Ep # 190: How to Catch a Bad-Fit Customer Before They Churn ft. Andrew Loomis (VP of Customer Success, Sisense)

Andrew Loomis 00:05 If someone came to me, a CSM came to me and said, "Hey, I've got a great relationship with this customer, and now it's this one guy," I'm like, "You've already made a mistake because you're only talking to one person," right? So get to more people and figure out what the broad consensus is of the organization, not one person, right? Intro 00:26 Welcome to Across The Funnel, where we dig into concrete Go-To-Market moves across sales, customer success, and account management so you can build revenue that lasts. Brought to you by Hyperengage and Dextego. Adil Saleh 00:42 Hey, greetings, everybody. This is Across The Funnel. I'm your host, Adil. There's so much time that we bought in the past few quarters to make sure we come up with some unique stories. A lot of these new-age platforms we're trying to cut off a little bit because, of course, they're experimenting a lot. There's so much that they need to mature. They're so dependent on AI, I would say over-dependent on AI and the model. So that's why we're trying to hedge with more post-sales GTM leaders to explore how this industry is moving, what kind of mature experiments and initiatives they have taken down in the post-sales GTM, and what's been working for them. So today we're gonna be talking about Sisense. It's an API-first predictive analytics platform for all of your business functions, be it Go-To-Market, be it product, be it industry, or even from technology to oil and gas to manufacturing. So all of these industries. Today we're gonna be talking to Andrew, who's the VP of Customer Success at Sisense. Been there for quite some time, more than five years now. Been through the entire, I would say, post-sales journey at Sisense most of the time and taking some really cool initiatives into streamlining the predictive analytics part and, of course, the predictive revenue potential funnel. So thank you very much, Andrew, for taking the time. Andrew Loomis 02:09 Of course. Happy to be here. Adil Saleh 02:12 Love it. So now first off, being a VP in the post-sales function, I would not say customer success because customer success is now taken in a different perspective when it comes to the engineering and implementation and a lot of this over-deployed engineer stigma that's going on these days. Is this more heavily into that, and then how it breaks the onboarding to adoption funnel too, because a lot of this tooling AI adoption has been in place for not only the internal side on your product or company, but also on the external side, on the other side of the table, which is the customers and how they're adopting AI and all this. How do you see this role evolving for yourself in the recent times, I would say six to eight months? Andrew Loomis 02:58 Yeah. Customer success is in an interesting place right now. I think that there are many different types of leaders who prioritize different things, right? There's been the classic CS motion, like you go through the onboarding process, you start doing EBRs, you have your cadences, you do the renewals, right? And all of that is, I don't want to say thrown out the window, but it's being reimagined right now with the AI functionality, agentic AI in particular, that's coming in. And it's like, what do you offload to the AI agents versus what do you have the people work on, right? And so what I think about as a leader in a post-sale function is, how do we get customers to their outcome, right? That is sort of a classic approach, but it's more about, hey, I don't care about the EBRs as much as I care about are we driving the customer to an outcome, right? What is that outcome that we're striving for, and what are the steps that we are taking as a partner to get to that outcome, right? And that comes in the form of success plan. I think that would be harder for an AI agent to do on its own. Maybe they can help put some pieces together. But I think that's really where the value of the CS org is right now, is how do we get customers to their outcome, right? And then we let the agent take care of the meeting notes, the presentations. Adil Saleh 04:24 Customer research or maybe something like meeting briefs and all. So this is quite an interesting point that you brought. I know a lot of these tooling and a lot of these VPs of CS, sales, revenue, they're thinking about evaluating a lot of technologies built on top of these LLMs, and they're AI native, they call them. But the biggest problem that they're facing and their team is facing, talking about success or account management, is they're taking huge amounts of time training the LLMs with them. A lot of clients, they think that, "Hey, we need onboarding," but it seems like we are onboarded by AI asking a lot of these things to serve us, and that takes from one to three months to get to a point where they can get the outcomes which can replace sixty or seventy percent of the human effort. Keeping the research part and all this basic, I would say, conversation analysis and all this part beside. But how do you see it as