At this point, it’s an obvious understatement to say that there’s recently been a lot of excitement about Artificial Intelligence (AI). But let’s be frank. Its more of a feeding frenzy. Which reminds me. I read a report this week that said that all the great white sharks have left South African waters. Maybe they’ve joined the party that’s feeding on all the chum of AI.
Seriously, it’s legit for Customer Success professionals to be asking what is AI? How do we use it? Can we leverage it for our business? How intelligent is it, really? In Customer Success, we like to say we’re proactive. That means we should always be thinking ahead and figuring out the best ways to harness new tools and technologies to help our organizations evolve and our customers to more optimally achieve their desired outcomes. With this in mind, I’ve turned to a good friend of mine of many years, Mary Poppen. We sat down and had a chat about AI and Customer Success – what it is today and what it could mean for us, tomorrow. I hope you enjoy this recap of that conversation. Oh, I almost forgot something super important. Mary and I will be speaking together on a panel, along with Jay Nathan and Alli Tiscornia, at Alli’s company’s annual conference on Oct 4/5. You should check out the agenda for Churnzero‘s BIG RYG and consider registering.
The conversation
Peter Armaly (PA): So, tell our readers a little bit about yourself and your career in Customer Success. What got you involved in the industry?
Mary Poppen (MP): I’ve been in customer delivery pretty much my entire career. If you had asked me years ago if I would be in tech, I’d have said no. But the majority of my career has actually been in tech, mostly HR tech. I got involved in Software as a Service in the really early days as it was completely shifting the customer experience. Seeing that transformation firsthand has been really exciting. I was a Chief Customer Officer for over a decade, moving from SAP to Glint Inc. and then LinkedIn. I’ve always been focused on building out the customer experience. It’s been a really wild, exciting ride. What I’m doing now is a kind of synergy between employee experience and customer experience. So, having built the customer experience for technology that was focused on employees, I was able to really see the link between impacting customers and impacting employees. I have the opportunity to bring those pieces together in my current role, which is the President of HRIZONS, Employee Experience Division.
PA: We’ve talked about how employee success leads to Customer Success in a previous interview with our own CEO, Michael Harnum. We know firsthand how important that connection, that link between the two, can be. Your book, Goodbye, Churn. Hello, Growth!, talks about this too, harnessing customer intelligence to create employee heroes.
MP: Yes, I talk about leveraging customer intelligence to kind of get ahead of your customers and start predicting what their needs are. One of the chapters is all about creating opportunities for your team to jump in and become heroes for their customers. To deliver the right service at the right time, which is super engaging. Who would want to leave a job where they’re having fun and doing great work that makes that kind of impact on your customers’ lives? We’ve been collecting data for years, and with the right technologies, we’ll get to the point where we can actually truly predict what our customers need – before they even know they need it.
PA: And this is where these new, advanced tools we’re hearing about these days come into play.
MP: Yes, and with AI, we’re talking about leveraging it in two key ways. One is tactical usage, you know, like content generation. The other is in the backend, analyzing trends and patterns across millions of data points to raise insights Customer Success can use to be strategic and proactive. Both of these pieces have value. Both will help teams scale. They’ll also help create an amazing experience for our customers.
But these tools come with risks too. If you’re not giving your team any guidance, they might end up communicating in a way that doesn’t follow policies and protocols in terms of what information gets shared. An important part of AI for CS will be building guardrails and governance for customer communication. You’ll have early adopters on your team that love new tech and innovation. They’re willing to just turn it on and try it. Then, you’ll have others that will need more guidance. They want direction, templates. They need that to be successful. Most CS teams are going to have a mix of different appetites for innovation. You have to decide how far to let people innovate and create new use cases, and then create consistency as you scale.
PA: I think we’ve gotten a taste of what AI can do through some of these platforms that have been out for a while. Technologies dedicated to Customer Success. But I know we’ve faced a lot of challenges when it comes to implementing some of these solutions, company-wide.
MP: It’s true. If we think back, AI has been applied to Customer Success for several years, but it’s all been behind the scenes. Within certain platforms. The challenge is that every function in a company uses different solutions and they don’t share data across systems. A lot of times the data isn’t maintained or processes and people change. All of a sudden, you have years of data that you’re not even sure is good.
PA: Unfortunately, it’s a common theme, especially for CS Ops.
MP: I like to think that the real, untapped potential of AI, machine learning, and natural language processing is the ability to take data across silos, across functions, and integrate all of the information you’ve ever collected on your customers. Once you can do that, you have a complete story, and that story is everything that’s happened with your customers in the past. What’s happened in the past can help us predict the future. So, what are those flags and triggers for a customer who’s going off-track? Right now, we’re telling CSMs, it’s your job to figure out if a customer is doing well. You’ve got to keep that customer happy. But we’re not arming them with any insights or the right tools and processes. If you’re not doing that, you’re not setting them up for success.
To me, that’s the real possibility of AI. It’s not just being proactive. It’s more. It’s being predictive. It’s knowing that if my customer stays on this product adoption journey, I know it’s 10 times as likely they’ll renew. I don’t need to wait till their contract is up to ask for an expansion. I can go in right when the customer needs it because I know their license consumption is so significant. It’s those kinds of things that I think tech, and especially AI, can help teams really wow their customers.
PA: It’s building that strategic partnership.
