Your Customer Data Isn't Actionable Yet: Here's Why

Speaker A: I call this part the Signal Conversation Framework. Um, and it's five pieces. And honestly, if I were building or encouraging people to build QBR decks or customer meeting decks, check, index, whatever frequency you're using it in, I would actually build five slides. And each of these slides are a piece. So first is observation. We've noticed blank and that's your data, right? You as the one who understands your product, your business, um, your other customers, you provide the context. This often happens when you know, this often happens when customers are looking to add this new feature. Impact Slide three, if this continues, positive or negative impact. Hey, I've noticed your usage is dropping and you're not getting the most out of the tool. If this continues, and this is where you can put some feeling behind it or some emphasis if this continues, I'm worried that by the time your renewal, you're not going to be getting the most out of the tool. Slide 4, if I'm building out this deck is validation. Is this true? Um, do you guys feel the same way? Sometimes? You'd be amazed. I've lost track of how many potential risk at risk churn accounts I've seen. Saved by a validating question. And then number five, which is maybe the most important in this conversation framework, to finish it is next step. Would it help to explore blank? Would it help to explore some new features we have that I think can solve this problem for you? Would it help to explore our different training and enable options? But all of that, literally every conversation a CSM could have could come down to the Signal Conversation framework if they have data behind.

Speaker B: Hello everyone. Welcome to another episode of Customer Success Talks. Real Challenges, Experts Advice. The podcast dedicated to helping those transitioning into customer success and early career customer success managers. I'm, um, your host, Byron Toruno. Just like you, I'm still learning about this amazing world of customer success. And today we will be touching on one of the episodes that I have been wanting to record for such a long time. But into now we have the right guest who will be touching about data. So what we're going to be doing here is that we're going to break it down into the three pieces that I consider that are important for when it comes to data. The first one is analyzing the data and then it's about presenting, which includes presenting it visually to make it easy to digest, but also the story behind that to make it easy for people to understand from the start to the to the end and the outcomes of that. So it's going to be a really interesting topic. About, um, data, which sometimes it can be really intimidating, especially if one is new at the organization and maybe don't know exactly yet what value the product brings. And so it's a lot of research, but it could be also a mess. So there are so many challenges behind this. And without data, it's hard to be actually accurate and it's hard to show that value that we bring to the customers. So all of this is what we will be talking about today. And our guest is a guest. That is not the first time who has been here with us. It's actually the second episode that we record. The first one was about how to scale approaches within our portfolio. Big portfolio of customers that we have at csm. Amazing episode. You will find it in the description. But today we have him again. So welcome and let me just let everyone know who are, uh, you a little bit. So Danny Burda, someone who started his career in the nonprofit world, and then he noticed that this field, this role, this something in the far away called customer success management, and just realized that he was a natural fit. And that's how, uh, as well he ended up in customer success with working with large companies in the world, supporting strategic initiatives in the global impact side of things. He served as global head of customer success and today is the chief customer officer, sorry, at River Consultancy Group. So, Danny, again, welcome to customer success talks and thank you again for your time.

Speaker A: Glad to be here, Baron. Thanks for, thanks for having me back and thanks for letting me come back to talk about this topic.

Speaker B: Can you tell everyone, uh, a little bit more about River Consultancy Group?

Speaker A: Yeah, absolutely. So river is. Myself and my partner James founded, and we really both came out of the customer success world post sales revenue, however you want to call it these days. And we built river originally just doing kind of classic coaching and consulting and things like that. But as time grew, we really started to see a clear challenge occurring for SaaS companies, software companies, AI companies, uh, around how do you retain customers, how do you grow? Uh, the model of a few years ago where just get more investors, get more money, get new market, all that was starting to collapse. And so we really started to have to focus on, okay, what are the practices, the skills, what are the operational things you can do to actually make go to market work and to make revenue work? Because what worked a year or two ago doesn't work now. And so, yeah, we go into different companies of, uh, various sizes from kind of a few million all the way up, uh, well over a hundred million. And we work in different ways from fractional roles to our revenue strategy lab program to help them really fine tune from end to end everything about the revenue engine. But we also do a lot of trainings and opportunities to train teams in post sales, classic customer success, things like that. On how to be a bit more revenue oriented, which I think is what we're going to talk about a little bit today, uh, around how you can use data and signals to do that as a csm.

Speaker B: Yeah, that sounds so interesting how many things happens in the organizations and then if we go one step bigger is the go to market strategy. So it sounds like fun but it could be stressful I guess.