a VP evaluating a lot of this technology or even building agents internally, like a lot of these companies are doing too? What is your approach as a VP? Andrew Loomis 05:32 So everyone at Sisense has access to different AI tools. We have an entire stack that our IT department has made available to the team. A lot of people have drifted towards Claude as their de facto tool of choice. The only problem with Claude can be that people can end up with duplicative efforts. So you really wanna focus on building org-wide skills that everyone can use so that you avoid repeating the same efforts across multiple people. The other thing I would say is structurally, there is a team at Sisense focused purely on engineering these AI solutions. So within the post-sale organization, we have individuals who are purely focused on building out these tools. It is becoming a full-time job in many ways because you're right, there's a lot of effort that goes into training. Yes, an agent can quickly learn the basics of customer success or any of those things, but to know what specific things are relevant for your company, for your product, your industry, your customers that you serve, that takes a lot of training and effort. So for us, we made the decision that that needs to be a dedicated role, and that's a role that we're gonna continue to invest in and potentially add more people into as this thing takes off. So long story short, everyone's using AI, and we're trying to focus more on how do we make it an enterprise standard and how we use those tools right now. Adil Saleh 07:05 Yeah, so biggest thing, because we spoke to a lot of SaaS founders, GTM leaders too, and the data integration part and putting in place all of these integrations has been the biggest thing, even with some of the competitors that I'm talking about. A lot of these BI tooling that have been legacy tooling for fifteen, twenty years, on average, the onboarding time is bare minimum around six months. So this is one of the things that Sisense has changed in the past, I would say five, six years. How do you see the big adoption to the product itself elevated during the recent years? And of course, I'm just sensing that there's some AI initiatives that you've taken as well as AI got more intelligent. Andrew Loomis 07:48 Yeah. And it's not just on the customer success side. Obviously, we'll talk more about the Sisense product later, but there's AI on both ends. We have to teach our customers how to use AI in our product, right? So AI is everywhere. It's unavoidable. It's inevitable at this point. Adil Saleh 08:05 Yeah, love that. So I was just looking deeply into the technology segment of yours, how things are moving towards that. Because a lot of these technology companies, they are thinking of, for example, you're thinking of hiring engineers that can integrate a lot of this tooling on top of LLMs or CRMs and all of those. So how do you see this? What's the shift towards the technology segment of how they're thinking of building something internally versus using a technology like Sisense? Andrew Loomis 08:37 Yeah. So I know vibe coding's really cool right now, and a lot of people wanna use it to build their own applications. However, I don't think that vibe coding has gotten to a point where people are gonna put that in a production tool that goes out to potentially tens of thousands, maybe a million people who are gonna be accessing it. It hasn't reached that scale yet. It's great for building internal tools that you wanna use for your own workflow, but I don't think it's there yet for deploying to tens of thousands of users. So that's why customers come to Sisense, right? We are an enterprise-grade solution. And I use the term enterprise loosely because most of who buy Sisense are emerging technology companies, right, that don't have engineering teams that can build an analytic solution from the ground up. They need to partner with someone not only that has the technological expertise, but industry expertise. Like, what can I build that will be a value add to my customers, right? And so we're not just a technology provider. A lot of my team is actually focused more on consulting and subject matter expertise on what makes a good analytics solution, right? So that's where partnering is really valuable, is you get the technology, but you also get access to the expertise. And again, I don't know that AI can really replace that expertise part at this point. Maybe in the future, right? It'll have industry experts powering LLMs. But for right now, we really do have to lean into our expertise as an analytics provider. Adil Saleh 10:19 Love it. So you already mentioned, and of course, keeping human in the loop is super critical for anything at scale, be it a product or solution platform, anything. So now, you mentioned earlier that you were taking some huge health scoring models, like building predictive models internally and, of course, using Sisense. So you talk about customer success, you talk about technology segment of yours. So how has that been in place? What kind of tech stack do you guys have internally to measure success? Because