Putting The 'Success' Back In: Customer Success

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Speaker 2: Welcome to the GTM Pro Podcast, your essential 2 - > audio resource for mastering go-to-market discussions in the 3 - > boardroom. 4 - > Here we share insights for revenue leaders at B2B software 5 - > and services companies, especially those with less than 6 - > $50 million in revenue. 7 - > Why? 8 - > Because the challenges faced by companies of this size are 9 - > unique. 10 - > They are too big to be small and too small to be big. 11 - > This dynamic pushes revenue leaders into executive 12 - > leadership without a lot of help or support. 13 - > We are here to provide that support. 14 - > Your journey to boardroom excellence starts now. 15 - > All right, here we are. 16 - > We took a week off, so kind of a crazy January for everybody 17 - > it's holiday and then back in. 18 - > So we're back at it here for GTM Pros. 19 - > We are going to stay on the same theme of customer success, 20 - > however, because there's a lot of change around that and, 21 - > frankly, we're doing a lot of work on it ourselves and just 22 - > how we rethink that in this new AI world and what we can do 23 - > about it. 24 - > So, andy, you were kind enough to kind of frame up a discussion 25 - > for us. 26 - > You want to kind of kick that off, and then we'll just dive 27 - > right in. 28 - >

Speaker 1: Sure a discussion for us. 29 - > You want to kind of kick that off and then we'll just dive 30 - > right in Sure. 31 - > So putting the success back in customer success, I mean it 32 - > really is a very good jumping off point from everything we've 33 - > really ever talked about with ideal customer profile and 34 - > really framing the problem for the customer. 35 - > And that's really, in my opinion, where customer success 36 - > really starts is really understanding the problem and 37 - > everything from there. 38 - > So there's really a framework to it which includes the problem 39 - > , understanding the path to the solution, how the product gets 40 - > adopted for people, and then really a methodology for how we 41 - > might attack that. 42 - > And we can kind of finish off with a little bit of a tidbit 43 - > and I know we could do multiple podcasts on AI, but since that 44 - > is such a hot topic right now, it obviously does play into it. 45 - > But since that is such a hot topic right now, it obviously 46 - > does play into it. 47 - > But really starting with like the framework, like how would we 48 - > , how would we like lay this out , and I think it really does 49 - > start with the problem. 50 - >

Speaker 2: Oh, I couldn't agree more. 51 - > I think, when you talk about bringing the success back to 52 - > success, a lot, of a lot of it is around the process, and you 53 - > you've heard a lot of people talk about how we've weaponized 54 - > customer success. 55 - > Right, it turned into, its only mission was net revenue 56 - > retention, which became an obsession with strategies to 57 - > mitigate churn, which we would only focus on people who are at 58 - > risk from a health core score perspective and we would try to 59 - > work on expansions and cross sales, and it became all about 60 - > us. 61 - > It wasn't really about success, it became all about us, and we 62 - > just kept throwing bodies at it and we would have executive 63 - > business reviews and quarterly business reviews, and the sole 64 - > purpose of those things was that we wanted to set the hooks that 65 - > you know you were going to retain, and we were trying to 66 - > prove to you that we showed value, versus really thinking 67 - > about it from a success perspective. 68 - > Yes, the spirit of those things is sound, right, there are some 69 - > cases where a QBR makes sense. 70 - > There are probably more cases where it does not make sense, 71 - > but yet we do it anyway. 72 - > Same thing with an EBR, and so I think, as companies grew and we 73 - > fell in love with this process, to me it's very similar to what 74 - > we see with marketing, which is we have a whole generation of 75 - > marketers over the last 10 years who grew up in an era where it 76 - > was more about the process of marketing than it was the 77 - > outcome of marketing, because you could get better and better 78 - > and better at the process of driving leads and getting new 79 - > people in the funnel, and it became about the tactics of ads 80 - > and downloads and gating content and all that kind of stuff. 81 - > And I think customer success was very similar. 82 - > Right, it came, it became about the process and getting better 83 - > at it and using tools and systems and data and it made all 84 - > of that quote unquote better. 85 - > But at some point in time you reach diminishing returns and 86 - > the law of shitty click-throughs kicks in and everybody's doing 87 - > the same thing and it becomes less and less effective and you 88 - > go back to basics, which is, but you're not really helping them 89 - > solve their core problem. 90 - >

