Episode No:83

Optimizing Net Retention for SaaS Businesses

Brent Grimes

Founder, Reef.ai

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Ep#83: Optimizing Net Retention for
SaaS Businesses ft. Brent Grimes (Founder, Reef.ai)
Ep#83: Optimizing Net Retention for SaaS Businesses ft. Brent Grimes (Founder, Reef.ai)
  • Ep#83: Optimizing Net Retention for SaaS Businesses ft. Brent Grimes (Founder, Reef.ai)

Episode Summary

In this Hyperengage Podcast episode, Adil and Taylor interview Brent Grimes, CEO and Founder of Reef.ai, a customer revenue platform. Brent shares his journey and experiences, including his time at MuleSoft, where he gained insights into the challenges and opportunities in driving Net Revenue Retention (NRR). He highlights the value of recurring revenue and the nuances of managing it, emphasizing that it’s different from new customer acquisition. Brent explains how Reef.ai was inspired by the need to effectively allocate resources within customer success teams, particularly in identifying which customers are primed for growth and which are at risk, without burdening CS teams with data entry. He discusses the challenges faced by startups and larger teams when adopting customer success platforms and how Reef.ai‘s approach eliminates the need for heavy data capture and change management while optimizing customer success. Brent also talks about the failures and successes in implementing technology to support customer success and the importance of smart pivots in refining their approach.
Key Takeaways Time
Brent Grimes’ startup experience, with a focus on recurring revenue and net retention, shaped his creation of Reef.ai.
Reef.ai arose from the need for efficient resource allocation and customer prioritization, moving beyond traditional customer journey models. 3:10
Reef.ai tackles customer success challenges with a lightweight, exception-based approach that eliminates data entry burdens for teams. 7:54
The platform’s philosophy revolves around using machine-generated data, enhancing efficiency for customer success teams. 9:32
Reef.ai‘s development was prompted by MuleSoft’s challenges in managing automated activities and relies on existing data sources. 14:16
Reef.ai supports a variety of roles in customer success organizations, offering reporting and insights for all levels of management and contributors. 18:04