health scoring has become a pretty vague term. And with this AI, a lot of these platforms or models or any tech stack that VPs are using, they are still having human in the loop and some exceptional behaviors that is not giving them one thousand percent visibility because this is what they need to measure the success around any account or user. Talking about the top-tier accounts, it's about big money, right? So how do you measure success as a VP internally for Sisense? Andrew Loomis 11:20 In terms of leveraging AI or just in general? Adil Saleh 11:24 In general. Of course, there's a strong chance you implemented an AI solution or anything built off of AI. But health scoring and measuring that success point that you mentioned earlier, making your customers widely successful, is the bigger purpose we all want to advance, right, as a CS leader. So how do you measure it? What is it that you want to share? Andrew Loomis 11:49 Yeah, I mean, I think all of us that are working in a success organization, our bottom-line metric is always gonna be retention, right? That is how we look at success and failure. Now, I will say there's only so much CS can do on its own as far as retention is concerned. But how do we get there, right? That's the real tricky part. It's easy for me to say, "Oh, if our retention number is high, that means we're successful. If our retention number is low, that means we're not successful," right? But that's a lagging indicator, right? What you want to figure out is, how do I prevent the customer from getting to that non-renewal state, right? And that's where the health score comes in. I think Gainsight was the one that really popularized the concept of a health score. But I don't know that it really, again, every customer is different, and so it's somewhat difficult to kind of have a one-size-fits-all solution for the entire customer base. Where AI and LLMs have come in is like, okay, great, we have all this usage and product telemetry on our customers, right? We could plug it into Gainsight, which allows us to do some analysis on that, or we could connect it to an LLM and allow the LLM to kind of learn, and we will teach it, like, what does a healthy customer look like versus an unhealthy customer, right? And then it's off to the races at that point, right? Once it knows what healthy looks like and what unhealthy looks like, a lot of that legwork, that's where AI really does come in. And then it can build at scale, right? You can use AI to actually build the views that you want, which I think is great, but what I think is even better is now you can build an agent that says, "Hey, this customer is trending in the wrong direction, right? So you better take action now." Adil Saleh 13:45 Forecasting, yeah. Andrew Loomis 13:47 Exactly. Right? Adil Saleh 13:47 Forecasting is super important, yeah. Andrew Loomis 13:49 And not wait until you have your call with them, look at their health dashboard, and realize, "Oh, crap, things are going in the wrong direction," right? So now the agent really is that assistant for the CSM that can prevent you from getting on that call and not being prepared for that conversation, right? You're coming in with an action plan. Like, "Hey, I see this is what, let's try this, this, and this," right? So that's where I see a lot of value in health scoring in the age of AI. Adil Saleh 14:20 Love it. Love it. And also this becomes even super critical, like the agent mode that you talked about. Like that predicts, forecasts, and recommends an action, or even can do an action to some point when it understands one hundred percent about the different exceptional behaviors across any segment. So now talking about, and that's where becomes the segmentation part because I'm a SaaS founder myself. We're building a platform that is serving the post-sales, specifically the revenue account management and CS. And the biggest problem that we first faced in the first quarter was this piece that a lot of these teams are missing, like a lot of these journey mapping, segmentation. They don't know what kind of signals or success metrics are defining a better health or retention, possible retention, or what are these signals that are not good enough, so you need to take action well before time. And if you get notified like any of the tooling out in the industry, it's just gonna be a notification that, "Hey, this customer is quitting on you." This is just a notification. So this predictive forecasting, I would say the score was something that was missing. And as these LLMs got mature, a lot of platforms started building this piece. But there's one thing that we're building, is the memory graph. I'm not sure you're familiar with this concept that has recently been initiated by Tesla. The CTO, former CTO of Tesla, is building second brains, this concept and harnessing concept, and this is what we follow as our technology. There is one platform by the name of Agency built by ex-VP of Engineering HubSpot, ex-founder of Drift. So this guy is really smart, but we spoke with them, they're still missing on the whole picture of, let's say, you talk about one account with