Speaker A: Yeah, it's challenging. No two companies are exactly the same. But what we found is when you align around your business's revenue driving okrs, uh, objective, key results and what actually matters to your business, where you need to go once you get your, what we would call revenue teams aligned, that's sales, customer, uh, success, marketing, sometimes product, sometimes support, you know, really, really working together towards those goals and understanding how they can actually kind of support each other and how you can get some of the dream states of you know, secular customers, you know, renewing customers that grow with each renewal, customers that actually bring into customer led growth or provide information to product for product led growth. Once you kind of put those systems into place you see a pretty solid immediate bump in your revenue because we call it kind of the lost or leaking ARR starts to patch up because you're not losing it in handovers. That's actually again where data makes a difference, um, and signals make a huge difference. But it also then empowers those teams to start asking questions like well what else can we do? How can we push this further? And you get revenue and growth no longer becomes this kind of executive leadership strategy. It becomes operational at the ground level and the execution level and that's when is really cool to see.

Speaker B: Yeah and by the way everyone listening, all the information about River Consultancy Group and Danny will be in the description. So if you're really curious to see how they could help you and help your organization, just go and check out the links and reach out 100% recommend it. And I have, have uh, met your partner as well and um, also you in person people that I will recommend easy to talk to as well. So go ahead and take a look at the information and all of this that you're talking about and what you have seen in your experience. Danny, where are, where do you think that companies are messing up when it comes to data? What are the biggest issues that you're encountering.

Speaker A: Yeah, so I, I think the two biggest issues that come up is one, um, you know, it's the old adage, everyone knows it, but garbage in and garbage out.

Speaker B: All right.

Speaker A: You know, this was, this was a common phrase kind of when you looked at the big company salesforces or Hubspots, you know, CRMs where just everybody was putting in their own data and no one was really owning that side of things. And then you go and try to use that data and it's, it's impossible. You know, there's no real guided source of truth. And, and that same practice has moved into the CSPs, the um, customer IO, the, the Gainsite of the world. You know, kind of those platforms anywhere where you can put in data. If you don't have this kind of clear initial setup of governance and boundaries around what data, who puts the data in, who, who's checking the health of that data, that becomes kind of problem A. Uh, but problem B is even if that data is great and, and, and right, what we find is most people in post sales, uh, and actually in sales don't really know how to use that data to create anything out of it. So, so we've started to, to kind of differentiate and say you have data and data informs signals. Kind of think of it, think of it almost as like you're looking at the, the old school radar, you know, like the, the little green dot with the, the little green lines around it and you get the little. And, and now, uh, as that works, you start to put together a signal and you say, oh, okay, uh, you know, we can, we can see the ship moving across radar or if you think of, you know, like the idea of, of uh, a lighthouse sitting on a coast, you know, as it goes around, it's sending the signal on repeat, you know, saying, hey, warning rocks ahead here, things like that. Well, we know these signals exist to go back to the radar option, you know, you know, you, you know, an opportunity could be moving closer with a customer. You could see different, different things coming together. But when you track those points repeatedly and see, see certain things happen over and over again, they're no longer just a blip on the screen, they're, they're a path of blips. And those path of blips can actually tell you, hey, this is a really strong signal for either something good or something bad. Um, and, and so that's kind of where, yeah, as I mentioned, but when we were talking before one of the trainings, we do, which is our revenue enablement for post sales teams. The second session we do is all about signals and, and why they matter. Because risk is never, should never be a complete surprise. If it is, it's because somebody was holding on to sign signals and not sharing customer. If a customer's churning, odds are you can trace that path back. You know, there's always surprises. There's, there's, you know, exceptions to every rule, but I would say with fairly high regularity. You know, if a customer's turning months in advance, um, if a customer's looks like a solid opportunity to grow or upsell again, the people interacting with that customer tend to know these things before it becomes an opportunity in Salesforce. Um, and, and really what we found is, you know, for existing customer bases, it's your post sales teams that see that data first. But the problem, not that they can access that data, it's that they, they often don't have the skills or uh, the practices to interpret that data.

Speaker B: Yeah, yeah, that's actually a good side of way because you, you touch on so many important things. But the one that I really want to highlight is like what do we do with the data? So the data is here, right? Everyone who revops created this amazing dashboard is so visually beautiful for us, it's easy to download but then like how to start even analyzing all of that data, uh, for even for us ourselves to know what to bring to the table for the customer.

