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Artificial Intelligence (AI) is rapidly transforming call and contact center operations, making them more efficient and cost-effective and helping to reduce work-related stress for human agents. Cloud-based technologies enabled the expansion of AI for contact centers, and the need to support customers effectively during the COVID-19 pandemic prompted many businesses to speed up the adoption of these solutions. By 2021, more than half of call centers had already developed an AI strategy.
If you need to make a case for your business to transform its traditional call center into a future-forward, AI-powered operation, this blog can help to support your efforts. It includes several examples of how leading companies in various industries are using AI in contact centers. It also highlights the results they’re seeing from these investments. But before we get to those stories, let’s look at why AI is important in delivering a modern customer service experience — and what types of contact AI solutions are commonly used today.
AI has long been viewed as a technology destined to streamline and enhance call center operations. The technology’s ability to recognize speech, learn from that speech, and interact effectively with customers is invaluable for a contact center, of course. Plus, by using AI to automate routine processes, such as call scoring, call center operators can ease workloads and take pressure off of human agents, freeing them to focus on higher-value and more fulfilling work.
That’s a lot, but AI can do even more. For example, the technology can help supplement the efforts of live agents by making appointments for callers or recording bill payments, effectively providing a self-service option for callers.
Machine learning can be applied in various ways in contact center environments, including automating processes, analyzing data, and improving key functions, especially in call centers focused on providing customer service. Examples of artificial intelligence in customer service include automated call scoring for quality assurance, which we will explore in more detail in the next section.
Here’s an overview of some contact center AI solutions that could benefit your business:
By using AI and automation to get an objective view of 100% of calls into the call center, companies can automate quality assurance or QA, and efficiently evaluate every call for quality and compliance. That, in turn, leaves more time for call center operators to solve call-handling problems and spend less time looking for performance and QA issues.
Interactive voice response (IVR) tools assist callers around the clock. Conversational IVRs interact with callers in a natural, human-like way by allowing them to respond via voice instead of keypresses. IVR systems like Invoca’s can be set up quickly (i.e., in minutes), without any coding or help from IT. And because IVRs from Invoca work with every phone system, they can be deployed immediately without any worry about business disruption.
Automation enables rapid scans of data, providing contact centers with insights such as hold and call times, and a wealth of information on customers — from buying personality and sentiment analysis to intent. Through machine learning, AI can go further and provide predictive analytics to benefit marketing as well as customer service teams.
Another benefit of using AI solutions in the contact center is gaining access to intelligent call routing. While it is not AI-powered itself, many leading AI platforms for call centers, including Invoca, offer intelligent routing as a companion feature that complements AI capabilities.
Using intelligent routing in a call center greatly reduces hold times by efficiently directing customers where they need to go — including across multiple call centers and branches if needed. It works by using data about the caller’s digital journey, such as the webpages they visited, to route them according to their intent. Agents are also presented automatically with pertinent information about callers and their intent. That helps to drive higher agent productivity and a better overall customer experience.
Chatbots, or virtual agents, are AI call center agents that can simulate conversations with live users via text chat programs on websites. They’re doing good work, too: According to a recent survey by Microsoft, nearly 90% of customers reported that chatbots were effective in resolving their issues.
Chatbot technology is advancing fast. OpenAI’s development of ChatGPT-3 has opened the door for businesses to easily provide self-service options to their customers, which can dramatically reduce hold and resolution times in customer service. And OpenAI recently released a new language model, GTP-3, which has the capacity to produce far more realistic text than prior models.
Automating routine tasks, using natural language processing (NLP) to understand human speech, and generating human-like responses virtually via text or voice are primarily what drive the main benefits of call center AI. Call center managers can create a response ecosystem encompassing live agents and virtual agents to streamline workflow, speed up routine tasks, and allow live agents to focus on complex and more serious customer issues.
In addition, AI’s ability to generate, gather, and analyze tremendous amounts of data further boosts call center efficiency by providing valuable insights into the customer, such as sentiment analysis. It can also help deliver relevant and targeted training material to live agents to help them raise the bar on their performance.
Now, let’s look at seven examples of AI in the contact center. These case studies illustrate some of the key benefits of using artificial intelligence in the call center environment. These examples feature major companies operating in the healthcare, financial services, and consumer sectors.
MoneySolver, a financial services company, provides customized student loan, tax, business, and credit solutions. Before deploying Invoca’s AI-driven platform, MoneySolver tracked only a small percentage of calls into its call center where over 100 agents handle customer inquiries.
Invoca’s platform now provides automated QA based on 100% of calls and provides instant feedback to agents. This has led to a doubling of the close rate at the contact center. Invoca’s Google Ads integration has also helped MoneySolver’s marketing team to track call attribution more efficiently, allowing for better optimization of ads and a 30% increase in return on ad spend (ROAS).
