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.
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:
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.
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:
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:
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 AI agents and intelligent automation can help increase efficiency, reduce costs, and deliver a superior customer experience for contact centers.
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