multi-user, like fifteen, twenty users in an account and technology segment, but they are near to renewal. You're not one hundred percent sure what are these business outcomes that they've shared during the sales call, during the handoff, have been fulfilled or they have taken action. Because a lot of times customers say like, "Hey, this is what our goals, some features, some initiatives, this is the outcomes we want from your product." And over time, during the course of three months, they are not validating themselves. And then you're taking it for granted, hey, they're good enough. They're using the platform. Their users are active. Their champions are active. But those relationships have been missing. The memory of that context of those business goals have not evolved from that point to three months down, which is the contextual layer we're working on as a product. And this is very hard engineering, that's why we took a lot of time. So this is the whole context that you're talking about too. Nobody is going to understand. It might be different. Even within your customers, there are customers that are perceiving value differently. You have, let's say, seven different modules. A lot of them they don't use, but there are some of them that's how their business outcomes are tied to. So how do you think this as a VP, this contextual intelligence brand layer for every segment, if not customer? This could be same for one, like in technology, there's gonna be some repetitive, standardized kind of playbooks, and if you break it down from onboarding to expansion, this entire life cycle, like you break it down success across onboarding and then adoption because this contributes to, of course, the churn or retention. I've done a personal survey with more than hundred and sixty founders in the past four years. I've done a lot of these interviews. So what we've found, more than thirty-six percent of the customers, they actually quit between the onboarding and adoption stage. This is big thing, right? So measuring success in components is super important, right? So that's where you need a lot of context because onboarding challenges are different to different segments. So how do you incorporate all of this as a VP? We all know that we have lived this pain a lot of times in my second role, back in 2017, 2018, big time. We've wasted a lot of revenue and top-line revenue on the expansion funnel that was pretty broken because we didn't have those signals. Andrew Loomis 18:32 Onboarding is critical, right? It's sort of like the newborn phase, right? The organs are very vulnerable, right? If anything goes wrong, onboarding is the time where the customer can make a decision, this is just not a fit, right? But if you can have a successful onboarding, your chances of having a lifelong customer are much greater. Nobody wants to rip a system out and replace it. Rip and replace is a pain for a reason because it takes a lot of time and effort, and there has to be compelling reason to want to do that. So actually, we at Sisense, I've kind of drifted back and forth. We had a dedicated onboarding function. But then I realized the more handoffs that you have within an organization, the more chance that you kind of hit that reset button and you introduce risk again, right? So now onboarding is back to being a CSM-owned responsibility, right? Getting that customer. And the reason is because you want to establish those outcomes early on, right? Your first conversation with a customer coming over from sales should be, "What are you expecting Sisense to accomplish for your organization? What impact do you..." Not, "Hey, I want ten dashboards and a chatbot in my application," right? It's, "Okay, well, what impact do you..." "Okay, great. Now that I know that, I can guide you on what you should be building or what you should be focusing on to achieve those outcomes," right? And it's also important to get multiple perspectives. I say this to people all the time. Sometimes, and this is a common trap in the customer success world, you find that person that you really vibe with, you really get along with, and they're your best friend at the customer, and they tell you everything that you want to hear. But that's just one person's perspective at the organization, right? Your first mission should be, "Okay, great. Let me make sure that I'm talking to two or three or four different people at that organization at different levels," right? Adil Saleh 20:42 Multi-stakeholder, yeah. Andrew Loomis 20:44 Multi-stakeholder. Yeah. If someone came to me, a CSM came to me and said, "Hey, I've got a great relationship with this customer, and now it's this one guy," I'm like, "You've already made a mistake because you're only talking to one person," right? So get to more people and figure out what the broad consensus is of the organization, not one person, right? Because I can tell you from experience, people leave organizations all the time, right? That person leaves, somebody else takes over. They don't understand why this person bought Sisense. You're educating them, and they're like, "Oh, that doesn't make sense. Nobody else has ever