National window replacement franchise Renewal by Andersen gets its most valuable sales conversions over the phone and uses a pay-per-call fee model to send leads to its 90 franchise affiliates. However, the firm lacked an effective way to measure and qualify leads or confirm it was billing the correct fees. Additionally, Renewal’s contact center QA was based on just 2% of phone calls graded manually — a time-consuming system that was prone to error.
Invoca’s AI-driven platform changed all that. Not only did Renewal by Andersen fully automate quality assurance in the contact center, tracking 100% of calls, but it was able to validate every phone lead and bill each affiliate correctly. The result was a decreased cost per acquisition (CPA) and increased return on ad spend for the marketing team. Meanwhile, the contact center team saw a 47% increase in customer appointments made, and a 129% increase in agents correctly assessing callers’ needs.
Windstream Holdings, based in Little Rock, Ark., set its sales team a goal of 40,000 new subscribers for its premium broadband and communication services in a pandemic-disrupted economy. However, management knew they needed to better integrate sales and marketing first to achieve that goal.
Using Invoca’s AI-driven platform with its automated call recording and conversation intelligence, leadership was able to achieve marketing efficacy by accurately tying ad campaigns to actual phone sales, which represented 60% of their business. Prior to deploying Invoca, attributing ads or campaigns to phone sales was guesswork. Using Invoca helped Windstream reduce CPA by 17% and achieve 150% of its subscriber goal in 10 months.
CHRISTUS Health Plan, an international faith-based, not-for-profit headquartered in Irving, Texas, deployed Invoca’s platform to automate QA in its call center and better train its call center agents. Support specialists now spend 50% less time scoring phone conversations, making sure that agents use the proper greeting and other script prompts.
Using Invoca to record and transcribe every call made into the call center also provides CHRISTUS Health Plan’s call center leadership with invaluable, real-life teachable moments that they use to train agents and help drive continuous improvement in the customer experience.
With over 300 locations, AutoNation is America’s largest and most admired auto retailer. AutoNation uses Invoca to train its sales team to close more deals and better serve customers. Invoca automatically records and transcribes each inbound call, and AutoNation uses these insights to identify sales agents’ weaknesses and coach them to improve their performance.
AutoNation has also started using Invoca to automate customer call quality assurance (QA). With Invoca automated call QA, AutoNation can select the criteria that make up a successful phone conversation for both sales and customer care agents and use AI to automatically scan every call for those criteria, at scale. These criteria include if the agent is greeting a caller correctly, asking them to set an appointment, mentioning a recent promotion, and more. This eliminates the manual work of scoring calls and removes human error from the process. It also gives agents real-time feedback on their performance so they can adjust on the fly, without having to wait for their next meeting with their manager.
Rick’s Custom Fencing & Decking is one of the largest retailers of fencing and decking in the Pacific Northwest. Rick’s Custom Fencing & Decking has five retail locations where sales agents take calls and schedule appointments. Before using Invoca, the team didn’t have a formalized call QA process in place. Sales managers would occasionally listen to calls and give ad hoc coaching. Coaching based on such a small sample of calls was prone to human error and didn’t give a full picture of agent performance.
Now, with Invoca conversation analytics, the sales managers use AI to automatically QA 100% of inbound calls based on their criteria. The company doesn’t use scripts and instead empowers its sales team to have free-flowing conversations with customers — but there are a few topics that agents need to cover on every call. For example, they need to state the name of the business clearly, mention any upcoming promotions, and ask a list of questions to qualify the lead. If the lead is qualified, they need to ask them to schedule an appointment. Invoca’s AI identifies these moments in each conversation and grades the agents accordingly. With Invoca’s help, the company’s agents achieved a 23% improvement in call etiquette pass rate and were 6x more likely to use scripted phrases.
These are just a few contact center AI use cases illustrating how artificial intelligence is transforming contact center operations. Automation is also driving greater efficiency in customer interactions while helping to preserve the human touch. Customers can get fast answers to easy inquiries, or they connect quickly with a live agent if they prefer. And automation supports agents by giving them more information about customers’ needs so they can address them more effectively and deliver the personalized experiences today’s customers expect.
As NLP and machine learning continue to evolve rapidly, AI for contact centers will become even more widespread — and necessary for competitive advantage. Invoca’s platform is already delivering valuable AI solutions in call center operations using conversation intelligence. Businesses use our solution to modernize their call center operations and gain customer insights from calls that are otherwise challenging to track. And with Invoca’s automated QA features, including immediate, automated call scoring, call center managers can monitor QA much more efficiently and make sure agents keep customer conversations on the right track.
For more real-world examples of AI in the contact center, visit our Customers page.
