CCAI: AI & The Future of Contact Centers
Nirmala
Aug 23, 2023
AI can supercharge your business more than you could have imagined. According to Accenture, 84% of CXOs understand the value of AI for their businesses. They feel that a strategic plan to deploy AI in any business operation can generate up to 3x times more value compared to non-AI-led operations.
Today, with AI at the core of their contact center, businesses can automate, analyze, and improve communications across departments. It can be simpler for these businesses to build exceptional customer experiences in a scalable, efficient manner.
Decision-makers in many direct-to-customer (D2C) companies are in hot pursuit of contact center applications that would give them an inevitable edge over their competitors. According to Gartner*, organizations focusing on AI and related technologies such as natural language processing and understanding, RPA, and no-code analytics would play a decisive role in taking conversational AI for contact centers to new heights in the next 2 years.
In this article, we will explore:
- 1. How can AI-driven contact centers transform customer experience?
- 2. What is Contact Center AI: A Definition
- 3. How is AI used in Contact Centers?
- 4. Enabling rich and conversational experiences with CCAI
- 5. Examples of AI-based Contact Center Operations
- 6. Challenges surrounding AI in Contact Centers
- 7. Future of contact centers & AI
How can AI-driven contact centers transform customer experience?
Your contact center is at the core of your customer communications. Contact centers streamline and augment customer communications across marketing, sales, customer service, and operations. In doing so, they relay critical information as well as capture data across the customer journey.
With the number of customer conversations across voice and digital channels exploding, AI will be essential not only to automate conversations but also to analyze the data within these conversations effectively.
Business leaders see AI and machine learning capabilities such as conversational AI, text analytics, and automated call routing with virtual assistants as the pillars of their call center operations.
This article will highlight how contact center organizations could digitally transform their operations with AI and improve effectiveness by creating a tech-centric agile ecosystem for its human agents.
What is Contact Center AI: A Definition
Contact center AI is the advanced application of AI-related technologies specifically designed to automate contact center operations and analyze contact center data. The ultimate goal of using contact center AI is to improve customer experience with targeted communication, hyper-personalization, faster resolutions, and lower wait times.
By leveraging AI, you can build a purpose-led workflow of communications, insights, and predictive intelligence that syncs with your immediate customer experience (CX) management goals.
Based on their AI applications and industry use cases, contact center AI solutions could be defined as:
“Integrating AI-based capabilities to garner insights and automate conversations to improve how a virtual agent, a human agent, or both work together to deliver a seamless and consistent CX with the flexibility to scale support and service anytime, anywhere.”
Customer-facing AI
Today, AI can automate most repetitive tasks within a contact center. AI-based bots or virtual agents can become the first point of contact as customers browse websites, wait for deliveries, onboard a new service, or ask for customer service via WhatsApp, messages, chats, or phone calls.
Agent-facing AI
Virtual assistants (also known as Agent Assist) within the contact center will continually analyze agent conversations presenting them with relevant nudges to improve the conversation, access relevant customer or product-related data, or leverage upsell and cross-sell opportunities.
Supervisor-facing AI
Businesses can use AI-based real-time and historical Speech Analytics to help their call centers to pinpoint agent training requirements, reduce escalations, and increase first-call resolutions. Real-time speech analytics makes it possible to proactively alert supervisors about dips in customer sentiment.
Management-facing AI
Predictive decision-making based on trend analytics alleviates trust deficit and other negative sentiments. Today, conversational analytics makes it possible to automate quality assurance and deliver deep granular insights into the root cause of customer dissatisfaction.
AI-powered contact centers offer innovative solutions for three major stakeholders within the contact center:
- The customer.
- Agents.
- Contact center manager/Supervisor.
How is AI used in Contact Centers?
Conversational AI-based contact centers could spend up to $2 billion by the end of 2022 to make their digital touchpoints with customers more effective and engaging. By 2026, 10 digital touchpoints could be fully automated with chatbots and IVAs to curtail workforce costs. Based on these projections, we can categorize AI applications for contact centers into two types:
Transactional uses
Transactional applications involve the automatic triggering of omnichannel conversations with the customer using AI-based call routing functionalities. These involve the synergistic integration of an automatic call dialer, call distributor, omnichannel router, virtual agents, and an interactive voice response agent.