talked to me about this," right? When you have that multi-stakeholder perspective, now you're like, "Okay, I see what this organization is trying to do. I understand how we connect strategically to the bigger picture here." So then you can build your plan based on that, right? Now the CSM has this perspective. They can build a success plan that is addressing all of the stakeholders, not just one person, right? Adil Saleh 21:43 Yeah. And also, of course, a lot of these CSMs, I would say, and account managers, they are thinking about usage and product analytics, and they're so married to how they're interacting with our platforms, multi-modules, multiple users. That's fine. But when it comes to qualitative data analytics, like what discussions they had during the last meeting, the cadences, any follow-ups that they have, any signals that they dropped in the first, the context from the beginning is super important. Let's say you're talking about multi-stakeholder. There's gonna be, one would be, let's say for us, your VP or CCOs are the top-level stakeholder. So what is that top-level stakeholder talking or thinking about, some of the business goals or accomplishments they want out of this platform in the last recorded meeting, any notes, any email communication, any support. So those qualitative data is also being overlooked, or I would say for CSMs, account managers. What do you think? What's your viewpoint on this? I know, in a larger context. I know they'll be sitting in the moment at the meeting that they had three weeks back themselves, that's fine. But in a larger context, how they do their decision-making and follow-ups, is it support? Andrew Loomis 22:55 I don't know that it necessarily gets overlooked. I think that CSMs have a lot on their plate. Particularly here at Sisense, right? We're helping people. Sisense is not a workflow tool, right? It is something that actually needs to be engineered and implemented, integrated into a customer product. That takes a lot of time and effort. The CSM has to be on top of not just the customer, but internal resources, sometimes our partner network as well. So it's very easy to get lost in the details of checking boxes. Is this thing getting done? Is this thing getting done? Is this thing getting done? That's why it's important to have an executive sponsor program at a company where somebody who's not necessarily in the day-to-day, like I am not in the day-to-day of the customer. I come in maybe once a month or every couple months and take a look at, okay, how have we progressed since the last time? Is the customer in market, right? How many customers do they have using the platform, right? And I'm not mired in day-to-day operational. So I'm looking at, okay, is this thing generally moving in the right direction? And if so, that's a great sign, right? Then I come in and like, "Okay, I see that you're getting more customers on the platform. I see that usage has gone up. How has this impacted your market share? Have you won any deals from any competitors, right? Have you noticed higher customer satisfaction scores in your survey responses, right?" And those are the levels of discussions that executives can have with other executives because, again, it's very easy. Any product is gonna have implementation issues. You're gonna have support issues, and those can be very distracting. If that's what you talk about during every meeting, that's what's really gonna drive the sentiment. But if you talk about top-line metrics, then it's a healthier conversation around, "Okay, great. The business is healthy. We have some issues that we need to deal with on a product level, but your business is benefiting from our partnership, and that's what really matters to us," right? Adil Saleh 24:57 Yeah. Of course, living closer to the value that they are yielding out of the product, whether they know it or not, you should know it as a partner, I would say. So now thinking about, of course, you're at the VP role as CS, a lot of this has to go through expansion models. So what kind of expansion models have you laid out with this? A lot of these VPs are thinking about going slightly adjacent use cases of the product, working closely with the product team. "Hey, some of these, we can go multi-product. We can have some more modules that are going to help us expand this install base," with the founders, these conversations. So how are you positioning, and I'm sure analytics platform is sticking up, like it's so hard to get out of it, which is good news for post-sales. But again, at the same time, at some point, you're now thinking about increasing the lifetime value of the customer expansion model. What is that you guys are thinking about in the near future or have as yet? Andrew Loomis 25:56 Expansion's a very important motion. I will say this is where having a disciplined sales team is very important as well, right? You can only control so much based on the contract that is agreed upon during the sales process, right? So I know that years ago, Sisense used to offer these all-you-can-eat contracts, where basically if you spend enough money, you can just do