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[00:00:03] Interview with Brent Grimes, CEO and Founder of Wefri [00:00:03] Adil Saleh: Hey, greetings, everybody. This is Adil from Hyperengage Podcast. I have my cohost, Taylor Kennedrson, a very special guest, long awaited. We met Brand back when a customer success event hosted by John and his team and the very first time we heard the story was incredible. Ever since then, we are following him and his product. Thank you very much, Brent, for taking the time. Today, Brent is the CEO and founder of reef.ai. It's a customer revenue platform serving small to mid sized businesses. Recently visited funding a team of ten people one more time. Thank you very much, Ben, for taking your schedule. [00:00:41] Brent Grimes: Ideal. Hi, Taylor, such a pleasure to be here. Really excited to jump OOH. [00:00:46] Discussing the Journey and Challenges in Driving NRR with Brent Grimes [00:00:46] Taylor Kenerson: So we're going to go nitty gritty. We're going to go into really interesting you have a really interesting journey and background, Brent, to lead, you know, founding your own company, your second company that you founded, but your own company in this space now. So really curious on how your experience, specifically at MuleSoft helped you understand the challenges and opportunities in driving NRR and then how that shaped and played into reef today. [00:01:15] Brent Grimes: Sure, yeah, happy to dive into that and just going way back just to give you the full background. So started as a developer many, many years ago. And then, as you mentioned, I did my first startup in the.com cycle, way back, so 1998 to 2002. So it was a four year run, a lot of fun. Just like many companies, we followed the wave and went from really high to really low really fast. And that was my first learning in the world of startups. And then after that, I really wanted to know all the things I didn't know the first time around. So I went and I built out my career first as a presales leader. So sales, engineering. So the tip of the spear in the sales cycle. And then I did sales and carried a bag and then really made my way to net retention and recurring revenue, actually in sales at a company called Service Source. And so what we did at Service Source is we would outsource the recurring revenue for mostly large technology companies at the time. And this was before staff was really a big thing. It was still more licensed sales. So imagine you buy a Cisco router, you get a maintenance contract that's recurring along with that router. And these companies, even though they were big revenue streams, didn't do a great job of taking care of them. So we'd come in, we'd have specialized people, processes, technology, and we would do a much better job than our clients at managing this revenue stream. And our business model is we would just take a percentage of the incremental revenue that we drove on their behalf. So really successful business, we went public and I really walked away with two big learnings. One is that recurring revenue is extremely valuable. And two is that it's actually hard, it's really nuanced and really different than new customer acquisition, I think to a degree that most companies didn't really understand or appreciate. And I think that's still an issue today. [00:03:10] Discussion on the effective utilization of resources and the inspiration behind Reef.ai [00:03:10] Brent Grimes: So fast forward. When I met with the leadership at MuleSoft about the customer success opportunity there. This is early days. I talked to Ross, the founder and Greg the CEO. And what I was really excited about was they were very open to giving me the latitude to create the model for customer success that I thought would best fit the business at MuleSoft and best support the business. So the model we created was a little bit of an outlier model because of my background on the sales side. It was more, I would say, revenue attached and accountable than was average in the industry at the time, right? So people had leveraged, comp plans, they had individual quotas, because I thought it was really important at the end of the day, as MuleSoft succeeded, that we could draw a very clear line between the success of the company and the contributions of customer success. And I'm not an advocate for turning CS people into salespeople and making them salesy, but I am a big proponent of it's really important that you can quantify the impact that you have on an organization and the contribution that you make, right? And especially in times like today, the economy is tough and it's really hard to justify resource investments, right? So if you can't clearly say, look, here's the yield that I can produce if I get another resource, it's really hard to justify new resources. In some cases, it's hard to justify your existence. Right? And so I'm a big proponent that we need to go beyond the lagging indicators like revenue and pipeline and really have a clear, common set of leading indicators for customer success that are true reflections of customer health and customer value realization. Kind of beyond the traditional feel good metrics of customer happiness and the things that are much harder to quantify. And that was really the inspiration for Reeve. So at MuleSoft, as we were building and scaling the team, we reached a point where we realized we just can't cover every customer. Every year we're asked to do more with less, and we realized we were spinning a lot of cycles and wasting a lot of time on things that were not high yield or high impact. And we tried a couple of times with CS systems off the shelf to solve it. And what happened was it spun up a bunch of activity and busy work, but it didn't really help us get good at the thing we wanted to get good at. Which was, if we have to ruthlessly prioritize our resources. How do we make sure that people are focused on the things that are going to have the biggest revenue impact or customer outcome impact? At the end of the day. So we ended up building it ourselves. We pulled a bunch of data related to our customers. We aggregated the data. We started with a manual regression model, which eventually became machine learning, but it allowed us to better understand what are the conditions that we created with customers historically, or the actions that we took with customers that made them statistically more likely to grow or less likely to churn. And once we understood that, we could identify cohorts of customers that we knew were a better investment of time and resource than other customers. And this allowed us to get much more efficient with our model. So we got sales leadership on board, we got CS leadership on board to agree to treat these customers differently. So that meant investing at a different level, tracking data at a different level, and holding the teams accountable at a different level. And this shift in model, what it did is, on one hand, it freed up a bunch of capacity because we said, look, you can let go of all this rote, busy work. You don't need to check in with every customer every two weeks just to make sure things don't fall through the cracks. That's a really inefficient way to manage a customer lifecycle. Or because you hit some time based milestone, we're going to just allow you to focus on the ones that we know are most likely to have a revenue impact or a customer outcome impact if you invest right. And so the shift in model freed up capacity and allowed us to actually perform better. So our growth rate accelerated, our net retention accelerated. So I'm a huge believer in the model. The way we built it at MuleSoft was very manual and labor intensive and something we could only do as a once a year planning exercise. So the whole vision with Reef is we've productized that whole lifecycle from data connectivity to aggregation, to scoring customers and really bringing it to life in a UX that makes it really easy for people who deal with customers to make good decisions about where they spend their time and what they interesting, interesting. [00:07:49] Adil Saleh: Quick question, if I may, kidder, you have a question on top? [00:07:52] Taylor Kenerson: Go for it. [00:07:54] Adil Saleh Discusses Customer Revenue Platform Adoption Challenges in SaaS Businesses [00:07:54] Adil Saleh: Okay, cool. So we spoke to more than 50 SaaS businesses. Most of them are small to mid market about this. They're also thinking of doing more with less. They're also thinking about digital CS. They're also thinking about optimizing their Customer success, task management and all of these things. They