Speaker 1: So we have a whole generation of people who, for 91 - > them, marketing and customer success not to overgeneralize, 92 - > but is the process of it versus what is the purpose of it. 93 - > We talk about checkbox marketing, and I think that's 94 - > exactly right, gary. 95 - > I think people have gotten into for lack of a better word a rut 96 - > around checkbox customer success, right? 97 - > So there's great technology, especially to your point about 98 - > being able to detect people that aren't using the product. 99 - > They're at risk, right, and an over-reliance on that as 100 - > something of a leading indicator for churn, for sure, but, as we 101 - > know, oftentimes that's too late, like you've got a window 102 - > of getting people to that moment of value and beyond that it 103 - > almost doesn't matter what you do, right. 104 - > And I think another compounding factor in all of that is the 105 - > notion of features. 106 - > And to your point about with marketing and with sales, right, 107 - > we often want to talk about and this is with founder-led 108 - > companies, oftentimes product-led companies. 109 - > We want to talk about the features. 110 - > This is what it does, this is a cool thing it does right, but 111 - > that doesn't necessarily talk about the problem does right, 112 - > but that doesn't necessarily talk about the problem, right 113 - > yeah, I was just going to reference that. 114 - >

Speaker 2: I'm glad you brought it up is that the feature is a 115 - > tool to help you solve the problem. 116 - > But I think, as we understand the problem, the level or the 117 - > amount of information that we need to understand about the 118 - > problem is broader than it's ever been, because we can't just 119 - > say here's a feature, this is how you implement it, this is 120 - > how it works, and you should do this because it's going to drive 121 - > this outcome. 122 - > But what we fail to understand is well, what are the dependent 123 - > things that happen outside, that need to happen outside of the 124 - > tool, that make the the that outcome possible? 125 - > Like do does this affect my stakeholders? 126 - > Does it affect other parts of the process? 127 - > If so, how do I properly message those changes in the 128 - > process to other parts of the organization? 129 - > What objections am I going to run into? 130 - > What you know, if there's something with which it needs to 131 - > be integrated, well, what does that department need to know? 132 - > How is that going to affect what they do? 133 - > There's a broader perspective that's needed there, and so 134 - > that's when you talk about the problem. 135 - > I think one of the biggest challenges we have is that we 136 - > equip our customer success and even support professionals with, 137 - > theoretically, a lot of product knowledge, but we do not equip 138 - > them with a lot of problem knowledge. 139 - > Right, a lot of context for what is life like on the other side. 140 - > And, as I think about the adoption of this feature, what 141 - > are the other things that I'm thinking about? 142 - > You know, walking a mile in their shoes and having that 143 - > empathy for not just the generic customer but that specific 144 - > customer is you know what moves the needle. 145 - > And then, if you further complicate it by the fact that 146 - > for many products um, that are, you know, that aren't true 147 - > enterprise, where you have a dedicated CSM who actually 148 - > understands the organization, who really is having frequent 149 - > communication, right Is is a part of that. 150 - > There are many, many, many products out there where that 151 - > just that relationship doesn't exist, for good reason, because 152 - > it's it's a more transactional workflow tool or what have you. 153 - > Now, how do you create empathy with your team when they're when 154 - > they? 155 - > They don't have that relationship, they don't have 156 - > the conversations, they don't know the people, the departments 157 - > , the org structure, right there are two compounding variables 158 - > there, right? 159 - >

Speaker 1: One is it's positioned too broadly in 160 - > general, right, so you're selling to people and the 161 - > specific use case isn't really well known at all. 162 - > And then the other compounding variable is when CS gets 163 - > involved, they don't have the context for any of it, 164 - > regardless of like, even if they did, even if it was well 165 - > documented and captured and everything knowing what you know 166 - > use case to bring forward in the first place, to really get 167 - > to that moment of value, that one thing which we'll talk about 168 - > here in a little bit it's that one thing. 169 - >

Speaker 2: They don't have any context for. 170 - > Right, right, okay, so you talked-. 171 - >

Speaker 3: It revolves around giving it a little structure. 172 - > People understand how much structure just relieves the pain 173 - > out of going through the process, because when you have 174 - > run a problem you sometimes don't know where it is, where it 175 - > starts and when it where it ends. 176 - > And if you really give like and he said, if you put some 177 - > example of use cases where this actually happens and just lay 178 - > out, uh, certain paths that the customer go through when you're 179 - > they're going through your product and what they're using 180 - > it for, I think that alternative ABC, if this happens and this 181 - > happens and then this other thing happens, like you know, 182 - > straight path forward, and if you can walk them through that I 183 - > think that's just something that relieves the pain out of it 184 - > . 185 - >