Speaker A: So I like to tackle that in what I call the signal driven post sales model. Um, and it's very simple. You're going from signals to insight to conversation to action. So again, think of data as a single point on the radar signal. Is that point repeating over and over again or multiple points in a cluster? You know, things like that. Um, create a signal. So once you have a signal you can say hey, this is what we're observing. You know, and like I said, this can be good or bad signals. Signals can either say hey, go this way for you know, safe passage or they can say danger rocks ahead. We don't need to separate out necessarily right now. But, but a signal is going to tell you what we observe. Hey, we observe that this customer is showing all the signs of a, ah, growing customer. They're maxing out their usage. They're constantly coming to us with ideas or saying hey, how do we come work around or how do we do this? So they're really looking for ways to expand the tooling. Um, you know, flip side of that, hey, we've noticed this Customer has gone completely, um, you know, offline. They're not responding, they're not doing that. You know, either way, those are a signal. So that's what we observe. The insight is, what does that mean again? Could be good, could be bad. Could, um, be something telling you, hey, I think there's room to grow this customer. Or it could be, hey, I think we need to proactively do something or we will lose this customer. Um, but really where I think the skills grow or the opportunity grows is in conversation and action. So the conversation side is saying, how do we validate it? If you're, if you're a CSM and you see these signals and they've given you this tip off that something, you know is possibly going to happen with the customer, how do you respond to that? And you respond to that, you know, not with a gut feeling. So, like, if, if you're my customer and I say, Baron, it kind of feels to me like you're not very, uh, into the product. You know, I'm talking feelings, I'm talking warm and fuzzies. But if I come to you and I say, hey, Baron, we've noticed that there's been a 15% dip in your usage over the past two months. Do you, do you know why this is happening? Or can we have a conversation about kind of what's going on there? I'd love to know, is this a temporary thing? Did something happen, uh, within the organization that we can support with? You know, you turn that conversation around and then the action is you're either driving towards retention, risk reduction, saving that customer because you're addressing a problem before it becomes a bigger problem, or you're actually driving expansion. Hey, hey, Baron, we actually noticed that there's been a 50% increase in usage over the last two months. Can you fill us in? Why, why has this been going on? What's going on in, in the company that kind of drives this? So, so again, post sales, signal, insight,

Speaker B: conversation, action, just like that. But I think that it also touch on really the part of the confidence, the numbers give you the confidence to say, this is what is happening. It's not that I think it's like, is the confidence of coming and giving you the authority during the call and saying, this is what happening, and this is what we can do as well. So, uh, that's how I feel when you're talking and saying you're using the word instead of I feel towards more concrete. What we are seeing here.

Speaker A: Yeah, the phrase I see or we see or we've observed is so much more powerful than I feel when you're talking to the customers. And that's why getting that foundational layer, that first layer of data right matters. And I've seen this countless times where actually companies, customer success teams will protect and guard their data and not allow it. They might keep it in their plant hat or their gainsight, um, or in a separate HubSpot instance so that it doesn't get distorted so that they can keep tracking the right data. And you know, because as soon as that data becomes corrupted, you don't have that confidence to say I see or I observe. And so this is, yeah, customer data, usage data. Um, actually we kind of break it down into four categories usually. So you can see product and usage which we just kind of referred to in the last example, you know, goes up, goes down, things like that. Um, there's commercial and contract signals. You know, I've all seen a customer's asking and saying hey, what would it look like for us to add 200 licenses? Or how many more AI credits can. Well that's a clear sign they're thinking about doing something big. Um, or if they're saying hey, we're looking, we um, just kind of came into um, a cash flow, could we actually look at locking in a price for X number of years if we did a longer contract? So contract and commercial signals, um, there's operational and support signals. I often say support is the first line defense in the trenches with customers like more often than not they see signals and we tend to think oh yeah, they see the problems. That's not always true. They also see the questions, they see the ideas, they see the insights way, way before we do. Sometimes they get signal. They're the, they're the, they are the lighthouse at the front. So like I was, I was actually talking um, with ah, with a customer of ours that I was doing this training for last week and they brought up their support team, they said oh yeah, we actually get questions about the product all the time. And they're not support tickets, they're not bugs, they're not issues, they're just going hey, can we do this? Or is there a feature that does this because people just don't know who else to turn to. And I said well what do you do with those? And they kind of paused and they uh, said well usually we, we tell them to talk to their csm. And I said that's fantastic, that's the right thing. And I said but what happens if you suddenly bring that CSM in Like don't let the, don't let the data drop. You know, add them to the ticket, let them read it, let them see who's asking the question, Give them the data from your support side. You know, there's also other support signals. Obviously, if a customer's been really good and happy with you and suddenly there's 50 tickets being produced about issues and bugs and features, well, suddenly they're not happy, you know, uh, or they're struggling with the product, it's time to re engage. On the flip side, yeah, if there's a bunch of tickets open, but they're all usage questions or adoption questions or feature questions, like it's time to engage and take control of that conversation. And then of course, the last set of signals that we tend to cluster together would be like organizational and strategic signals. Um, again, these can be growth, uh, signals, they can be risk signals. If your key stakeholders leaving the company or leaves the company, where does that leave your product? Uh, if all of a sudden at a higher up level, the company's hiring a new CIO or CTO or CFO or CRO, you know, depending on your product space, how, how that person feels about your product? Uh, you know, are they, you know, are they a die hard. If you're, if you're selling, uh, AWS and they're a diehard Azure fan, like, how do you get in front of that conversation from a retention standpoint and say, hey, let me show you how our thing built on AWS drives this and this. And we've been working with you guys for this time, like bring in that conversation and that history, but also hit to the data points. Here's how you've grown with us. Different things like that. So again, kind of four common signal categories. I'm sure for individual companies they might find some that fall outside of those. But I would say if you're looking into those four areas, then what's nice is with a lot of those you can get the data and you can control that data.

