Chatbots have found their place within the realm of customer experience. Brands are no longer asking, “Do I need a chatbot?” In the face of increasing customer demand for responsiveness, round-the-clock coverage, and digital self-service, savvy brands are already planning their chat automation roadmaps several years out.
Discussions have evolved to be about how to use conversational technology to drive desired outcomes and exceed customers’ expectations. When framing your conversational strategy there are many decisions to be made, but perhaps the most impactful one is whether to power your chatbot with Conversational AI or a more traditional rules-based engine.
What’s the difference?
Traditional chatbots are programmed to follow a pre-determined flow, presenting text menus or buttons to guide the user. They can be set up to recognize specific keywords or patterns, but the “brain” of the bot is primitive and doesn’t learn from experience. Chatbots built using this type of simplistic pattern-matching will not be able to handle things like typos, slang, or unanticipated phrasing. And without good error-handling, they’ll respond too often with the dreaded, “Sorry, I didn’t understand.”
By comparison, chatbots powered by Conversational AI leverage recent developments in natural language processing and artificial intelligence. This type of chatbot is trained and learns to interpret a much broader set of inputs based on its initial training set. It also learns over time based on how real-world users interact with it.
Most importantly, users don’t need to speak the bot’s language: they can simply ask their question in their own way and trust that the bot will understand. Chatting with a traditional bot often feels like talking to a system, whereas a conversation with a well-designed chatbot powered by Conversational AI feels much more natural.
The case for traditional chatbots
While they may lack the kind of natural interaction Conversational AI can bring, there are many instances when using a traditional chatbot is the more appropriate option.
First, when you need to deliver simple automation quickly, the path to launch for a traditional chatbot can be less complex. Chatbot initiatives with a targeted scope can often be launched in shorter timeframe.
When the list of paths and options in the bot is constrained and unlikely to change much, a traditional menu-based chatbot will also offer a simpler user interface. The overhead of building out Conversational AI may not be warranted for these cases.
Another case where traditional chatbots shine is experimenting to test your users’ appetite and reasons for using automated chat. This can be a good starting point for brands that aren’t ready for the more substantial investment and cross-departmental support that Conversational AI typically requires.
The case for Conversational AI
Despite the greater level of investment required, Conversational AI is the right choice when users’ needs vary widely and don’t fit into a flowchart.
Thanks to advances in AI and natural language processing, Conversational AI also delivers more robust recognition in the face of slang, typos, and novel phrasing. This translates to fewer instances of the dreaded, “Sorry, I didn’t understand.”
Lastly, if your goals include providing a differentiated user experience that delights your users, Conversational AI offers the true potential of a powerful virtual assistant, allowing users to speak naturally and have their needs understood.
In short, when automation needs to be able to handle a wide range of user requests, in a way that feels more human and natural, Conversational AI is the better choice.
Key considerations of both Conversational AI and traditional chatbots
1. Make your bot as smart as possible with integrations to data sources
Some brands are reluctant to employ automation because they see it as delivering an inferior experience; they assume customers would always prefer to reach a human, regardless of context. But recent data confirms that most consumers are very comfortable interacting with chatbots and, in fact, they often prefer bots over human agents, provided the bot is equipped to answer quickly and fully handle their request.
In order to deliver on this expectation, it’s important to connect your bot to the remote systems needed to fully handle user requests. These may include your billing system, order status, or CRM. Most conversational platforms on the market support integrations with any remote system that offers an Application Programming Interface (API).
Whether your bot’s front-end interactions are scripted or powered by AI, it’s important to not neglect the back-end layer that allows you to connect your bot to critical information from other systems.
2. Launching is a milestone, not the destination
Regardless of which conversational technology and integrations you choose to power the bot, keep in mind that launching your chatbot is a milestone, not the destination. The post-launch tuning period is a critical step to achieving optimal performance.
Tuning is the process where you evaluate how users are interacting with the bot and adapt the experience to be as seamless as possible based on real-world usage. While changing scripted menus and pattern matching takes a bit more effort, conversational technology is designed from the ground up to easily evolve and adapt over time, with most platforms offering detailed performance analytics that allow you to pinpoint exactly what needs to be enhanced.
Budget for success, feed the bot, and plan for the long term
Whether your brand is contemplating its very first chatbot or looking to expand its conversational AI footprint, here are the most important takeaways to consider:
- Budget and plan for a successful implementation, including everything needed to empower how the technology performs.
- To maximize your chatbot’s value to your users and the business, connect it to relevant data sources via integrations.
- Don’t forget your bot post-launch. Plan for ongoing tuning to drive higher performance and unlock new automation opportunities.
No matter which technology you choose, the effort in deploying chat automation will produce substantial payoffs in the forms of elevated CX, brand reputation, employee experience, and brand loyalty.