Speaker 2: Yep. 186 - > So, andy, you were talking a little bit about you know 187 - > methodology here. 188 - > So we've established that it all starts with really all 189 - > things in go-to-market start with ideal customer profile, 190 - > period Check Forever. 191 - > We've said that, we'll continue to say that, and chances are, 192 - > if you're listening to this, because you're listening to this 193 - > , you're farther along than others. 194 - > So pat yourself on the back. 195 - > But in our experience, which is over the last, well, decades, 196 - > but especially the last five years as advisors, it all comes 197 - > back to ideal customer profile and the lack of a clear and deep 198 - > and methodical definition around it. 199 - > So get that right first, because then you can understand 200 - > the problems. 201 - > But once we understand that, now what can understand? 202 - >

Speaker 1: the problems. 203 - > But once we understand that, now what, what's next? 204 - > Yeah, and I think it's useful to try and give some context to 205 - > what to do. 206 - > Right, and we've really been grappling with this around 207 - > customer success, which is it does feel almost so analog where 208 - > we talk about QBRs and stuff, but better data is at our 209 - > fingertips, whether that's the ability to integrate product 210 - > analytics or the ability to do conversational intelligence. 211 - > I think our philosophy now and moving forward, is that CS needs 212 - > to be way more analytical. 213 - > So what can you do around that? 214 - > So one simple example is conversational intelligence. 215 - > Right, that used to be really hard, gary, we have friends that 216 - > used to run businesses around trying to get to conversational 217 - > intelligence, right, like, and we think back, and that wasn't 218 - > that long ago how for lack of a better word crude, that might 219 - > have been right. 220 - > It was like there were tools and you know it was like 221 - > tech-enabled service and we were trying to like pull information 222 - > out of like daily conversations and a lot of those were like 223 - > like daily conversations and a lot of those were like calls, 224 - > let's just say actual calls. 225 - > And that wasn't that long ago. 226 - > But now, assuming people are recording these conversations CS 227 - > conversations, sales conversations, which might 228 - > include discovery, demo and so on. 229 - > Right, there is a wealth of information at one's fingertips 230 - > to be able to do what we just talked about, which is map. 231 - > You know the customer's journey Like how do they get to that 232 - > moment of value? 233 - > What is the problem? 234 - > Can we glean more about this use case? 235 - > And around you know the people that have that use case. 236 - > You know ideal customers, so you do that through. 237 - > You know there's a lot of tools for that sophisticated tools, 238 - > but you can do it in in much simpler ways too. 239 - > But that's one example of being more analytically driven is 240 - > just just dig into that sort of stuff. 241 - > And the other side is, as I mentioned earlier is product 242 - > analytics right? 243 - > So not just taking what the tool and and I won't name names 244 - > says about somebody being at risk of churn, actually doing a 245 - > lot more to understand why and to get to the bottom of that, to 246 - > say you know what? 247 - > We lost them here, and we've seen that now three times. 248 - > And it was this situation, it was these type of customers and 249 - > we didn't do this. 250 - > And I bet if we did this it would make a difference in 251 - > testing and doing it, but it's really all about being 252 - > analytical and probably having someone whether that's a 253 - > full-time, that's going to be dependent on resource 254 - > availability, but having someone dedicated to that not just on, 255 - > we, we, we all know about that from you know marketing and 256 - > sales, but really truly on the cs side yeah, so there's a lot 257 - > in there, andy, so so I there's three things. 258 - >