Speaker B: Interesting, because when you started with the analogy, uh, of the radar, and then there are like different points as you were talking about those categories, I was like, huh, so there might be several points in the radar at the same time, which can make it so loud as well. It's like, okay, then which one do I used to focus on? Which one should I actually pay attention to? So now that we have those categories, or someone creates their own categories based on knowing how to show the value to the customer, what is, what are the next steps in Terms of which data or which category to actually focus on. Mhm.

Speaker A: Yeah. And I mean that's a, it's a great question. I'm going to give the slightly consultant answer of it very much depends, obviously. Um, but I think usually I would say this is where you would know your data and you would know your tool and you would know your products and you would know your general customer base. Um, and again, this is expanding that idea of signals and going, I'm not just looking at one customer, I'm looking at. Back to our conversation from a couple months ago. If you're in that kind of, um, you have scaled CS or SMB CS1 to many CS, you can look at patterns or dots on the radar from dozens or even hundreds of customers. And so if you can say, okay, I know I'm in, let's say you're in that space and you go, I know that really good usage in this customer segment looks like X. You know, you see it, it's repeated over and over again. Um, you know, it doesn't even have to be your customers. It could be your enterprise custom customers or maybe give them a name like ninjas or titans, um, or champions or superhero customers. Whatever you call, they might give you a really good indication for what usage looks like. Or um, you know, you can, you could run and you know, you can look at data for, hey, of all of our customers that have um, expanded at their renewal, you know, were there common things. And then you can use that to kind of weed out the noise and say, okay, I'm not, I'm not superhuman. I don't have eight arms and 10 sets of eyeballs to look at everything all at once. You can just say, I see this as a really good indicator of um, of growth.

Speaker B: Yeah.

Speaker A: So I'm going to take that and I'm going to look at that and kind of use that as the net around my signals that I have within my customer base and say who fits into that and who doesn't fit into that? Uh, and you can kind of go from there.

Speaker B: Oh, sorry, yeah, sorry, there was a delay. So I think also that a lot of the intention, like even knowing what we want to show is also one of those filters. Isn't it like the intention of us, like what do we want to show? What do we. Because I think it's like the customer's perspective that we have to keep in mind. But also we have to save our perspective as CSM that is representing a company or platform. So I think that the intention of okay, do we want to focus on the expansion? Do we want to focus on a churn signal? Do we want to focus on areas of improvements or do we want to focus on a trend? Do you think that's, that will be a good way to start to filter that as well?