unlimited users, unlimited storage, unlimited... Adil Saleh 26:30 Every other company that does it in the early days. Yeah. Andrew Loomis 26:32 Yeah. And it creates a lot of problems on the customer success side because, number one, you're gonna have more scaling issues, right? Number two, it becomes philosophical, like what is the value then for the customer, right? How do they know that they're getting good value out of their contract, right? Because is one hundred active users good value? Is one thousand active users good value? When you have a fixed amount that you're like, "Okay, this is our user base," and of that, sixty percent are using it, right? That's very easy to measure adoption. When you have something that is uncapped, it's like, okay, the only place to go is down because they have now figured out, "Okay, this is roughly what our needs are. We can scale down our contract now." So like I said, having good contracts matters in the sense of being able to expand and grow with customers. And you want contracts that make sense for both sides. So I'm not saying this selfishly for the technology partner. I'm saying this like you want contracts that make sense for both sides because we want our customers to grow. If our customers are growing, then that means they're getting additional revenue as well. So our motion for growing customers, we call it land and expand. It's not a new concept by any means. Get the customer in, figure out what is the way that they can get some immediate value. Don't oversell them too much, right? We want to say, "Okay, why don't we start with this pilot group of customers or this product," right? "And if we're successful, let's focus on getting into other products," right? So we actually push back and say, "No, you're buying too much right now. We need to prove this out before you buy more." Because you don't want to invite questions of, "I don't think we're getting what we imagined or what we thought we were going to get," right? So focus on a concrete win that you can get for that customer, keep the scope manageable, and deliver it, right? And then you just build on that use case after use case after use case, right? Naturally, the users will grow. They'll want to invest in more features. We have credits that customers can buy for AI functionality, right? All that stuff grows naturally as you drive adoption in the platform. Adil Saleh 29:00 Love it. I love the way you guys are approaching it because, of course, before we move onto the expansion, retention and, of course, value realization, utilization should be the first and foremost goal. So now thinking about time to value, what is the ideal time post-kickoff you guys have, talking about one module in a technology segment? Andrew Loomis 29:22 Sisense varies quite a bit. I will say, our goal, our target is always ninety days. Adil Saleh 29:28 The ideal goal. Andrew Loomis 29:29 Ninety days. Adil Saleh 29:30 Yeah, okay. Andrew Loomis 29:31 That's a pretty standard baseline that a lot of companies have. It's like, let's get them going, and if that first quarter's critical, let's get something, get the value trickling in by the time we hit the second quarter of the partnership, right? It's a great target. In practice, it doesn't always work out that way. Again, particularly for Sisense because we're integrating into other systems. Often these systems are going through software development life cycles, which can take several months. Sometimes we end up at a six-month mark. Sometimes it can go longer. Hopefully not. I would say if you're in that 90 to 180-day window, you're in pretty good shape with Sisense. So that's what we target, right? Because that's a great timeline to launch a new product into the market, right? Adil Saleh 30:18 Awesome. Yeah. No, it's a pretty ample amount of time. Yeah. You will think about Sisense while you're thinking about building a product, and you can get it all done in less than 180 days. It's pretty doable. So now thinking about the planning, I know the pricing and packaging, talk about eight months back for less than $500 a month plan, was it not big enough for a company? Because now there's so much noise, so much option, capabilities that they can build some of it internally to cut the cost and do more with less on the bandwidth side as well as the technology tech stack side. So now companies in the midsize, even this pricing sits more in the mid-market size. So how do you do all the education part, and how is this funnel going from the sales and acquisition perspective? Andrew Loomis 31:04 Yeah. So Sisense now has multiple ways that you can buy it. We have that PLG. You can go on the website, you can try it for free. If you're interested and you're listening to this podcast, you can go to Sisense website, sign up for a free trial, start using it. Now what I'll say is, we have those starter packages for those smaller companies that really just wanna experiment putting analytics in the product, kind of build something from the ground up. And then as you see traction with that, right? That's when you can buy the scale or enterprise-level packages, where now you've got