Speaker 2: Right, the is and I want to touch on this because it 259 - > actually is um, uh, very hot off the press from a 260 - > conversation I had this morning and that's around that 261 - > conversational intelligence piece. 262 - > The second is around uh, product analytics as uh, as an 263 - > indicator to help prioritize where we should be spending time 264 - > and effort. 265 - > And, um, thirdly is around resource allocation. 266 - > So let's tackle those in those that now were. 267 - > So the first is that the thing. 268 - > So, as some of you may know, I am stepping into a role, have 269 - > stepped into a role, as chief revenue officer for SparkHire, 270 - > which is a portfolio company of Boathouse Capital, and we are 271 - > actively working on how we think about extracting valuable from 272 - > the customer information from unstructured data, mostly calls 273 - > and emails. 274 - > And, to your point, there's been quote unquote 275 - > conversational intelligence tools as long as people have 276 - > been recording calls and creating that category. 277 - > But really, how it informs what you do beyond just a selling 278 - > process and how you bring it into customer success is really 279 - > important. 280 - > But I knew this going in, but what I've discovered is that the 281 - > or reaffirmed, I should say the AI tool is only as good as what 282 - > you provide it. 283 - > And that starts with the questions and conversation and 284 - > exploration that your team pursues, whether it's on a Zoom 285 - > call or via an email. 286 - > And the problem most organizations have when they 287 - > start to implement those tools is they want the output but they 288 - > haven't done the hard work to get the inputs right 100%. 289 - > And that goes back to ideal customer profile understanding 290 - > what their challenges are. 291 - > In our case, we use the SPICED framework situation, pain, 292 - > impact, critical event decision-making process. 293 - > In almost every stage of GTM, all of those apply. 294 - > There is some critical event, there is some decision that 295 - > needs to be made, there's certainly situation and impact. 296 - > And so getting the organization to think like an advisor or a 297 - > consultant who starts all conversations with great 298 - > discovery that that is what feeds the true insights. 299 - > For so you can begin to see patterns and what you want to 300 - > take action on. 301 - > But most organizations jump straight to the tool and don't 302 - > spend the hard work there. 303 - > The other thing that I've learned is that there really 304 - > needs to be. 305 - > You can't just throw this over the wall and implement, because 306 - > what you get out of the tool is largely a function of what 307 - > you're, what you're asking it and how you're asking it. 308 - > And so we've heard a lot about this prompt engineering thing, 309 - > right, and so there really is a. 310 - > In order to get the fidelity that you'd like out of these 311 - > tools, you really, senior leaders, need to invest time in 312 - > getting that right so that we get to the insights that we need 313 - > , which is, again dependent on the questions that you ask. 314 - > So it really comes back to fundamentals, right? 315 - > I mean, yes, now, for the first time, we actually have tools 316 - > that can help you get and make sense of, and begin to structure 317 - > unstructured data in a way, but it's not rows in a spreadsheet, 318 - > right? 319 - > It's not something that's deterministic, that's created in 320 - > one system and passed through to another and then we want to 321 - > analyze it. 322 - > It's humans, it's conversation, so we need to mold it and shape 323 - > it, and we do that, by the way that we ask questions. 324 - >

Speaker 1: Yeah, I do think there's a starting point there 325 - > and it's not implementing a sophisticated tool, right? 326 - > If you're not doing that today, if you don't, if you're being 327 - > really honest about it and you're saying I'm not entirely 328 - > sure what my ICP is, if we really think about ICP and 329 - > really dig in and say, okay, do I know not only like 330 - > pharmacographics associated with you know who I might sell into 331 - > fairly typically, but what are the conditions, what are the 332 - > situations around where somebody actually ends up getting value 333 - > from that? 334 - > If we're really thoughtful about that, we know we're not 335 - > quite there yet. 336 - > If we're really thoughtful about knowing that we don't, you 337 - > know, quite have our onboarding where it needs to be and a lot 338 - > of things around that. 339 - > But starting there, you can start to create a virtuous cycle 340 - > around that. 341 - > Right, using the simple methods that we talked about a little 342 - > bit using what are the conversations I'm having today? 343 - > Can I use thoughtful prompts and we won't get into any of those 344 - > right now to start to tease out some of those patterns of 345 - > discovery? 346 - > If I can combine that with Spiced and really, you know, try 347 - > and map that and say, okay, I'm at least at a point where I 348 - > have a place to begin with discovery, then I can start to 349 - > have more thoughtful discovery, which will then feed better 350 - > pattern matching and so on. 351 - > So it becomes like a cycle of saying, like I have to start 352 - > somewhere, I can start with at least pattern matching what I've 353 - > done to date. 354 - > You know, let's say I don't know what volume makes sense to 355 - > do that against. 356 - > You know several dozen conversations at least where I 357 - > can take them pattern match against those using you know the 358 - > crude tools. 359 - > If you will chatPT for one, which we've done, we've proven 360 - > that can be done and start there , I totally agree, gary, if you 361 - > just go to one of these more sophisticated tools and just say 362 - > , actually, I'll just say this they know, based on 363 - > conversations we've had, that there are customers that 364 - > shouldn't be using their tools. 365 - >

Speaker 2: Yeah, you are not ready for us, you're not ready. 366 - > They won't admit it, but yes, they don't want to admit it. 367 - >

Speaker 1: They'll try and make it work, for sure. 368 - >

Speaker 2: But yeah, yeah. 369 - >

Speaker 3: How can you determine if a customer well, of course, 370 - > knowing well your ICP like going , but going beyond that. 371 - > How do you determine if a customer is right based on your 372 - > ICP? 373 - > How do you strictly define who they are in order for you to be 374 - > able to understand if they are a right fit for you? 375 - > And then how can you find the signals that indicate that the 376 - > customer will be successful with your solution? 377 - >

