conversational AI

4 Use Cases for Conversational AI in Contact Centers

Conversational AI can be applied to your contact center in countless ways: here are four use cases that will get you thinking.

It should be a high priority in your organization to focus on improving the customer experience. That's one of the crucial ingredients in promoting customer retention and developing a higher level of return business. And satisfied customers are your ticket to more referrals and expanding your brand in the marketplace.

To promote a better environment for customer service, you want to take advantage of the latest in technology and software solutions. This can help you keep the lines of communication open (ideally 24/7/365) and provide much more comprehensive support for your team. With conversational AI, you can achieve this and maintain your competitive edge.

Experts anticipate that using conversational AI in contact centers to support human agents will cut down labor costs to the tune of $80 billion, according to a report from Gartner. It's projected that in 2022, the estimated spending on conversational AI will rise to $1.99 billion. 

If you are preparing to budget for conversational AI and are looking for more information on deploying it in your organization, here are four use cases for conversational AI in contact centers to consider:

1. Conduct Customer Calls

Between rising labor costs and difficulties sourcing a sufficiently large team from the currently available labor pool, the push to rely on virtual agents to support your human team grows. But, with a virtual AI assistant in your company's contact center, you can conduct a much higher volume of customer calls. Gartner predicts that 10% of interactions with call center agents should be automated by 2026 - a dramatic leap from the current 1.6% of interactions covered by conversational AI.

Customers can direct their calls to a conversational AI agent just as naturally as when speaking to an ordinary human. The solution will respond intuitively, answering customer inquiries accurately. That's a much easier scenario than getting new hires up to speed and hoping they're detail-oriented and avoid common errors.

Moreover, with access to your company's database, your virtual AI assistant can provide accurate information and resources much more quickly and without the tedium of forcing people to look up the same types of information over and over every day.

2. Automate Tedious Tasks

A workforce is happier when they do not have to spend much of their day doing repetitive activities, especially when aware that machines and software can take over many of the tedious tasks they currently have on their plate.

Indeed, automating the most tedious tasks to free up people to do more complex and nuanced work should be at the heart of your call center. Consider the following routine tasks that your virtual AI assistants could handle so much more efficiently:

  • Reset passwords
  • Update customer files
  • Track orders
  • Check the status of back-ordered items
  • Provide a history of purchases or charges

These and many other rote tasks are easy to delegate to your conversational AI solution.

The result is a fast, accurate and efficient system to serve more customers when they need service at any time of the day or night. For example, if you're spending more on payroll to keep the call center open during a holiday, your conversational AI agents can pick up much of the slack, helping to improve your budget and bottom line.

With fast, accurate, and efficient customer interactions, conversational AI saves human agents time that they can use to better use, such as addressing unique or quite challenging customer inquiries.



3. Support Your Workforce and Scale Their Capacity

Conversational AI can also help human agents by supporting them in customer interactions. For example, the conversational AI agent can easily transfer customers to a human agent if needed. Should this occur, it can communicate relevant information such as previous interactions, order history, customer, files, and other material to your human agent.

As noted by Destination CRM, virtual AI assistants are well-suited for incoming and outgoing calls. "For example, provide sales teams with the right time to reach out to a particular lead based on a wide array of variables," including a history of previous interactions presented in the context of other leads with similar industry characteristics.

Automating more of the customer experience can remove much of the friction customers experience when trying to get quick answers to questions. By fully automating customer interactions, or "call containments," you stand to save more money per call. Automatically pulling up the customer's name, phone number, and the reason for calling in today will save enormous amounts of time for the human staff.

Conversational AI agents, therefore, allow human agents to work faster, more accurately, and more efficiently. If your company has been having difficulty recruiting new workers for your call center, or if there have been challenges in retaining these employees, conversational AI to support current workers could be the solution you've been looking for.

The bottom line is that virtual AI assistants can better satisfy customers and work faster to address even more customers as call volumes increase and outbound communications ramp up as you follow up on previous customer interactions.

4. Improve Your Contact Center KPIs

Staying on top of your Key Performance Indicators (KPIs) will be more efficient when you deploy conversational AI in your call center facilities. There are many ways to support your team in meeting current goals and addressing trendlines.

After all, how can you expect to boost your KPIs when you're also experiencing employee turnover or facing severe difficulties in employee retention? It's no secret that conversational AI makes for a more stable work capacity. With virtual AI assistants deployed to run 24/7 on demand, you can alleviate your workforce's workload and, consequently, combat human agent turnover. 

Additionally, conversational AI leverages Natural Language Processing (NLP) to "understand" the customer's intent, which helps gather the required information from your database. For example, the system pulls up a customer's shopping history when the customer brings up a problem with a "recent shipment." This combines information the customer is providing to the virtual assistant with your database.

Conversational AI allows you to scale the capacity for your human team to work on other tasks without losing the human aspect of customer interactions. The upshot is that you can reliably offer 24/7 support and achieve 100% call acceptance, helping you delight customers and meet KPIs

Perhaps best of all, the system enables you to better meet customer demand–especially during upcoming holiday seasons. And it's easier to respond to all types of callers, even when they are phoning in using different languages or are coming from any time zone on the planet. Conversational AI will always be there to greet and respond to their inquiries.

Scaling Your Customer Support Team With Conversational AI

It's wise to keep an eye out for new processes that can boost performance and support your team more effectively. With virtual AI assistant technology running in your organization's contact center, you can get more work done with less.

From conducting customer calls and answering their most pressing questions to automating the most tedious tasks and supporting your workforce to scale up capacity, conversational AI is poised to take your company to the next level.

To get a better return on your investments in contact centers, HR operations, and other areas you're looking to improve business operations, it makes sense to look for solutions such as conversational AI. This is crucial when you are mandated to offer 24/7 support and increase customer satisfaction.

Interested in learning more about DRUID's conversational AI solutions for your contact center? Download our free case study to see how we've helped other businesses thrive. 

Banking Case Study

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