a whole army of people behind you, right? You've got account managers, success managers, technical resources. Right now it's becoming, "All right, let's take this concept of a thing," right? "Let's get it into market. Let's get the adoption," right? So we appeal to people who are just experimenting with analytics and maybe small, emerging startups, right? Every day it feels like there's ten new AI startups, right? And they all wanna have some form of analytics. And all the way to, okay, we are a two hundred, three hundred, four hundred, five hundred-person company. Maybe we're a couple thousand people, right? But that's a different package, right, that requires maybe a few more bells and whistles, a lot more support, and that type of stuff. So we're trying to make sure that everyone has access to build analytics into their product, no matter what stage company you're at. Adil Saleh 32:38 No matter the size. And of course, you're willing to grow with them, right? Yeah. So that's why I see the pricing is pretty much designed for that too. So now for all the VPs struggling with the retention piece, and the churn is a big hit that they're getting, what is the one thing that you would like to share in terms of leveraging AI, building systems and processes that can help them mitigate churn? I'll be pretty vocal about it because it's one of the biggest things. A lot of companies are struggling, especially the companies that are in the first three years, pre-product market fit. They are going wide, and it's so hard to go wide these times, especially with so much of AI adoption on the other side of, and of course, the capabilities of AI costing them tokens and everything. So on average, a B2B SaaS in the first three years takes minimum six months to get the return on investment of the acquisition, so they need to retain the customer good enough. And then the second piece that is hitting them, the churn part as well, is they're not getting a lot of annual contracts because it's more about monthly or quarterly contracts with all of this usage-based, consumption-based pricing. So what is that one thing you would like to see and people would like to learn from Andrew that you have practically maybe applied or you're thinking of applying? Andrew Loomis 34:00 First off, you're not alone. I think you've made it clear that a lot of companies are struggling with churn right now. AI has a lot to do with that, right? I think that's one piece of it. The second piece is, at least in the analytics space, there's been a lot of commoditization. I saw a couple weeks ago, Claude can actually build a lot of dashboards and analytics, not meant for building into your product. So you have to make sure that you're also focusing on the right markets. One thing that Sisense has learned is we are not a great solution for every analytics use case, right? We used to try and satisfy people who wanted to just do Sisense internally. Great, that's one price point. Now, if you want to build analytics into your product and scale, that's a different price point, right? And so it's important for you to look at how your customers are using your product. What are the attributes of your customers that are renewing, expanding, versus the attributes of those who are churning? And we quickly identified, okay, the traditional BI is not a great fit for Sisense. It's highly commoditized. It's an area that no matter how many resources we pour into it, we're gonna see a lot of churn there simply because there are cheaper solutions on the market that can do eighty to ninety percent, if not more, right? So focus on where you differentiate, right? So how are we differentiating? We're AI powered, right? A lot of analytics products will say that, but I can truly say that we are not only AI powered, but we are the AI-powered embedded analytics platform that customers want to partner with, right? You're someone building an application and you want to introduce analytics, we are your partner, right? I would say take a look at your contracts, know who's paying a lot, and don't be afraid to proactively offer them a better contract, right? Because if you're thinking about the fact that they may be paying too much money for the contract that they're on, they're definitely thinking about it, right? And they may think, "Okay, well, my way of getting a better price is to go look at some competitors, evaluate solutions, and see how that stacks up against what Sisense is offering me." And when you let them do that, you're introducing the fact that, okay, they may find someone that does what they need, and they'll make the decision six months ahead of renewal, you're out the door. So if you identify that that risk is there early on, go to them and say, "Hey, we recognize your usage is not quite where it needs to be as far as what you're paying us. We wanna offer you a renegotiated rate." And it solves two problems. One, yeah, you're gonna take a little bit of a hit on churn, but it's better than losing the customer entirely, number one. Second, you're taking care of a renewal much earlier than you would have otherwise, right? And perhaps you even avoid