Speaker 2: Let me twist that question just a little bit and 378 - > bring it back to Andy's point. 379 - > So the point you made is fantastic, which is, before you 380 - > even think about the AI tool by walking through and in this case 381 - > we're talking about discovery from a sales perspective, but 382 - > it's just as important from a CS perspective, if not more 383 - > important, where you have the opportunity to do that, and that 384 - > is that there is immense benefit from structuring your 385 - > conversations in that way, I think for multiple reasons. 386 - > One is because so many times we provide people like here's what 387 - > , here are the questions that you should ask. 388 - > Well, they'll go ask those questions, but they don't know 389 - > why they're asking those questions. 390 - > So what we need to help them with is this is what we need to 391 - > understand. 392 - > Here are examples of questions that you could ask, but after 393 - > that, you need to give them the freedom to go two and three and 394 - > four layers deep to really unpack what's going on and and 395 - > and. 396 - > The benefits of that are that you start to create more 397 - > structure so that everybody in the organization is following a 398 - > similar framework not necessarily script, but 399 - > framework so that when you start doing deal reviews and film 400 - > reviews and situation reviews and risk level reviews for 401 - > customer success. 402 - > You're all getting, at the same , information that you know is 403 - > important and relevant. 404 - > Then when you put AI on top of that, then that's how you can 405 - > start to really make that home. 406 - > But you, but putting that first before you have the other, 407 - > you'll just you'll be spinning your cycle. 408 - > So, tiana, you were asking about this, the, the signals, and so, 409 - > in terms of fit, let me say that. 410 - > So now we're thinking about customer success and their 411 - > customer is. 412 - > It goes back to what we talked about from discovery, which is 413 - > there. 414 - > You know, at this point you're a customer. 415 - > So we have to recognize, based on where we are today, you may 416 - > very well be a customer, but that doesn't mean you're an 417 - > ideal customer, right, because the needs of the business have 418 - > shifted and that happens all the time, and so we need to 419 - > recognize that. 420 - > And then the other, as we start thinking about the application 421 - > of features, or you know, giving you advice or recommendation is 422 - > around. 423 - > Your readiness to adopt those features Is? 424 - > Is the, you know, your version of the pain sufficient enough 425 - > that this makes sense? 426 - > Is your organization structured in such a way that you're going 427 - > to get value from this? 428 - > And then so you're looking for for those I think from a quote, 429 - > unquote, fit standpoint. 430 - >

Speaker 1: Yeah, I mean I wish there was one answer to ideal 431 - > customer profile, but that's kind of the point, is it really 432 - > is business conditions for not only your prospect but their 433 - > customers. 434 - > It does boil down to, in a lot of cases, a unit of value which 435 - > we won't get into here but like what is? 436 - > what is like the benefit you convey to your customer? 437 - > What is it based on? 438 - > And there's usually a thing right could be like impressions 439 - > or seats or something like that. 440 - > And then there's a bunch of things below that, which is what 441 - > are those pains associated with getting to administering that? 442 - > Administering something, getting visibility on something, 443 - > getting value for something, and it really requires Tiana 444 - > just hearing that directly and indirectly. 445 - > Sometimes sales teams know that inherently and they just don't 446 - > know how to get it on paper sometimes. 447 - > So, yeah, yeah, I think like around. 448 - >

Speaker 3: What you're saying is like the focus on the one thing 449 - > , like what's the single most important success factor for 450 - > your customers, and like how do you ensure that you're not 451 - > overcomplicating that journey, the journey to get there, and 452 - > just focusing, like on those core, main aspects and of course 453 - > , there's way too many things involved around that. 454 - > But I think if you ask yourself that those questions like 455 - > constantly, every day, when you're, and you're paying 456 - > attention to finding, like those , those two key signals, to me I 457 - > feel like that that will make everything just much simpler for 458 - > you to decode. 459 - > How to get them there. 460 - >