Leveraging advanced contact center AI applications for predictive call routing allows you to connect your customer to your best-performing service agents without disrupting CX.
Transformational uses
You can now transform how your Marketing, Sales, and Support departments are trained to simultaneously handle cross-functional queries from a wide range of customers. This requires a unified AI integration with CRM, Customer Data platforms (CDPs), business analytics, and sales pipelines to ensure your customers never fall off your radar due to poor CX or delayed responses.
Transformational uses also include how the Head of Departments can optimize their workforce and unlock the potential of each service agent with superior call recording facilities.
In addition to the obvious benefit of delivering exceptional customer experience at each stage of their digital journey, organizations can save significantly on workforce costs. According to Gartner, Conversational AI contact centers can reduce call center costs by $80 billion in the next three to four years.
In aninterview, Chaitanya Chokkareddy, chief product officer, Ozonetel explained the finer nuances of AI-based omnichannel solutions for enterprises looking to transform their call center operations.
Additional uses of contact center platforms include:
- Workforce retention.
- Service quality management.
- HR-driven call center employee performance management (EPM), and much more.
Other significant benefits of using contact center applications with AI capabilities are:
- Blended call center functions with advanced integrations to BPS, Sales dialing hubs, and CX management tools;
- Effective handling of millions of calls per day, week, and month with consistent communication and feedback management;
- Better call management with live notifications and alerts and scheduled callbacks;
- Develop seamless alignment between the Sales, Marketing, Service, and Support teams;
- Faster and automated resolution of queries that are raised at multiple platforms such as emails, web, social media, chats, or dial-in calls;
- Create holistic communication workflows for your asynchronous teams spanning cross-functional teams;
- Proper workforce management through automated routing to agents that are currently available.
Enabling rich and conversational experiences with CCAI
Contact center AI platforms do more than just reply to customer queries. Virtual agents listen and help you foster great relationships with customers by identifying pain points and how to mitigate them quickly. To do all these, you would need more than just foundational AI. You require the power of integration with Customer data analytics, maps, and deep learning.
Let’s elaborate on this a little.
Contact center automation powered by AI and NLP capabilities has opened new avenues for every other major business function. These are used for AI-enhanced product development, recommendation engines, and service quality management.
According to McKinsey*, organizations that could reap bottom-line benefits from their AI adoption are better placed to adopt and advance with other AI technologies, such as MLOps, deep learning, and data governance. When seen through the lenses of democratized AI and open data ecosystems, all these could play a major role in deciding which way and how fast your contact center operations could progress in the next 5 years.
Build an AI-centric communication channel
AI-enriched conversations replace humans from the system, not their ability to emote and understand sentiments.
Get live insights on each call
Why did the customer give your call center agent a bad rating?
Does your agent truly understand the importance of listening and answering as per guidelines?
Is your contact service agency equipped to handle multiple queries of the same type?
What is the best way to contact a disgruntled customer — email, chatbox, a telecall, or WhatsApp call?
Getting a bird’s eye view of answers to these questions can make your contact center more efficient in handling large volumes of calls. AI enriches each conversation and delivers powerful insights through data visualization and reporting analytics for every call and every agent.
Enhance loyalty
Customers prefer automation or chatbot as long as this conversation is set up thoughtfully. Solving one problem at a time for the customer is the best way to stir a feeling of loyalty and sustain a healthy holistic relationship.
Increase productivity and agent performance
AI-powered call routing achieves higher service ticket closures in a shorter turn-around time (TAT). It also reduces fatigue among human agents and managers who might have to do a lot of mundane telecalling and take duplicate service queries from the same customers without AI-powered contact center automation software.
Work 24/7/365
In the era of remote working, give your agents and managers the benefit of working from any place by tapping into virtual agents and agent assistance linked to robot-based answering machines that deliver high-grade conversational self-service round-the-clock throughout the year.
If you aspire to become a call center that never sleeps, you could opt for an AI-supported conversational AI platform like Ozonetel today!