Speaker A: Yeah, absolutely. I mean again, you can't do everything all at once. Uh, especially if you haven't been doing it before. Um, if you're a new CSM or a junior CSM or a new CS manager, like I always always say, pick one area to improve. Don't try to improve everything a little bit, you know, because business moves too fast and by the time you make that little improvement, new product, new feature, new customers, uh, new team, you know, there's, there's so many factors like really drill down and say we are going to work on X and we are going to make sure we understand the data behind X very deeply and very intimately. And I always, always say this when I'm, when I'm doing training because at the end of the day I'm some guy who's coming from the outside in. No one knows the products, you know, better than the teams. No one knows the uh, the possibilities better than the team. Nobody knows the other customers in the space better than the team. The teams usually will tell you what they would love to see. And in fact I encourage us often when I'm working with companies and we start talking about these data and signals and they go, well we don't have the dashboards, we don't have table. We haven't set up the HubSpot dashboards yet. We haven't. I said great, like that is the best place to start is going. We know we need these, but we don't have them set up yet. Bring in your um, might be rev Ops, might be CSOps, whoever the team that's going to be in charge of these dashboards and all those things are bring them in to meet with the customer success managers or the post sales teams. Bring in support and say hey, support. What can you guys Track? Use uh, Jira Service Management or Zendesk or uh, ServiceNow. Those different, they have dashboards and they have reports and say hey, can we see what you're able to track? Can we see how many tickets are raised per customer over time and when and how quickly we're responding to them. You can tackle any number of you determine what signals you're going to try and look for or try and understand and then you can work with your ops teams to really get good reporting and data points within there and then you move forward. And again, I can give general examples, I can give things that most companies use, but more often than not, if you put all of your customer success managers and support managers and services team in a, uh, room and said, hey, what should we be looking for? What are the growth signs? What are the trend signs?

Speaker B: That's the conversation probably tell you.

Speaker A: Yeah, yeah. And I think um, a caution I want to add at this point too though is that signals are not conclusions. Signals are the start for conversation and conversation is the start for action. So just because you have signals that are low usage doesn't mean that customer is going to churn. On the flip side, just because a customer has super high usage doesn't mean they're going to expand. Just because a customer creates a ton of complaints or a ton of tickets doesn't mean they're dissatisfied. You know, I always like to joke, I say, has anyone worked with a German customer before? Uh, because everyone who's been in any customer facing role knows Germans like complain as their intro. Like if you're talking to a British person, they'll start talking about the weather. You know, when you get on the call, if you're talking to a German person, they're going to say, oh, this was bad this week, this broke, this doesn't work, I'm, I don't like this feature, you know, and that. And then they'll go, oh, and by the way, how are your kids and what's going on and all these other things. So you just have to realize that just because something says it, that is your footstep into a conversation, not a conclusion.

Speaker B: What happens at the point where we now gather the data? We know that we're not going to show three categories or not three signals, but we're going to just focus on one. And we have that data, we know the data and we have already digested. But now what is the story behind it? Because I used to create presentations before even thinking about this story. I used to create presentations without even having the intention or the awareness of thinking. What am I going to actually present? So uh, at the end it was not making sense. These slides with what I really wanted to talk. So how, uh, because also storytelling is a skill. What have you, what recommendations or what have you seen CSM doing in terms of I have the data, but now what and what story I want to tell?

Speaker A: Yeah, no, perfect, perfect segue actually, because I call this part the Signal Conversation framework. Um, and it's five pieces. And honestly, if I were building or encouraging people to build, uh, QBR decks or customer meeting decks, check, index, whatever, whatever frequency you're using it in. I would actually build five slides and each of these slides are a piece. So first is observation. We've noticed blank. And that's your data, right? Um, that's your, that's. We've noticed usage. We've noticed number of support tickets. We've noticed questions, um, about, you know, new features or growth, whatever it is, we've noticed blank. And then you as the one who understands your product, your business, your um, other customers, you provide the context. This often happens when, you know, this often happens when customers are looking to add this new feature. This often happens when customers maybe have had some changes internally and their teams need to be kind of re enabled. This often happens when customers are looking for workarounds for a manual process to have whatever it is. Impact, slide 3. If this continues, positive or negative impact. Hey, I've noticed your usage is dropping and you're not getting the most out of the tool. If this continues, and this is where you can put some feeling behind it or some emphasis. If this continues, I'm worried that by the time your renewal, you're not going to be getting the most out of the tool. I'd like to stop that before we get to that point and make sure we put you back on the right path. Or I've noticed, you know, or if this continues, hey, if you guys continue looking for these things, we could actually take this workaround that you're doing and talk to a product team and see if we can build this into the future product roadmap. See both of those impacts. Um, you know, I'm saying if this continues, we can do something proactive to stop it, um, or proactive to, to build off of it. And the beautiful part about impact is this ties into value based selling, which is something we're big fans of. River. But it also, it turns CSM reactive to proactive. You know, neither of those things I said were reactive. Oh my gosh. Your, your usage has dropped significantly. Uh, how do we uh, save this reactive? We've noticed that your usage has dropped. If this continues, I worry that you're not going to be getting everything out of our tool that you could be. I'd like to address this by doing this or this or this or hey, you know, am I right in assuming this is what happened? If this continues, I think this is where we're going to end up. How do we change that Together now, Proactive statements, slide 4. If I'm building out this deck is validation. Is this true? Um, do you guys feel the same way sometimes? You'd be amazed. I've lost track of how many potential risk at risk churn accounts I've seen. Saved by a validating question. Hey, we've noticed usage has dropped. We've noticed people aren't as engaged with the platform as they used to be. It seems like maybe they're just not as many people know how to use it or maybe they're just comfortable with the basic features. Is this something true on your side? Or this is a great time to throw feelings in. Is this what you feel? Or better yet, is this what you're seeing on your side from the data as well? And then you're giving the customer a chance to respond? Yeah, absolutely. That's how we're seeing it. Or no, no, no. Usage just dropped we off boarded a team. We're waiting to onboard the next team. Usage is going to spike again in a month when I'm done with that team and then I can still be proactive. Oh, can I provide you some new enablement videos? Can I join in and help that team get on board and you know, different conversations like that. And then number five, which is maybe the most important in this conversation framework to finish it is next step. Would it help to explore blank. Would it help to explore some new features we have that I think can solve this problem for you? Would it help to explore our different training and enable options? Would it help to explore our services team and bringing them in to help, uh, with some of these custom integrations so that you're not doing this manual work. But all of that, literally every conversation a CSM could have could come down to the signal conversation framework if they have data behind them.