Speaker 2: Yep, yep, and I would say so that's, and then I think 461 - > related to that then is the second point you made, andy, 462 - > around product analytics is. 463 - > You know, we've been using that for a long time, but it's been 464 - > overly focused on. 465 - > We have a predefined, we have a set of signals that we have 466 - > either validated or assume mean that you're getting value out of 467 - > the product based on the usage of the product, right. 468 - > But we've seen over and over again that those can often be 469 - > false positives, depending upon your industry and what you're 470 - > doing, where, yeah, I'm using the product, and then suddenly 471 - > you show up and you're like I'm going to cancel and we're moving 472 - > over this other tool. 473 - > But wait, but you've been, you know, you've, you're green, our, 474 - > our, our health score says you're green, like you're using 475 - > it all the way that you should. 476 - > And I think that one of the things that we are doing and 477 - > exploring is how can we begin to use those signals as indicators 478 - > of where we should step in and offer assistance, which is on 479 - > the basis of how big of an organization are you? 480 - > What do we know about your organizational structure? 481 - > Take everything that we learned from a Spice perspective and 482 - > have that be kind of the foundation and then knowing that 483 - > , looking at your specific usage of the product and when you 484 - > begin to do something, it may signal that we need to step in 485 - > and say, hey, I see you're doing this for the first time. 486 - > Let me offer you some help, and that doesn't necessarily need 487 - > to be a human being stepping in Although I think there is some 488 - > context there that you can provide, because it's not just 489 - > and here's how to use this feature, but it's hey, there's 490 - > some other things that you might think about as you begin to 491 - > implement this feature. 492 - > Here's a good blueprint that's worked for other organizations 493 - > that look just like you. 494 - > Here's what they have learned in this process. 495 - > So now you're truly putting the success back in, success Like 496 - > I'm. 497 - > I'm not waiting for you to run into a challenge and ask me, or 498 - > worse, run into a challenge and not ask me, or, you know, get 499 - > some. 500 - > Not even know about a particular feature or what have 501 - > you, but stepping in proactively , like, hey, I see that you're 502 - > doing this thing, but I also noticed that you've not used 503 - > these couple of features. 504 - > We built this things specifically for companies that 505 - > look like you who are in this situation. 506 - > Can I help you with that? 507 - > Would you like to see that, and here are the benefits. 508 - > If you were to do that, and sometimes like, no, this is good 509 - > enough for us, fine, right, but the fact that you stepped in 510 - > and were available to them at the moment and I think that's 511 - > the place that I believe that that's another place where AI 512 - > can begin to help us is, again, it's not deterministic, but it's 513 - > like hey, here's a pattern here that you may want to step into 514 - > and take a look at and lean into , and I think that's the one 515 - > thing, tiana. 516 - >

Speaker 1: It doesn't mean one feature to Gary's point right. 517 - > It means the situation that, like the team, the organization 518 - > involved get, it's getting to that moment of value they're 519 - > doing. 520 - > They're doing the thing as it's intended. 521 - > They're doing the thing in a prototypical fashion that we've 522 - > seen multiple businesses that are getting good value of this, 523 - > and we've heard this right. 524 - > Like the company has said, we are getting good value and we're 525 - > using it in this way. 526 - > We're now getting them to use it in that way, and it could be, 527 - > you know, any mishmash of features. 528 - > What it isn't, though, when we get outside of that one thing is 529 - > when we try and get too many, too many things going at once, 530 - > because this is, it's an exercise in change management. 531 - > A lot of times, right, you're getting an organization to 532 - > change the way they do things, so ideally, you're not over 533 - > complicating that with oh in this thing, oh in this thing, 534 - > it's here's a process and there's a number of ways, and I 535 - > think we're here's another way ai is going to really benefit is 536 - > giving a number of different ways to train, to onboard, to 537 - > give them a process to get from point A to point B in getting 538 - > value out of the tool. 539 - > I'm really excited about that. 540 - > That's maybe a playbook type of situation multiple formats, 541 - > video, the written word, tutorial, know, tutorial of some 542 - > type, getting them from point A to point B, but it's not giving 543 - > them too much to chew at once, I think is the one thing. 544 - > Getting them to a value but not overcomplicating it, yep. 545 - >

Speaker 3: Measuring success in terms of outcomes and not 546 - > focusing too much on feature usage. 547 - >