Examples of AI-based Contact Center Operations
We have garnered insights from multiple sources and our in-house case-study repository to highlight the multiple facets of contact center AI and its impact on customer experience management.
AI-based self-service and automation.
The ability to track past conversations and analyze keywords used in chats and calls can turn your contact center into a self-service hub. Address common queries with ice-breakers and probing questions using intelligent voice agents that offer far more effective solutions promptly.
These are used in hotel reservation bookings, e-commerce delivery tracking, logistics supports, flight ticket booking status, and loan approval systems.
Pin to cutting-edge big data analytics and customer data management.
Turn every conversation into a goldmine of insights that help you forecast future customer behavior. AI is highly suited to uncover hidden patterns in behavior and sentiments, which enable contact center AI tools to make accurate predictions about customer needs.
Increase CLTV
Brands use AI-based CCAI to increase the customer lifetime value or CLTV. Create personalized shopping experiences for your customers by providing them with relevant options to ask questions as they screen past recommendations, product reviews, and comments. AI’s conversational capability keeps your customer glued to the brand and helps win their trust with improved out-of-box sales and service strategies.
Digital engagement with feedback management.
Is your customer happy or sad with your response? Did your agent solve every query raised during customer interactions? How long did the call go?
Gain real-time analytics on these and much more with CCAI software to break away from the traditional framework of telecalling activities. With AI and machine learning-based automation, you can embrace the power of digital engagement with actionable feedback from your valuable customers. Never lose a customer again due to poor follow-up or a lost sales opportunity due to the lack of insights on feedback and digital conversations.
Challenges surrounding AI in Contact Centers
AI’s success in contact centers is dependent on many factors. We can define them as part of the DAT approach: DATA, AUDIT, and TECHNICAL COMPLEXITIES.
AI models require enriched data to perform as per requirement. Conversational A models, in particular, ingest a tremendous volume of data from NLP, Voice, text, speech analytics, and image recognition tools to deliver contextual results. Additionally, these models must be constantly fed with newer data that must be covered as part of the latest data audit, data governance, and compliance frameworks. 4 All these lead to the third challenge of technical complexity that impacts the speed at which contact center AI solutions are maturing. This makes the vendor options limited and complex. AI agents could be priced out anywhere between USD1000 and USD 5000 depending on the volume of tasks they handle and the ROI expected to be generated.
So, making a mistake in choosing contact center AI for your organization can severely dent your annual enterprise tech budget.
By 2026, AI will replace a part of the workforce currently engaged in contact center operations via automation and MLops. But, it does not mean that AI and human agents can’t work together. Contact center leaders and human agents trained to handle AI tools would enhance the scope of their digital transformation, particularly in the service operations field.
Retaining the human element in AI innovations across contact center operations is key to customer service models in the modern era. Brands that can provide empathy alongside good customer experience are likely to emerge as winners in the industry where AI has penetrated deep and far.
Futures of contact & AI
The future belongs to Embedded AI-powered conversations in contact center organizations.
AI, automation, and big data analytics will continue transforming contact center operations. Harnessing these technologies would be the central idea of any digital transformation at contact centers. We foresee more intelligent efforts in understanding these technologies would be taken to learn how each would evolve more systematically, allowing agents and managers to get on top of their CCAI operations.
With a more focused partner-vendor approach, decision-makers at the contact center organizations can successfully transform their existing workflows with AI at the core of every operations.
Ozonetel: Contact Center AI Solutions
At Ozonetel, AI is at the core of our contact center offering. Our AI-based omnichannel contact center solutions is an end-to-end solution that helps you build personalized communications at every step of the customer journey. Learn more
References:
1) AI: Built to Scale, by Accenture
2) Gartner’s Forecast-https://www.gartner.com/en/newsroom/press-releases/2022-08-31-gartner-predicts-conversational-ai-will-reduce-contac 3) The State of AI in 2023, by McKinsey
4) Hitachi Vantara’s Intelligent Data Governance For Dummies-https://www.hitachivantara.com/en-us/pdf/ebook/data-governance-for-dummies.pdfAfds
