Webinar Q&A Recap: Is CS the Next Frontier of AI?

January 25, 2023

Kate McBee

Category: Customer Experience, Customer Retention, Customer Success as a Service, Customer Success Maturity, Customer Success Operations, Customer Success Strategy

Speaker: Joel Passen, CRO and Co-Founder of Sturdy

During this session, host Peter Armaly was joined by Joel Passen to discuss practical applications of AI in the Customer Success world, challenges teams seeking to use AI are facing, and what’s on the horizon. Our audience submitted some compelling questions and Joel’s thoughtful answers are outlined below.


Q: Are both Customer Success and Sales paying attention to the AI input?

Joel Passen (JP): Look at Clarity, and there’s a whole handful of these solutions out there. I mean to a certain extent, Chorus and Gong bring this to life, but I think Sales is ahead of post-Sales in terms of technical sophistication, resource allocation, operation, and budget. By the way, this is probably another, you know topic, and probably something you’ve already explored, Peter. But if you want, so as a CS leader, if you want nice things, you carry a revenue number. That’s why Sales get nice things because somebody has ascribed, leadership, they’ve ascribed the revenue number to that person, and then they get resources to hit that revenue number. And so,  I did a panel talk at a conference, and they’re like, “how do I get a seat at the table?” and I didn’t want to, you know, act like I was trivializing it, but yeah, you carry a revenue number, you get in the revenue business, and you get nice things.

The other thing that I would say to this audience member is, you know, how are… I have a really specific example here, and this is not an infomercial for Sturdy, but one of the things that we built, because there’s a lot of it going on, is we built a detector, an AI, a language model, that detects when Sales has over-promised during the sales process. That now has come home to roost in post-Sales, and the customer is dissatisfied. So, it’s using AI to cross the chasm and create the collective reality and say, “hey, sellers, you people are saying this stuff, but we don’t actually do that”. Therefore, this relationship that we’re supposed to monetize for a long time is messed up, and it started here. It’s not because of our service delivery and frankly, it’s not necessarily because of a product deficiency. It’s because somebody has said something to the customer that’s inaccurate during the Sales process that now created this baggage that we’re forever carrying on the post-Sales side of the ball. I think that’s a practical application where AI can merge the two, where AI and CS are drinking from the same cup, so we get that out of our systems.


Q: Early on in the conversation, you talked about data, isn’t that incumbent upon the CS leader to get into place instrumentation for the data, what’s going on in the customer base, and the tools for execution? Essentially, does that all have to happen first before you can actually exploit AI?

JP: I think that the fundamental thing is that you have to have in place a customer database of record, and my advice is that you have at least some simple segmentation done. And I think those are the base-level requirements for starting to deploy an AI solution. I think what we’re missing, a lot of us if we really boil it down, I think the thesis of my answers to your questions in this webinar is, AI is very good and it’s because it’s a computer. It’s analyzing large sets of data to create insights that impact an outcome. And to that end, I think we’ve already got these data collection mechanisms in our company, like Zendesk or Freshdesk or ServiceNow, whatever you’re using for ticketing is a database with structured information in it that can be analyzed right out of the box. Email, it’s kind of a frontier that it’s not been analyzed yet, but the amount of email that we collect, the back and forth, and interactions between our customers, we already have it. Outlook and Gmail save it all.

Peter Armaly: I just read the other day that it’s still the number one channel for communication.

JP: Oh, by far. We find that it’s 2X. I mean if you get 100 tickets a week, which is low, you’re going to get about 300 emails a week. Right? We’re trying to figure out what are the major channels of interaction with customers. Of course, usage data and some stuff that’s already been really well done by a lot of our peer vendors. But emails are like a black hole, it’s like the dirty secret. By the way, finance email, like understanding the insights from financing, I’m not talking about like reading, creepy reading their emails back and forth to their, you know, spouse or partner about coming home late, and the pot roast isn’t done. I’m talking about reading specific customer emails or analyzing them for signals of importance. So to your friend’s question – actually, I don’t really think so. I don’t think you need to build all this tooling and infrastructure. You’re already collecting all of this stuff in commercial databases and silos already. Now it’s just a matter of applying something to it. They can aggregate it, normalize it, and start to analyze it so you can get insights quickly.


Q: If you had one wish that you were granted and it had to do with this Customer Success community that you’re a part of, what would it be?

JP: I guess my one wish for people to take away from this is to dispel the fear that AI is here to do your brain work. AI is here to do that tiring, mundane minutia-driven stuff that you’re carving out budget to do already.

And so frankly, it’s just like the cloud. And this is really similar, Peter. I remember – I’m of the age when people were like, “is it in the cloud?”, meaning, “you have all my data”, and people will be like “oh, the cloud is bad”. I mean, I’m that old, and you’d have to fight it. I was selling a SaaS product back when it used to be the install base-only crowd. And I was trying to get people to cross the chasm to join the cloud, and now I’m significantly older, 15 to 20 years older now. But I feel the same inertia. I feel the same sort of mechanics with getting people to adopt. Listen! It’s not just AI, it’s data sciences to do our job better. Don’t be scared. There are some folks that would kind of, probably, they would raise an eyebrow at this. But yeah, there are always things that are going to be creepy. They’re always going to be things that are going to be nefarious. But I think, as business leaders, you know, part of our job is to cut through that and see if there’s actually real value in something that isn’t a challenge ethically or more or morally. And I don’t think we’re talking about that in this community. So, my wish is that people think about it as something that can advance them and their team’s understanding of their customers to drive value. And I think that the future is the system of intelligence that sits between some of the tooling that we already have, but provides advanced outputs.


Watch the recording of this webinar to catch up on the full conversation!