Speaker 2: Absolutely Yep, connecting the dots Exactly Well 548 - > . 549 - > It leads to the third point, then, which you mentioned around 550 - > the need for some potentially in the organization, some form 551 - > of analytical support in the organization, some form of 552 - > analytical support, and I frame that as a resource allocation 553 - > perspective, because I think that's another thing that we 554 - > need to think about, and part of the discussion I had this 555 - > morning regarding AI is that we need to rethink how we solve 556 - > problems, and one of those is how are we thinking about how we 557 - > should structure our organizations and what skill 558 - > sets we need? 559 - > How are we thinking about how we should structure our 560 - > organizations and what skill sets we need? 561 - > And when you look at all the level of nuance that we now have 562 - > access to through AI, that we didn't have before. 563 - > The only way we had that nuance was to get somebody involved 564 - > and have a conversation directly and then extract that and 565 - > interpret the nuance or whatever , but we have now an ability to 566 - > take some of those and start to see themes and patterns. 567 - > It requires a much more data-driven, analytical approach 568 - > to this so that we can prioritize where we spend our 569 - > time, so that we can be efficient, and that doesn't mean 570 - > that we're only helping the quote, unquote at-risk customers 571 - > and not helping the ones that are doing okay. 572 - > It's like, truly from a success perspective, we're at the 573 - > moment that the point at which help is the most powerful is in 574 - > the moment you need it. 575 - > Right, you get a flat tire and suddenly somebody all of a 576 - > sudden a tow truck shows up right beside you Like that was 577 - > awesome. 578 - > Right Versus waiting, having a call, figure it out, wait three 579 - > hours, get it scheduled. 580 - > And I think that's where we have the opportunity to be 581 - > either much faster from a responsiveness perspective or 582 - > even anticipate what challenges are, knowing the questions that 583 - > you should be asking before you're asking them, and giving 584 - > you this smoother path. 585 - > That actually okay. 586 - > Yes, theoretically I could throw this. 587 - > Hey, here are these features and you know, here's a bunch of 588 - > help articles to how to implement them. 589 - > But what if I actually walked them through, walked alongside 590 - > of you to see you go and what that would look like, walked 591 - > alongside of you to see you go and what that would look like, 592 - > and now you're off and running. 593 - > So that requires us to rethink. 594 - > Does that skill set sit inside of each individual, or should we 595 - > think about creating? 596 - > Is that in RevOps? 597 - > We hear a lot about a GTM engineer? 598 - > Is it in CS. 599 - > There's no frankly right answer , but that capability is 600 - > something that is increasingly important and we're going to 601 - > need to invest in. 602 - >

Speaker 1: That's changing. 603 - > I mean honestly, that's changing every day too. 604 - > It's really. 605 - > I mean just observing that, like the whole notion around a 606 - > GTM engineer. 607 - > Now that's mostly, I think, geared. 608 - > I've seen it around like the clays of the world. 609 - >

Speaker 2: Yeah, mostly acquisition oriented yeah. 610 - >

Speaker 1: You're 100% right, that is absolutely changing 611 - > rapidly for all facets of GTM and I would say this CS might 612 - > have the nearest term and biggest uh gains from doing that 613 - > thoughtfully anyway, right like it's to your point. 614 - > That's a different skill set, it's a different mindset yeah 615 - > we've been talking about right, the, the think of ways of doing 616 - > things differently. 617 - > You talked about the, the, the story about the printer, 618 - > somebody, somebody printing out the like, and I don't know if 619 - > you want to say that, yeah, so real it's funny, Andy. 620 - >

Speaker 2: It's so funny. 621 - > You brought that up because I literally referenced that this 622 - > morning, because it jumped out in terms of how we have to 623 - > rethink, and that's and I wasn't listening. 624 - >

Speaker 1: by the way, this is a total story. 625 - >

Speaker 2: But but I don't even know if it's real. 626 - > But you know, we, as experienced people, are 627 - > encumbered by the curse of knowledge and the way that we've 628 - > solved problems. 629 - > And so an intern is asked by someone to put 50 pieces of 630 - > paper together, collated in the conference room so that we can 631 - > use them to put up ideas on the whiteboard. 632 - > So they go back to their desk, they open up a blank document in 633 - > their word processor, they hit print, they hit quantity 50, and 634 - > they hit go and the printer spits out 50 collated pieces of 635 - > paper and they take the output over to the conference room and 636 - > slap it on the table. 637 - > You know and you're like well, honestly, is that lazy? 638 - > Is it a waste of printer capacity or whatever? 639 - > But nonetheless, what struck me was that I never in a billion 640 - > years would have thought that's how I would go produce 50 pieces 641 - > of collated paper in one go. 642 - > And so I think a lot of that is true for those of us who have 643 - > been around this a long time is to be we. 644 - > We will have a tendency to try to take this new tool and put it 645 - > into the framework that we already understand and get it to 646 - > conform to the way we would solve the problem versus how 647 - > could I, you know, unlearn all of that? 648 - > And if I were, this is, I guess , your first principles thinking 649 - > take what this thing is able to do and rethink how I solve the 650 - > problem. 651 - > And I think what it's a good segue to kind of wrap us up to, 652 - > which is I'm increasingly seeing , like where does customer 653 - > success begin and product end? 654 - > Like those lines are really blurring because, as we think 655 - > about analytics and data driven and AI, it's like the, the, the, 656 - > the success team really done well, is an extension of product 657 - > and vice versa. 658 - > Right, and it's the CS aspect, which is understanding the 659 - > nuance in the situations to be able to help you conform, mold 660 - > the product to meet your needs. 661 - > And the problem that we've had in the past with the product is 662 - > it's very deterministic, right, it works like this, it works 663 - > like this, this is how you use it, but creatively, we think 664 - > about ways that we can mold it and shape it for our particular 665 - > business purpose, and so now do we have that ability to start to 666 - > do that? 667 - > You know where does the product actually start, to recommend, 668 - > based on that knowledge of the customer situation and 669 - > conditions, how you might implement this or how you might 670 - > use that. 671 - > So anyway, it's the wild west in many ways. 672 - >

