In this episode, you'll hear insights from Jenny Ames, Gary Maggiolino, and Joey Moritz about the new chat bot that was implemented on a few different InterSystems sites. Using a chat bot, in conjunction with a human support team, can enable users to find answers to their questions quickly and easily.
To see the chat functionality discussed in this podcast, you can check out https://gettingstarted.intersystems.com or browse https://www.intersystems.com, notably the "Try InterSystems IRIS" page linked at the top.
For more information about Data Points, visit https://datapoints.intersystems.com.
Derek Robinson 00:00:02 Welcome to Data Points, a podcast by InterSystems Learning Services. Make sure to subscribe to the podcast on your favorite podcast app. Links can be found at datapoints.intersystems.com. I'm Derek Robinson. And on today's episode, I'll talk to a few different team members here at InterSystems about the all-new chat feature that enables users to get their questions answered quickly and easily.
Derek Robinson 00:00:39 Welcome to Episode 12 of Data Points by InterSystems Learning Services. Today's episode features parts of conversations with three different people at InterSystems. These three people are Jenny Ames, the team lead of Online Learning content, who you've heard from before; Gary Maggiolino, Senior Manager of Global Marketing Technology; and Joey Moritz, Market Development Event Representative. Jenny, Gary, and Joey all have different roles, and they complement each other in the project that you'll hear us refer to as the chatbot. This chat tool is something similar to what you've probably seen on a bunch of websites, a pop-up assistant to help the user find what they're looking for or answer their question. This episode contains a look behind the scenes of building that functionality to help InterSystems users browsing the Getting Started site, the official InterSystems site, or the Try InterSystems IRIS page. Rather than run the interviews uncut, I'm grouping together their answers on various topics so we can easily hear the similarities and differences in their perspectives.
Derek Robinson 00:1:42 My first question to all three of our guests was about the value that a chatbot like this provides for our customers. You'll hear Jenny, Gary, and then Joey give their thoughts, in that order.
Jenny Ames 00:01:52 Well, the chatbot has been really interesting because it helps us meet the need of really helping our prospects and our customers get help and answers as quickly as possible. So it really is like that first connection point. And then we can use our experts to get people quickly to what they need, and we can also learn from it as well to build on that and help make our sites better.
Gary Maggiolino 00:02:14 You know, first and foremost, from a marketing perspective, it really provides insights into the behaviors on how individuals are using the website. How are they finding information? You know, what are the questions they're asking themselves as they're researching, as they're browsing, as they're trying to find information? Gaining that type of data really helps you shape the experience. You can provide somebody — whenever somebody is engaging with your entire web ecosystem as a whole, you want to be able to provide them the most seamless, the most interactive, but at the same time, an experience that allows them to find what they need quickly and efficiently. So you know, besides that engagement, we want to know how people are using our website, but then you can flip the coin and you can look at it from a user's perspective. What chat really provides is the opportunity to engage with an organization in a very low committal way. You know, you can get answers to questions. You can find information you want, and you control the information about yourself you want to give, and when you want to give it. You're not having to register and log in. Kind of like walking up to somebody at Target and saying, hey, where are the cameras? You know, you get down to the section, you can browse, you can hold the camera, you can look at it. And then you say, if I need to know more, I can ask. And then the more I get in the conversation, I'm going to control how much information I want to tell you, what I want to provide, and what I'm looking for. So it gives that kind of experience. And that's what our goal around a good chatbot is.
Joey Moritz 00:03:59 I think the value of providing our customers with the chatbot is that instant gratification of being able to talk to somebody they know. A lot of times, they have to call, they have to get in touch with the right person. Some personalities may not like talking on the phone as much; they may be used to just typing and talking through email, things like that. So I think that when they're able to just jump on, they don't have to be a VP level or a C level or any of that. Your average developer can jump on. Hey, I'm looking to learn more about this, or my company is doing this. So you get a lot of the developers and the people doing the research actually coming to you, and you get to make that personal connection with them. And I think that personal connection, especially right now, during these times, is kind of key.
Derek Robinson 00:04:55 Considering these value props, I asked Gary for more information about developing requirements for something like this, and any key elements they needed to consider in the planning and design of this tool.
