contact center

Conversational AI for Contact Centers - Top Deployment Tips

Top deployment tips to run conversational automation projects for contact centers and customer support teams with AI chatbots

Today’s contact centers are sophisticated technology hubs with integrated software systems. Cutting-edge contact centers have also embraced conversational AI, moving beyond the awkward, limited interactions of conventional chatbots - and it’s not for the reason you might think.

According to a recent poll, customer experience has surpassed cost savings as the number-one reason for adopting AI. This fact underscores the ways that customer expectations have evolved, and how enterprises in every industry have had to respond.

Regardless of your motivation for deploying conversational AI, it’s critical to make the customer experience a top priority. These tips will help ensure a smooth deployment while keeping your customers happy.


#1. Get Your Data in Order

Your conversational AI solution can only be as good as your company’s data. First and foremost, an AI chatbot uses data to learn. Then it uses data during interactions with customers, bringing additional context and information to the conversation. And finally, the bot provides a wealth of new data that can then potentially be used elsewhere in the business.

To that end, the first step in any conversational AI deployment is to assess your current data architecture:

  • What data sources are already available? Do you have access to any conversation logs that could be used to train a chatbot? What data would help personalize customer interactions?
  • What data will the chatbot need to operate? In a contact center, you’ll surely need data from the CRM. Other necessary data might come from the ERP or back-office systems.
  • How can these data sources be integrated? Will they require an API?

Once you’ve answered these questions, it’s time to consider what to do with the data that will be generated by the chatbot itself. Of course, you’ll need to develop a data governance plan and privacy policy that comply with any relevant regulatory requirements, such as GDPR or HIPAA.

The next step is to think about how you can use the data collected by chatbots to make better business decisions across the organization. In some cases, you may even decide that you want a business intelligence (BI) chatbot to deliver personalized, real-time data and report to business leaders for added visibility.

#2. Choose the Right Starting Point

There are plenty of use cases for conversational AI and chatbots in contact centers. So where do you begin? At its core, the adoption of conversational AI is essentially an automation project - you’re automating the customer interactions normally handled by a contact center agent.

In that context, the ideal starter project offers substantial potential gains, without being too complicated. Consider these factors as you decide which conversational AI project to tackle first:

  • Complexity: Automating an extremely simple process might not yield high ROI, since it doesn’t require much time to complete. On the other hand, automating an overly complex process right away can be too difficult. Choose something that will result in material time savings, but isn’t so complicated that it will be impossible to automate without significant experience.
  • Repetitiveness: Your contact center agents can tell you what inquiries they answer over and over again. You’ll see the biggest time savings by using conversational AI to address these queries. Repetitiveness can also mean that your chatbot gets trained faster since it will quickly see how many different people ask the same basic questions.
  • Repeatability: It’s impossible to automate something that isn’t standardized. Select a process that all employees complete exactly the same way, every time (or should, anyway!).
  • Audience: Think about the types of people who use your contact center. Some of them might have very specific needs. For example, a utility company’s contact center probably gets different questions from its business versus residential customers. It can be beneficial to choose a specific audience for your conversational AI “pilot group.”

Want To Learn More About the Benefits of Conversational AI for Contact Centers?

#3. Plan to Scale

Your conversational AI initiative might start small, with a single-use case for a limited audience. But to maximize ROI, you’ll need to scale up. For example, you may also need to expand to different geographical regions or add more languages over time. Be sure to select a chatbot provider that reuses what you’ve already created, rather than rebuilding a brand-new bot from the ground up for each language.

Equally important is to plan how you’ll scale your conversational AI to other channels. Consumers are increasingly expressing a preference for seamless, multichannel interactions. And there are many channels to choose from:

  • Interactive voice response (IVR): This is perhaps the most common channel for chatbots in contact centers, because it’s for telephone callers.
  • Website: Users are accustomed to interacting with chatbots on all kinds of websites, making this channel relatively important.
  • Messaging apps: Using conversational AI to proactively reach customers via text messages can help reduce call volume.
  • Social media: Users are already engaging with social media, so implementing conversational AI here can help you connect with customers more easily.
  • Smart speakers: These are still considered “emerging technology,” as they don’t have widespread adoption among consumers. However, forward-thinking organizations are offering chatbots for smart speakers to help users get accustomed to the technology.
Prioritize the different channels based on your organization’s capacity and your customers’ behavior. Once you’ve perfected your most important channel, move to the next one.

#4. Decide Who’s Running the Show

Once upon a time, programming chatbots was a laborious, complicated process that required highly specialized expertise from people like computational linguists and data scientists. They also required extensive programming, both at the beginning and as updates were needed. It’s no wonder, then, that chatbot maintenance was often relegated to the IT department.

Today’s low-code and no-code chatbots don’t require such sophisticated expertise to train, launch, and maintain. But it can still be tempting to put IT in charge, since chatbots are, after all, technology. But while your IT staff are dynamite at all things hardware and software, they’re probably not as well versed in your customers’ perspectives and needs.

Here's an example showing how the DRUID platform's Conversation Flow Designer works to enable any business user to configure complex conversational AI solutions:


The person with the ultimate authority over the chatbot deployment should be someone who’s intimately acquainted with your customer journey, in the context of your contact center. They should also understand the challenges faced by your contact center agents. This might seem counterintuitive for technology deployment. Keep in mind that this person will likely be the best equipped to keep the customer experience at the center of the project, with technical support from your chatbot provider and IT team.

Learn how conversational AI can help increase efficiency, reduce costs, and deliver a superior customer experience for contact centers.

Get the Guide

Similar posts

Get notified on new Conversational AI insights

Get the latest insights on how conversational AI and automation are transforming the way teams work, while enabling cost savings and better user experience.