MP: I’m a little concerned that people think AI is just going to help with content generation. It’s so much more than that. I feel like we say AI and people have a narrow view of what that entails. It’s hard to get your arms around what it can really be unless you’re an engineer or a data scientist. But ChatGPT has put something in front of people that’s tangible, and it can be understood. So, when you say AI, people know what that is now. Which is cool, but also not the whole story.
PA: The content piece is sort of like a shiny object that everyone is really excited about, but the real work is in everything going on behind the scenes with data and data governance, pulling it all together like you said, into a full, comprehensive customer story.
MP: Absolutely.
PA: It does seem like tech solutions are really on the ball. They’re working on incorporating this AI functionality as fast as possible. Some of the Customer Success Platforms out there, for example, have some AI tools integrated already.
MP: A lot of our tech stack today, probably like 80% of it, has an AI offering built-in already. So now customers should be asking providers, what are you doing with AI? How can we use it? Because now you have things that can improve your business that you don’t even have to pay extra for. If it’s in the technology, in the tech stack you’ve already implemented, take advantage of it. See what’s there!
PA: Some of these cutting-edge tools are really taking this AI trend and running with it.
MP: They are! I feel like there’s this window we’re in right now of total exploration. We’re going to see how many use cases we can come up with, see how we can use AI, what we have and what we’d like to have. I don’t know how long the window will be open, but my guess is it’s not going to be for very long. Governments are going to come out with compliance regulations. We’re going to start seeing more questions, concerns, about security in particular. I think the key is going to be finding a balance, making sure that these fears are not slowing down what organizations can do and what we can continue to improve so we can move forward while also mitigating risk.
PA: In my experience, it’s not just security concerns, but also status quo. Patterns will emerge and start establishing norms. People are going to see these tools used for specific things, and then there’s less “outside the box” type thinking. But right now, there are no boxes!
MP: I think that’s a really good way to put it. We’re in this window of pure potential right now. How much “out of the box” can we do? That’s where the talent is going to go, too. Who’s innovating? Who’s at the leading edge? Who’s allowing their employees to really go for it?
PA: In that vein, have you seen any platforms that are really taking things to the next level for Customer Success organizations?
MP: Well, there isn’t an end-to-end platform out there yet. Really, it’s individual solutions I’m seeing. For example, I’ve been working with involve.ai to get their solution off the ground. We’re building a customer intelligence solution that does the hard work of pulling all the data from multiple sources and aggregating it and then running the AI. It already has models trained on millions of pieces of data that are customer-related, like adoption and customer satisfaction. It’s a solution that will allow you to very quickly take your historical data and apply a model that looks ahead to the future, like seeing who is at risk with your current customer base. It’s exciting. And there are platforms like Gainsight that has built AI into their workflows. They keep innovating and acquiring. Definitely one to watch. Also, startups like Bagel are leveraging AI to solve business problems in new and better ways. There will be many solutions that re-imagine how business can be done through leveraging the power of AI over the next few years. The role of Customer Success will continue to evolve in the strategic direction as AI helps reduce time to bring customers value and allows for predictive delivery.
PA: But, because there’s no one-size-fits-all, end-to-end solution, Customer Success leaders need to get out there and see what’s happening. Find out what’s available and what is going to meet their growing needs the best.
MP: Yes, and we’re also going to start to see a consolidation of some of these solutions. Whether it’s through acquisition or some companies building a broader platform to meet those needs.
PA: What advice would you give to CS leaders approaching their executive leadership to ask for investments in some of these resources for their organization? How do we make the case for these trailblazing tools and technologies?
MP: Every once in a while, you get to work with an executive team who really understands that improving the customer experience and improving the employee experience will result in returns on the business. But it’s kind of rare. So, the reality is, anytime you’re going to ask for an investment, you need to tie it to a business impact. You have to find the business impact that is meaningful to them. Right now, it might be attrition. You might have lost really great talent and feel the pain because really big customers have been transitioned to multiple people in the last six months. They’ve had three CSMs. They don’t know who to talk to anymore. The executive sponsors are getting calls. Team turnover would be a good place to start making a case in this example. If operating margin is the focus, you could say, we’re going to scale the business, we’re going to give people these tools to help them take on more customers, and do their work more effectively.
Another example is if you see a drop in customer satisfaction or an increase in support tickets – that’s costing the business. If for every escalation that comes in, it takes an average of 16 hours to resolve it and X resources from Product Engineering, you could run the numbers and figure out what implementing the technology will save. Say it reduces those hours and resources by 75%, which means a return of Y and Z to the business. It’s an easier sell when you tie it to business outcomes.
PA: It’s easy to get excited, but we need to do our homework.
MP: Yes.
PA: One of the fun things I got to do for our recent white paper on Advanced Digital Modalities in Customer Success was sort of dream a little bit about what the future could hold for us. What these tools could evolve into for CS. If you could take all these new possibilities to the extreme, what’s your dream for the future of digital Customer Success?
MP: I’m going to go back to prediction. And actually, in my book, I have five P’s. I mention using tech and data and AI to have a playbook that’s predictive and then prescriptive because you know your customer really well. And you’re proactive, so you’re going to act ahead of time. And it’s personalized. For me, the predictive piece and the personalized piece are the two things that will really differentiate a company and an experience in the future. If you can arm your employees with that, they’re going to be more strategic, that much more prepared, and that much more ahead of their customers. It’s just a win-win-win all around. A win for employees, a win for the company, and a win for the customers. That’s where I see us going. I would love to get there. It’s going to differentiate the great companies from the good ones.