Gary Maggiolino 00:05:05 The type of chat you want to have was…actually for us, too, it was one of the most critical things we had to decide, meaning are we going to build just a live chat where somebody clicks on it, says, how can we help you, and Bob's waiting there to type away? Or is it something that's completely automated and driven by a script and predefined pathways and kind of a choose-your-own-adventure kind of book? Or is it a hybrid approach? And we built the latter. We thought it was important to let people have an unobtrusive kind of beginning to it. You know, here's the path that I want to take. I know what I'm looking for — but then provide the opportunity at multiple touchpoints to say, oh, how can we help you? Would you like to speak to somebody? Would you like to get connected to somebody? Just providing those off-roads is kind of super important to them. So we thought that was the easiest way for individuals to get information, but at the same time, have engagement in the process. You know, you don't ever want to keep somebody waiting, either. So that's kind of something. It's like you text somebody, and you're waiting for an immediate answer, and you're staring at three dots for a minute. And you know, that minute can seem like an hour.
Derek Robinson 00:06:24 Following on to that answer, I mentioned to Gary that you might also need to think about the resources that you'll make available for live chats, with something like this. Gary added a bit more insight about resources, as well as planning how many chatbots you may want for different use cases.
Gary Maggiolino 00:06:38 You know, if you're a company who has multiple products, so you know that you span multiple industries, are you going to build one or two that addresses all products and then all industries, or are you going to specialize? You know, you can build 10, 12, 15 bots in the blink of an eye if you really say, I want to have customized journeys and speak to people in their own language. And of all of those though, one of the most key elements is be conversational. Remember, this is a person; the goal of this is to have someone talk to somebody. So even if it's automated, it should have that tone to it.
Derek Robinson 00:07:12 Gary's final thought here stood out to me. The goal is to talk to a person, but here we are, talking about a chatbot. I asked both Jenny and Joey for their take on the transition between robot and human in tools like this one.
Jenny Ames 00:07:25 Yeah, that's a great question. So first of all, we established up front that our main goal is to help people get the answers they need. So whether that's the bot that can answer the question or a person that can answer the question, we want both customers and prospects to be successful. And so whichever one can answer the question better, faster, that's really the ideal. Now that transition between the two is really, really important. So the bot should not be a person. It needs to be clear. It's not going to have a person picture there. It's going to be a generic graphic or something like that. And it needs to be very clear that it is a bot that is not going to be as personable. Now when the human jumps in, they need to be personable and open and transparent. And so one of the things that we've been kind of working through is for the person to, right off the bat, introduce who they are and then ask how they can help before even looking at the conversation. Then they go back and look at the conversation and try to catch up. But yeah, making that distinction between the bot and the person is really, really important, to set expectations for what kind of conversation they're going to be able to have.
Joey Moritz 00:08:40 The transition from the actual to the human is very important. You can see a lot of problems that could occur during that transition with the many different questions that can come up, and just training that bot to ready for any of those to come up. It can just be a mind-numbing task. But I think that where — back to the value is — even if that bot doesn't seamlessly pull us in, we have such a great team already usually watching, that we can notice something going wrong and we can jump in. And I think the customers just getting somebody there willing to help them kind of lessens the need for the seamless transition as much as okay, at least somebody is here to help me, like that's their comfort zone now.
Derek Robinson 00:09:33 So a bit of a common thread that maybe I didn't really expect here was the notion that you may actually not want that transition to be totally seamless and undetectable. Maybe it is better for the user to actually know that they have made the switch from bot to human. Joey echoed this with this short follow-up answer.
Joey Moritz 00:09:49 I almost want them to know they were just talking to a bot and now they're talking to a human who is going to give them human responses. And you know, this is also a good time to bring up like, oh yeah, I know your team that you work with, things like that. So, as much as you would love it to just go bot to human without them noticing, I think there is some appreciation and the fact that, okay, we got the bot to do what we need it to do. Now they have a human and they feel comfortable.
Derek Robinson 00:10:23 I wrapped up the interviews with each guest by asking general questions about the overall process, as well as their key takeaways. Here, you'll hear their answers about the process of working as a cross-functional team to build this thing. And I have to issue a quick apology here. You'll hear a Microsoft Teams message sound during one of Jenny's answers. That's on me. I forgot to mute my alerts. So don't be confused why you actually don't have a Teams message. That's straight in the podcast audio.