Speaker B: Wow, you just gave these steps on how to create this story.

Speaker A: Yeah, and that's the thing. Like, I love storytelling. My, my master's thesis was on storytelling. But what I found to be the most useful is stories that people can relate to. And ultimately the things we relate to are data points. It takes all the romance out of a story to call it that, but it's true. When you think about your favorite story, favorite fantasy story, Sci Fi story, star, uh, Wars, Star Trek, Harry Potter, whatever you're looking at, the things that connect with you are the points along the way that make it a good story for you. And those are points just like data points. They're emotional points, but they're still little blips on that radar. Saying this is why I like the, this story. And so our customers who are in business, sure, they love a bit of, bit of fantasy and like to imagine, uh, you're making them the hero of their company by using your tool. That's usually how things might get sold sometimes. But at the end of the day, they want the points along the way and they want that data to say, hey, this is how you're doing. We see, this is really. Well, here's where we can see potential for improvement. Um, and then you get to step in and be the Gandalf of this journey and say, let me guide you there, let me help you with that.

Speaker B: You're telling a story now.

Speaker A: Yeah, exactly. So that's the thing is data leads to signals, signals lead to insights, insights lead to conversation, conversation leads to action. And that action is the next chapter of the story. And by following these type of frameworks, you get to write it with them, which is a very cool place to be.

Speaker B: And Denny, like from these five points, I'm just gonna recap them really quick. Observation, context, impact, validation. Next steps, which are the, which is the one step that you have seen CSMs messing up the most?

Speaker A: Observation.

Speaker B: Observation.

Speaker A: Yeah, um, yeah, probably I would say

Speaker B: for me, sorry for me it's observation. And also I think next steps.

Speaker A: I think that's where our first training in this training that we do for post sales teams is value based selling. And we start there to make people start to think about next steps. Hey, how do you rewire your brain to always be thinking about, you know, what is the next step? What does growth look like? But I would agree often it's very, you know, it feels scary to be the person in the driver's seat and the person proposing that next step. If you're in a good place with your, your customers, if you're that kind of holy grail, trusted advisor, customer success manager, they are going to and saying, hey, because you walk through the first four steps, what do we do now? It becomes a lot more natural. So I would actually say for me, observation's always the first because, you know, often we're scared to call out the data, especially when we think it's negative. That's why you bring it into context and impact. But, um, context is maybe the second one. If you're new as a csm, you don't have as much context. But I'd say what I find is like, again, take the data, you know, take the data, you understand, Take the pieces, you know, and just go through these five steps. Um, you know, and the good news is the news is customers churn all the time, sometimes for no reason at all. So don't be afraid to try, don't be afraid to practice this framework. Like if you're, if you're a customer, and I say, hey, Bayron, um, I'd really like to have this conversation with you. And I walk you through an observation, the context for it, what I think the impact is. I try to validate it with you, and I talk about next steps. What is the absolute worst that's going to happen. You say, thanks, we're not interested. Yeah, great. I practice that skill. I take it to the next. Bayron number two, I've refined my skills a little bit. Maybe I focus a bit more on making sure I, um, clarify my points. You might be. Oh, that's really interesting. Um, I don't think we need to address that right now. No problem. Thanks for your time. I move on to Bayron number three. I've refined this process, I've practiced it. It becomes just like a salesperson with their sales pitch. And I walk you through those with clarity and you go, wow, this person understands us and our business and what's going on. And they understand their tools. Yeah, I'm interested in that next step. And then all of a sudden it becomes repeat, you know, rinse and repeat with each customer.