Speaker 3: I think it's even extremely interesting to think 673 - > about the product person in a customer success position, for 674 - > them to first go through the product and then to be at the 675 - > customer success part of it, because nobody understands the 676 - > product better than them. 677 - > because they built it, they're a part of how it was built and 678 - > what it what it's for and, at the same time, them being able 679 - > to exist from a point where they already have all the 680 - > information and it's. 681 - > I think a huge part of this is like you were mentioning is just 682 - > being very proactive. 683 - > I don't think I don't remember where exactly I saw this. 684 - > There was this small if you're confused page or something like 685 - > that. 686 - > And if you went in, the questions were fairly simple, 687 - > like are you stuck, you know? 688 - > And I was like, yeah, I feel stuck. 689 - > So you started like and like I was telling you how you connect. 690 - > If A happens, then B is the solution and if you do B, then C 691 - > will be your outcome. 692 - > And instead of just thinking about teaching people how to use 693 - > the features, they go hey, do you want to accomplish this? 694 - > Then this is how you do it, like, after you tell them what 695 - > they're getting out of it, then you start teaching them how to 696 - > do it and like how to start using the feature. 697 - > But if you're just telling people to use features, for what 698 - > purpose? 699 - >

Speaker 2: Yeah, yeah, that's a great point too, and I think 700 - > it's a challenge, because the other aspect is that we live in 701 - > an attention deficit era and so people just want the easy button 702 - > and in some cases, like, okay, here's this feature and the 703 - > utilization of this feature will drive this outcome for you. 704 - > But before you get started, you really need to have answered 705 - > these questions. 706 - > In our case. 707 - > I'll give you an example. 708 - > In our hiring platform, we have something called a custom 709 - > scorecard, which allows you to customize how we're going to 710 - > assess a certain candidate. 711 - > Well, before you go diving in to use that, you better have a 712 - > pretty good idea of well, how do I want to structure that? 713 - > Like, what are the competencies that I want to look for? 714 - > How am I going to grade those? 715 - > Is that consistent? 716 - > So it doesn't matter what the tool does if I haven't 717 - > previously answered those questions. 718 - > And if I don't answer those questions and just dive right in 719 - > , then the results that I'm going to get aren't what's 720 - > advertised, and sometimes that's like, ah, it's too much work 721 - > and so. 722 - > But from that perspective, like , is that a customer's fault or 723 - > is ours? 724 - > Like, okay, well, how do I, how do I baby step you there so 725 - > that you can do it in increments and pieces. 726 - > Can I give you a template? 727 - > Can I give you a framework? 728 - > Can I give you something that makes it easy for you to get 729 - > started so that you're off to the races. 730 - >

Speaker 1: That's getting to the point. 731 - > Give me something usable now. 732 - > Get me to something usable so I can see that, so that I can 733 - > then augment it and really fit it to, say, the role I'm hiring 734 - > for. 735 - > But give me the like, get me started, show me the light. 736 - > And then then, yeah, they'll have a little bit of work to do, 737 - > of course, but that's that's. 738 - > That's a recurring theme that we keep hearing, right like 739 - > you've got to have a process yeah, indeed, all right. 740 - >

Speaker 2: Well, that's how uh, the beginnings of how you can 741 - > get the success back in customer success. 742 - > We're going to follow up on this theme and really dive into, 743 - > because I think it is the most interesting place where you can 744 - > see AI have a very real impact in the near term, and so we're 745 - > going to be spending a little bit more time there. 746 - > But in the meantime, go be a pro. 747 - > Bye, go be a pro. 748 - > Bye. 749 - > Thank you for tuning in to GTM Pro, where you become the pro. 750 - > We're here to foster your growth as a revenue leader, 751 - > offering the insights you need to thrive. 752 - > For further guidance, visit gtmproco and continue your path 753 - > to becoming board ready with us. 754 - > Share this journey, subscribe, engage and elevate your 755 - > go-to-market skills. 756 - > Until next time, go be a pro.