5 Steps to Make Chatbot Call Center Convos Feel Human
Although chatbots can be extremely helpful for call centers on the backend, they still don’t have a great reputation among customers. Simply put, since a call center is often the very first point of contact where a customer can communicate with a given company, greeting that customer with a poorly configured chatbot is not conducive to leaving a good first impression.
This is also what leads many people who encounter a chatbot to type “Representative” or “Connect me to an agent” as soon as possible—even if the chatbot could’ve helped with their inquiry.
But before you completely give up on your chatbots, keep in mind that there are many things you can do to provide your customers with a much better experience than they might expect.
Here are five steps to humanizing your chatbot:
Step 1: Figure Out Why Conversations Currently Don’t Feel Human
If you don’t know what’s wrong, you can’t fix it—that’s why figuring out why your chatbot conversations aren’t working is the first and most important step. Look back on past conversation data and try to get a sense of why conversations are falling flat. Try to spot any trends or patterns where customers tend to bounce out of the chat.
It can be especially helpful to review survey answers from past customers, especially if you’ve received feedback from any customers who provided a lot of details. Be on the lookout for feedback from those who didn’t get their issue resolved, as well as those who ran into technical issues.
For instance, maybe a customer had a question that the chatbot wasn’t programmed to answer and wouldn’t forward the case to a customer service representative. Or maybe your system just doesn’t keep track of information across interactions like today’s best live chat software, meaning customers have to put in the same information over and over again.
Lastly, if your chatbot is relatively new and you don’t have much feedback yet, do your best to think proactively about how an interaction with your system might feel. Be sure to set up systems to capture feedback so you can use it to improve your system.
Step 2: Define Your Call Center’s Personality
While we don’t have to answer the question of what makes us human, we do know that one key element of the human experience is personality. Thus, if you want your customer interactions to feel more natural, you’ll need to develop a brand personality for your call center and work it into your chatbot system.
For instance, you may decide that you want your call center to be known for agents who are a little quirky but super personable and always ready to help. Or maybe you want to be known as a no-nonsense call center, where everything is taken very seriously.
Whatever you decide, it needs to be consistent across all of your agents and any other place your customers can interact with you—including your chatbot. Take some time to define your call center’s personality, and then use that to inform the way you program your chatbot.
If you decide you’re the quirky call center, you could program your chatbot with funny or unexpected greetings. For instance, instead of saying something like, “Thank you for calling [Company Name], how can we help?” you might program it to say something like, “Hey there, we’re so pumped to talk to you! Let’s get you in touch with the right person, lickety split!”
It’s all about getting those little sparks of personality to show up in every interaction the customer has with your chatbot so that they don’t have to wait to talk to an agent before they feel like they’re talking to a person. You may even want to take things to the next level, giving your chatbot a name and a face so customers have a clearly defined “person” to talk to when they interact with it.
Step 3: Revamp Your Dedicated Chatbot Flows For Common Inquiries
Your chatbot should have a strong personality that shows up in any interaction your customer has with it, but especially during the most common inquiries. After all, that’s when the majority of your customers will interact with it.
Start by going back through all of your chatbot flows and reviewing your most common inquiries. These could include how to replace a customer ID, how to make a purchase, what to know about a particular product, and general information about the brand.
As you do so, look for places where you can incorporate empathy and emotions into the scripts alongside your call center’s personality.
For instance, imagine a customer tells your chatbot that they haven’t received their package yet and think it might be lost.
Instead of simply programming the chatbot to repeat their expected delivery date to them, have it express empathy and emotion first. Something as simple as having your chatbot say, “I’m so sorry about this! Let’s find your package so you can get it as quickly as possible. What’s your email address?”
Go through each of your scripts line by line and look for ways to make sure they feel conversational rather than transactional. Once you’ve done this once, add it to your team’s calendar to review regularly. Consider putting together a team of agents who go through your chatbot flows and refine them at least a couple of times per year.
Step 4. Make Transitioning to a Live Agent Easy
Sometimes, customers legitimately need a live agent to get the help they need, and nobody likes having to jump through a bunch of hoops just to talk to someone. Even if someone requests to speak with a live agent via your chatbot, that interaction should also feel human.
As a rule of thumb, it’s a bad practice to program your chatbot to discourage or make it difficult for customers to ask for a live agent. Instead, the customer should feel heard by the chatbot, which should fulfill their request without making it a big deal.
If you don’t already have a dedicated flow for connecting a person to a live agent, be sure to script one. For instance, if someone says, “Connect me to a live agent,” the chatbot could respond, “Of course! Can you tell me a little about your issue so I can connect you to the right agent?”
Then, once the customer responds, the chatbot could say, “Thanks. An agent has been requested and will be with you shortly.”
One important note here: It can be tempting to add extra steps to divert some customers to self-service, especially when your chatbot recognizes their requests. Use this data to improve your chatbot and the reasons your customer got to this point, but don’t add yet another friction point that will frustrate the customer.
When you’re connecting customers to live agents, keep the chatbot flow as short as possible. Only ask for information you legitimately need before you can connect them. Similarly, if a customer gives information to a chatbot, the agent they connect to should have access to that information. Don’t make your customers repeat themselves.
Step 5: Try the Chatbot Yourself
Instead of just running down a checklist of best practices and calling it a day, take your chatbot out for a spin yourself to determine whether or not it feels human. Gather a team of agents and have them role-play as customers, asking the chatbot a variety of questions.
Remember to engage with the chatbot as if you were a real customer, working through the whole user journey from start to finish. Each interaction should end when the issue is resolved or a transfer to a live agent. As you’re doing this, consider how your interactions with the chatbot would feel if you were having them in the middle of a busy day, rather than during a practice exercise.
For instance, try to think about how you would feel during the interaction if you had a couple of kids screaming in the background or if you were trying to resolve the issue in a car on the way to work. Remember, customers may have to take care of their issues during times that are inconvenient for them, so try to design your customer service processes in a way that can alleviate some of the pain.
As you go through this process, take down your own feedback and gather feedback from other agents so you can keep fine-tuning and humanizing your chatbot.
Lastly, don’t forget that many chatbots are intelligent, natural-language virtual assistants—meaning they can learn to recognize caller intent, ask better follow-up questions, and provide smarter answers. This also means that you can go into your test process with the intent of training your chatbot to be better and asking specific questions you’d like it to learn how to deal with.
In the end, the more intentionality you bring to your chatbot design, the better the experience its users can have.