Speaker B: Yeah, I love that. And then you gain more confidence as well then I love that because you gave us a clarity into. All right, so the data collection part, there are different signals that you categorize and you segment on, you know, which one to action on. Then now it's like, all right, now you have the data, you give the observation to the guests, I mean, to the customer. You go point by point. So the story is there, the data is there. But how the hell am I going to go and present this on a Google Slide, for example, or a PowerPoint? Because then I need to move from numbers into visual, easy to digest numbers. And at least for me, that's a struggle that I have most of the times. Now there's cool tools like AI. The Google Google has suite have their own integrated AI within Google Slides. That is could be helpful, but it's still not perfect. Now that we have this story, how do we make all of this data easy for them to digest and not have that famous data paralysis?

Speaker A: Mhm. Yeah. And again, I kind of call it a, uh, middle out approach. Data doesn't retain customers. Like, you know, there's companies with terabytes, you know, I don't know, it's bigger than A terabyte, a quantabyte of data. And it does nothing. It sits there. I call them data graveyards. Um, you know, um, data doesn't retain customers. It's conversations that do. And that's why post sales teams matter. But using those signals tells you where to start. Um, and so again, if you feel like you're sitting in a company or a role and you go, oh, I don't know how good our data is, or, I don't know. But, um, two options. One, you know, you can call it out and say, hey, guys, I'm not sure I have. You can say something like, I don't have high confidence in this data set. Can we review it? Can we improve it? And again, you know, huh. Most CSMs book a business. Twenty customers, fifty customers, a hundred customers. Tackling that as a data cleanup project in and of itself is, is worthwhile. So start, clean up the data. Have confidence in the data. Whatever the data is, whatever you're looking for, you have to be confident in data. Because if you're not confident in that data, it trickles on and moves on. I mean, I'm sure you've seen it. If you ever have been on the other side of a CSM conversation or a sales conversation, you know, uh, pm, product manager conversation, and you ask a question and know the answer for it, you can always tell if the,

Speaker B: yeah, I don't know what happened. You can always tell, yeah, you can

Speaker A: always tell, um, if the person on the other line, other side isn't confident with their answer. One of the absolute worst lessons I was taught very early on as a CSM, this was 11, 12 years ago, is I had a, uh, I had our founder of our company say, you cannot say I don't know. That was what he said to me. I was the first csm. And he goes, he goes, never say I don't know. He goes, they'll eat you alive. And so I got in so much trouble. We had a very tough customer and they would abuse that, that specific thing over and over again. And if you gave the wrong answer, they would literally go and check it. And if you gave the wrong answer, they would go seek a discount on their service with the CEO. And finally I, you know, and we ended up doing tons of stuff for free, bending over backwards. I was working late night, finally went to the CEO and I said, look, something's gotta change. And what I have to start saying is, no, and I don't know. But. And so, you know, and, and, and so I started doing that. So so that's the other thing too. I would maybe give, give to this audience is it's okay to say, I don't know, if you, if you come with a piece of data and they say, that's great. What about this? You know, I'm not sure about that. I haven't looked into that yet, or I haven't had the chance to explore that, or I'm not sure we have those insights. Let me go back and look. Um, and then just make sure you follow up. I've had great customer relationships with customers over the years where I don't know if I've ever given them solid data because we didn't have it. But the fact that they knew I would go and I would check and I would look and I would raise that that data wasn't available, at least gave them peace of mind. They'd say, oh, I wish we could see that, or I wish we knew that. And then sometimes weeks later, months later, years later, we got the dashboard that could show it, or we got, uh, analytics within our tool that could show it. And when I can bring that back to them increases confidence in the conversation.

Speaker B: So what about Google Slides? So you're not a fan of Google Slides? Or like, is that, is that, is not that important as the conversation and translation of the data?

Speaker A: Yeah, so, I mean, I, I would say, uh, I'm agnostic on slides.

Speaker B: All right?