Jenny Ames 00:10:46 It's a really interesting project because it unified a lot of different teams at our organization. So we have FRC, which is really the first response center. They are the first people in support that take the initial calls and then route them to different places. And then we also have ; they're more on the sales side, working with prospects and identifying leads. These are two awesome groups, but they don't really have many opportunities to interact and collaborate. So it's been really interesting to see how they've been working together. I think one thing that we've learned through this is setting expectations up front on what this is and how we can help. So to our customers, the chatbot is not really a way of getting support. Really, they should be going through support at intersystems.com, and the regular filing a ticket through the WRC, but the FRC group and the MDR group, they're really good at knowing who to connect people with. So one of the things we've learned is we may not necessarily be able to answer those big technical issues, which might be what somebody might expect the beginning. So we're trying to be better about setting expectations on what the
chatbot is, and how to really help people the best. But I think that's one thing that we're learning and we're trying to get better at. But it's also been a really great tool to unify within the organization, break down those silos, and really learn from each other, both on the support and the sales side.
Joey Moritz 00:12:17 Yeah. Luckily, I don't have to do the actual implementation of it. For me, it's more just viewing what's going correctly and what's going incorrectly. And then I just have to report it back to Gary and Jenny, who have to do the hard work. One thing though that I have found interesting about this project was seeing the different teams work together. As you said, we all come from different backgrounds, and we all have different positions in it. And a lot of times I'm used to working with marketing and sales teams because of my position, where now I'm seeing the FRC, the WRC, and kind of seeing how the support teams work together and everything. And I think that that's very important from an internal aspect because you're kind of getting out of your every day. Well, this is how the company is run. You're like, Oh, this is a whole 'nother world that the company that I had no clue existed.
Gary Maggiolino 00:13:17 We spent a lot of time, after we launched it in the first 30 to 60 days, and really looked at the data behind the conversations: how were people having them…you can do what you call a path analysis and say, oh, more people are following this path. We got to repeat it, we got to do it. But when you got into the nitty gritty of the conversations, I think the biggest thing for me was trust. And, you know, anytime you're engaging with an individual and you've established trust with them — I mean, that's huge. And I look back at the conversations, and you see where we've answered a question pretty quick, or maybe we've even solved a problem. The tone changes so fast. "Is there anything else that can help you with?" "Oh, by the way, I need this, this..." They become very open. They become very free. You can actually see where that wall comes down, that you've established trust and credibility, that you're there, and you're there to help them and support them. You know, that's one of the biggest things. And it's actually become a metric for me to look at, is how are we using this to establish trust with individuals?
Derek Robinson 00:14:32 Lastly, here are the key takeaways each of our guests had about where this project ended up, and what the future might hold.
Jenny Ames 00:14:38 So I think the biggest takeaway is: a chat element on the website is a really great tool. It's really just the beginning of the conversation. And one of the things that we have been trying to evaluate and how successful this is, is those different handoffs. So while the bot or a person, the live chat agent, is really that first connection point, what we really want it to be is a filter into the rest of the materials. And we want to really fine tune. It's going to be an agile process. We're going to continue to improve it over time, figure out what is most useful to people. And then we really want to evaluate based on those handoffs and how those handoffs are really helping people to be successful. So it's a process, and we're learning from it as we go.
Joey Moritz 00:15:30 I think this chatbot is great. I think it's great for our customers, our prospects. I think it really nails home kind of what John Paladino always brings up about our customer support is unrivaled by anyone else. And I think that this goes to show how much further we're willing to go than other people.
Derek Robinson 00:16:39 So thanks again to all three of our guests for taking the time to chat, no pun intended, of course. Hopefully you liked the different format of this podcast episode that featured spliced-up answers to my questions and kind of framing them in context. It seemed better than airing three interviews that were largely redundant right next to each other. This project turned out great and has been providing users with a path forward to answer their questions. Hopefully you found it useful, either due to your own interest in InterSystems products, or maybe your own interest in building one of these tools for your websites. To check out the bot that this team built, you can see those websites I mentioned in the intro, which are linked in the podcast description. That'll do it for Episode 12. Thanks for listening. And we'll see you next time on Data Points.
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