them going to market and looking at other solutions. So those are some things I can recommend. You really have to have an understanding of, hey, who's paying me a lot of money, and who is actually getting the value that they're paying for, right? And if there's a big mismatch there, you have to figure out why. Maybe they're not an ideal customer, even though they're paying you a lot of money, and you just have to manage that from a contract perspective. So that would be some of what I've learned, what we've experienced here, is finding the market fit. Adil Saleh 37:37 I can see them. They're absolutely practical because this time, this point in time, it's so hard to go wide, so it's always good to know where, go narrow and know who you're solving for. And second is making sure that your contracts are absolutely market competitive. And market is changing so fast, so you can think of even quarterly contracts, bi-yearly contracts too, and thinking about how the other platforms in the market are doing the same capabilities at a lesser price, and that can prevent the churn. So I really appreciate you've been absolutely concrete into everything that you've shared, and wish you best of luck for all that you're taking. Number one thing that you've implemented in the VP, starting out this VP role, I know that you were Director of Customer Success prior to this too, but number one thing that has made the bigger impact into this organization at Sisense, taking only your initiative. Andrew Loomis 38:34 Yeah. So I would say one of the things that I picked up early on in my ten years, there was a bigger drift or need for product expertise, right? So in the customer success world, you have the revenue-focused, you have the engagement-focused, and then you have sort of the product-focused, right? And each customer base is gonna be different. And what I recognized early on is that we had a very revenue-focused team, which was lacking in product expertise on the CSM side, right? And that meant that CSMs were just kind of managing around renewals and not really talking much about the product. They were reliant on other people to have that conversation. So the first thing I said is, "I want product expertise at every level of this organization. I don't want you just talking to customers about contracts. That's how you erode trust. It's not how you build trust," right? So I said, "Okay, you're all gonna learn how to use the product, right? If you haven't before, this is now standard." And I have to say, I am very impressed. It's been a little bit over six months. I recently gave a presentation to our executive leadership team. It's impressive how quickly people can learn if you give them the right focus, right? So now our CSMs are doing roadmap conversations with every single customer. They're talking about how to use features, right? The dependency on these subject matter experts has sort of died down a little bit, and they're able to focus on more complex tasks. So that would be my number one thing. Identify there was a profile mismatch between our CSM team and what our customers needed, and we were able to address that. Adil Saleh 40:20 You as a CSM or any post-sales, even sales, you cannot have a business acumen without looking at the product and how, as a software, it's pinning down and making an impact and solving any problem. And this might have also helped you and your team in the expansion model too. When a CSM knows, hey, this is a new module that we're launching. Hey, this is how it's making an impact. This is the customer's side of it. This is the industry impact. And then you look at like, hey, this customer is same industry. Why not? Why don't I just bring this up in the next cadence or maybe a review, maybe during a success plan, keep it inclusive. So I love the way that you mentioned. And on the channel part, Andrew, as a leader, because no matter where you are, what team, what culture, people look up to you. If you're a leader, a VP or Head of, CCO or founder, people definitely look up to you. And if you make the right decision on the top line, bottom line follows. So your job and every leader's job is to just channel them to the right direction because they're not as close to the industry and how AI is moving and everything. They're not as close as you, right? So you're picking all of this, how it is you want, and then keep feeding them and channeling them towards the right. And this is half of the leadership, going first and challenging people and making people follow. So thank you very much for being that leader, Andrew. It was really nice talking to you, and I had so much to learn about Sisense, and you pretty much did the justice. Andrew Loomis 41:44 Appreciate it, and thank you for having me on. And look forward to seeing future episodes. I like learning from all the guests that you have on your podcast, so appreciate the opportunity. Adil Saleh 41:54 You are the one. You're one of those. Yeah. Thank you very much. Andrew Loomis 41:58 All right, take care. Outro 41:59 Thank you very much for listening to Across The Funnel. 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