Speaker A: No one, no one wants to sit through a presentation where you're just reading 50 slides at em, right? Like, I mean, especially nightmare. Yeah, nightmare QBR scenario. You come in and they just start showing you slides of data. Something I actually make people practice in these workshops. I say, great, you now need to explain this back to me or you need to do, you know, this, this, you know, kind of, uh, signal conversation framework. And I said, you can't use slides and you can't show me the data. You have to explain it, you have to conversate it. Now that doesn't mean I'm against it. It just means it should never be kind of your fallback crutch of, okay, well, I put the data on the slides and I'm going to go, or I've, I've compiled the data and I'm going to show it to them. It's up to you sometimes to serve. Um, again, that's that, uh, that context and impact side of what I mean is that's the interpretation, that's the, the, the conversation. And then, you know, the validation and the next step is the storytelling. So, so if you Think of that way, observation of data. Put that in your slides. Great. But you should be able to, to tell me, you know, the context and the impact of that data without being dependent on, you know, your Google document.

Speaker B: Yeah. Because sometimes we have to share our screen and present the data there as well. Of course they destroy before the call, but not always have to be in slide.

Speaker A: And again, I think there's something about that idea of confidence and um, security of if you're presenting to me and you're reading the slides and it looks like you're reading those slides for the first time, how much do I trust you? Whereas if you've looked at those, that data, you've processed that data and then you're talking to me and you go. And I go, oh, well, what does that look like in the, you know, do you have a report? And go, oh yeah, yeah, I have the report right here. Or oh yeah, I put it together in the stack. I was just having a conversation with you. And then you show them. Some people will always like the slides and the data more like they want that, they want to check the box, that's fine. But for most people, I think the fact that you can, if you can, if you can give me that entire conversation framework without showing me the slides and then send me the slides as follow up, you're just backing up your.

Speaker B: Never thought about that, Danny. I was so stressed in the presentation. I mean, sometimes it's needed because maybe it's one year review, maybe the customer needs to share that internally. But it seems the way that you're expressing this is like first focus on the first two points that we touch about, which is data collection and then the storytelling and also, and then jumping into. All right, all of these conclusions from. For these five steps. Interesting. Never thought about that. So thank you for bringing clarity. And unfortunately, it's time to start wrapping up today's episode. Two questions. The first one, anything that we're missing, something that you would love to tell someone who is struggling right now with data, with collecting data, presenting it in general.

Speaker A: Um, I think I'd go back to something I said earlier, which is start small, start with focus. One data point, one cluster of data points, one group of customers. Don't try, um, don't try and change the whole world or the whole company. Um, off the bat, take something you can pick up and you can manage and work with that, even if it's just your customer data. Um, getting to that clarity and that source of truth is so valuable. Even if all you've done is figure out how to do that. And that can be repeated. You've done a huge service to your company. So I would say start small, pinpoint what you think you can impact, or at least investigate. And I think, you know, the smaller the company, the easier it is to kind of own that initiative and take it on. When you're jumping into Microsoft or Oracle or those things, it might feel daunting, but you can do it there too. You can kind of say, hey, I've noticed this, or I've, I've seen this. Things like that. And much like the conversation, uh, much like the conversation you'd have with your customer, you can take the Signal Conversation framework and bring it internally and say, hey, I've noticed that our data isn't very good. This is often happens when there's a lot of sources feeding in and no one's owning it. If this continues, we're going to have a really hard time tracking the things that impact, churn and growth. You know, Is that how you feel about it as well? Manager, boss, rev, ops person, sales counterpart, whoever you're talking to. And would it help if we, if, uh, we tackle this together? You've just done the Signal Conversation framework internally, but it works, it works in multiple contexts.

Speaker B: Thank you, Danny. Thank you very much for your time and your insights and where can people find you?

Speaker A: Yeah, so easy to find on LinkedIn. It's just, you know, LinkedIn.com backspace in backspace. Danny, Berta, uh, you can reach me there. Shoot me a dm. Always happy to chat and help people out. Also, if you go to riverconsultancygroup.co.uk you can find the different kind of offerings and services we do and reach out to us that way as well.

Speaker B: Perfect. So not a better way to close today's episode to know where to find you to start from today or tomorrow. Depends on the time where you, uh, the time that you're listening this episode to take the data to the next level and show the impact and the value. Thank you so much, Denny. And like I always say, remember, keep learning, keep growing, and let's keep improving the world of customer success. Until next time.

Speaker A: All right, thanks, Ferris.