and AI systems.
The truth is AI is accelerating faster than most organizations can adapt. While the benefits of these technologies are undeniable, CX professionals report less confidence in their own understanding of AI. According to a report from Talkdesk, the number of organizations classifying their usage of AI as “advanced” fell to
35% last year. And while the overall adoption of AI-powered automation has gone mainstream, only 54% of projects on average are successfully implemented at scale.
Commonly cited hurdles include everything from knowledge gaps to organizational inertia and an inability to define a strategic and quantifiable vision. It’s no wonder then, with so many terms and technologies to navigate, why making sense of this space has become increasingly difficult.
In our blog, we explore the nuances between automation and AI, how the two can work together to orchestrate a better experience, and top tips for increasing the success rate of your next pilot.
What Is Contact Center Automation? And How Is it Different than AI?
Both automation and AI can streamline workflows, gain efficiencies, and improve experiences, but they operate in different ways. Whereas automation works with data to perform manual and repetitive tasks, AI understands and interprets data to enhance and augment human capabilities. Put another way, one follows a predefined set of rules to improve the speed and accuracy of a process, and the other learns and adapts to ensure the process delivers the right outcome.
Together AI and automation can transform traditional service delivery models, using data to enhance both the employee and customer experience. And while it’s important to understand the various flavors of AI and automation, CX leaders would be wise to spend more time focusing on the “why” and “how” before skipping ahead to the “what”.
Leveraging Automation & AI to Orchestrate a Better Customer Experience
So how can CX leaders unlock the true potential of these technologies? Well to start, it’s important to select high-value use cases and understand how these tools can be used together to achieve the desired result.
Instead of beginning your journey with questions like, “Which AI product should I purchase?”, or “What can I do with Generative AI?”, ask your team “Do we know what the ideal experience looks like for our customers?”. Simply put, before you vet products, define where you’re going and what gaps need to be addressed to get there.
After all, the biggest return on investment (ROI) will come from leveraging variations of AI and automation together to unlock more value for the customer.
Imagine the following scenario:
A telecommunications company identifies the need to reimagine their service scheduling process to improve its Net Promoter Score (NPS), increase customer retention, and address an upward trend of negative consumer sentiment online.
After mapping out the current state and key friction points, the company designs its ideal experience to improve its time to resolution and shorten the appointment window for service visits to one hour. The following high-value use cases are then identified:
An AI-powered chatbot to improve self-service and prevent unnecessary dispatches.
RPA to streamline the scheduling process: prepopulating the customer’s information, service history, and auto-scheduling courtesy calls and SMS reminders.
An AI platform to combine all scheduling criteria, travel times, level of urgency, and workload distribution to quickly create routes and suggest optimal service windows for each customer.
Sentiment analysis to assess the level of urgency and frustration of the customer, prompting proactive communications from the agent and/or field technician.
The future state experience detailed above can’t be achieved by a single technology. Instead, it requires a combination of AI and automation to ingest the customer’s data, streamline and automate the scheduling process, and enhance the overall service delivery through personalized, proactive support.
6 Key Capabilities & Use Cases for Customer Care Teams:
Here are a few examples of how AI and automation can be deployed today to improve satisfaction, optimize costs, and scale high-touch, high-quality support. Whether your contact center schedules appointments, offers technical support, or processes insurance claims, any customer care team can benefit from the following applications.
1. Chatbots and virtual assistants
While we’ve all experienced a chatbot failure in the past, large language models are now capable of deploying more effective and conversational “virtual workers.” These intelligent assistants can handle common questions, from billing inquiries to product information, freeing up an agent’s time to focus on more complex issues.
2. Speech recognition and natural language processing
Other capabilities, such as speech-to-text and natural language processing, can analyze 100% of a customer’s interactions in real-time across calls, chats, and text-based communications to gain valuable insights into customer preferences, regulatory adherence, and overall sentiment.
3. Sentiment analysis
Sentiment analysis is another variation of AI that allows service teams to gauge customer emotions and satisfaction levels. By analyzing surveys,
social media interactions, and support tickets, the system can identify both positive and negative sentiments. Armed with this information, agents can prioritize and resolve critical issues promptly, leading to a higher degree of customer advocacy and retention. 4. Predictive analytics
AI can also be used to analyze large volumes of customer data and predict behaviors and outcomes. By analyzing historical data, customer patterns, and preferences, predictive analytics can provide personalized recommendations, proactively address potential issues, and even forecast customer churn.
5. Automated workflows
Automated workflows, facilitated by tools like robotic process automation, enhance the contact center’s efficiency by reducing errors and streamlining functions like call routing, ticket assignments, data entry, and order processing. When implemented correctly, the benefits include increased productivity and cost optimization.
6. Intelligent agent augmentation
While often referred to as “agent assist”, intelligent augmentation encompasses an array of capabilities to deliver timely guidance, information, and support to the employee. Context from the customer conversation prompts the technology to surface information across multiple systems (e.g., the knowledge base, CRM, or self-service systems), enable easy access to knowledge articles, and provide contextual details like the customer’s order history or recent transactions.
3 Tips for Implementing AI & Contact Center Automation:
Understanding the top use cases is important, but as we’ve discussed, orchestrating these capabilities to impact an end-to-end process or customer journey will separate the winners from the losers in the AI arms race. To come out on top, CX leaders will need to take a phased approach. Launching multiple technologies all at once isn’t feasible. That’s why operating in sprints and short bursts, learning as you go, and continuously course-correcting is key.
To launch an effective AI implementation strategy, here is some tried and true wisdom from VXI’s domain experts:
Tip 1: Start with your “why”
Artificial intelligence and automation can fix many of the problems CX leaders and operators face today. But the hard truth is that it can also be a huge time suck and waste of money if there is no clear objective or correlation back to the customer or employee experience. The list of AI applications and possibilities is endless, so use journey mapping and design thinking to keep your team focused on the right things. Here are a few other
crucial considerations to review before implementing your next pilot. Tip 2: Don’t use new technology to fix old problems
The convergence of Generative AI and Conversational AI has changed the game. Cost-cutting and task-based handle time reductions won’t delight the customer or justify a bigger budget. CX leaders can be more aspirational, shifting the business case and operating model to deploy AI-powered solutions designed around
customer lifetime value (retention, referrals, and revenue). Prioritize a better experience, and efficiency will follow. Tip 3: Involve your agents in the process
Finally, make sure to empower your agents by providing proper training and upskilling opportunities on AI-driven tools and technologies. This will boost their confidence in using new solutions effectively and improve their overall performance. By incorporating their input and addressing their concerns, you can create a more supportive and collaborative work environment, fostering greater acceptance of AI implementation.
Speak with our domain experts to accelerate AI adoption within your contact center
At VXI we are passionate about helping our partners rethink, reimagine, and revive traditional customer engagement models. It’s why we offer a team of Xperience Engineers who specialize in everything from experience design to digital transformation and program management within the contact center. Our practice leaders are pioneers of the experience economy and have helped leading Fortune 500 brands leverage CX as a competitive advantage and opportunity for ongoing value creation.
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