have like, VPs looking at reporting dashboards. We spoke to leadership at Widely, spoke to leadership at Catalyst. All these folks, they're serving the same customers, same use cases. And then we got back to these small teams and we asked these questions how easy or hard for them to make a decision on a customer revenue platform, customer success platform? What we heard from startups is, of course they think that their processes, their data structure, their events, their data ops is not there. [00:08:47] Taylor Kenerson: They're not there in the first two. [00:08:49] Adil Saleh: Years to invest or incorporate a tool, like re tool, like let's say to Tango. Gains at all these tools out there on the shelf. This is coming from the startups. Now when we talk about some bigger teams, what they say? Okay, we already using Tango. We already using these tools and it is so hard process for us to do the change management. And it takes like three to six months on average to basically introduce, incorporate and implement a new tech stack into our processes across the organization. So how are you going to really appreciate because you're the right person to ask this and I was waiting on this conversation. [00:09:32] Challenges in Customer Success for Startups and Big Teams, and How Reef.ai Addresses Them [00:09:32] Adil Saleh: So how do you cater both of these cases for startups that think that they don't need it, they don't have the data ops, they don't have the bandwidth, they don't have even more than two customer success people. [00:09:42] Taylor Kenerson: Or maybe if they have people on. [00:09:43] Adil Saleh: The customer facing roles, they're doing like support, sales and success altogether the same, wearing different hats versus bigger teams that think that there's a huge amount of change management they would require. [00:09:55] Brent Grimes: Yeah, I know, there's really good points and they're both valid. Right? And so our philosophy on this is a little bit different. And if you think about small startups, I absolutely agree, like putting in heavy overhead in terms of a customer success platform on top of your CRM, that spins up new data capture requirements, new processes and frankly bogs down the teams. Like what you want is you want your teams to have as much time to spend with the right customers as possible. Right? And I think one of the traps of customer success platforms is the day you install it, you suddenly put a burden on your customer success team to enter a bunch of data, capture a bunch of data and go from there. Right. And then for larger teams, you're right. Again, I think customer success platforms are unnecessarily kind of heavy and burdensome. I think there's no reason that customer success people should have to enter a bunch of data about customers. Right. There's a lot of data that exists. And this is one of the things we learned at MuleSoft was the data that people capture day to day is a much less reliable indicator of future performance or action than the machine generated data that already exists. Whether it's product telemetry, whether it's how they're engaging your support, whether it's how they're engaging your marketing efforts. There's a lot of signal out there that is actually more reliable signal than people having to update fields once a week or once a month or once a quarter. Right. So our philosophy is very different. Reef does not require any data capture data entry. Right. So I think that we've approached it a little bit differently, which is if you think about the typical kind of basket of capabilities with a customer success platform. You have customer data capture, you have journey management, you have things like NPS. We've really moved away from this attachment to a linear customer lifecycle, right? Because I think that's fundamentally flawed and it makes sense in the beginning, but it breaks down as you start to scale, right? And it just doesn't scale because this linear process really assumes that you're going to treat your customers in a certain way based on time or based on milestone, and it's going to spin up activity whether that activity is really the right thing or not. So the way that we approach it in our philosophy is much more of a lightweight exception based model, which is that if you think about a customer base, the majority of your customers are on track and don't need extra investment in terms of time and resource. Right. So they're on a pattern where they're probably likely to renew. They may not be in a position to grow a lot, but they're relatively healthy and succeeding with your product. And then you have the outliers, right? You have the ones that are primed for growth and you have the ones that are at risk or struggling and maybe likely to churn, right? So if you can take your resource and overinvest in the growth opportunities and the churn mitigation and just make sure that you have good touch points and kind of keep the lights on processes for the ones in the middle, you'll get a much higher return and better yield than trying to invest in all of your customers equally. The whole philosophy is that you don't put a burden on the CS teams. You don't worry about the change management as much because, again, you're not asking them to do a lot of new things. You're just helping them get good at identifying and making decisions about the customers that are primed for growth that they should be investing in and then the customers that may be at risk and not at the renewal cycle, but well in advance. Right. So if you're identifying six months in advance, we've got a problem or we've got an opportunity. You can build a plan to either mitigate risk or maximize your growth opportunity alongside that renewal when you get there. Absolutely. [00:14:02] Taylor Kenerson: And it's so much about going beyond the traditional metrics that we look at the time based those metrics are that's what causes either the churn or the invaluable waste of time in certain areas. It's taking that. [00:14:16] Dealing with Challenges and Building a Customer Success Model: Insights from the MuleSoft Experience [00:14:16] Taylor Kenerson: I love what you took when you joined MuleSoft. You took such an unorthodox approach to how you built the CS team. So I'm really curious to dive into because it seems like a lot of your experience really shaped how Reef was built and what Reef really turned into. So can you dive a little bit into specifically some of the challenges that you experienced at MuleSoft that really drove the philosophy behind Reef, you mentioned one thing was the linear customer journey and kind of breaking that stigma and implementing a different perspective and outlook into how you view. [00:14:52] Brent Grimes: Yeah, yeah, happy to do that. So it was a journey, we figured things out, but we had to bump our heads a few times before we really did it, right? And the cost was like the team, we knew we had to use data better. We knew we had to get smarter, work smarter, not just harder. Right. We had an amazing team who could do heroic things, but they just didn't have bandwidth to be heroic in every account, right. So we really owed it to them to help them, give them the tools to help them really focus and prioritize. And we thought the way to do it was, well, if we put a good CS platform in and there's all these cool things we can do to be better with our customers. And so I think one of the toughest learnings we had is we got all excited about technology and we said, okay, there's all these things we can solve with this technology. Right. But what we didn't appreciate was if you think about, in one or two instances, what spinning up automated activities might do, it might make sense on the surface, right? But when you start to scale that across a team of dozens and eventually hundreds, and you think about at scale, it spins up all this activity and creates what I call a graveyard of guilt that's just sitting out there, making people feel bad about all the things that they haven't done that have been assigned to them. And then ultimately, they just reject the system. Right? They get to a point where it's too much and they stop relying on that method and they go back to their own instinctual way of prioritizing where they spend their time and they end up spending time with the squeaky wheel customers or the customers they like, but not necessarily the ones that really need the investment. So we had a failure. We tried to roll out a system and the team ultimately rejected it, right, and then we did another attempt and we did a little bit better, right, because we really scaled back and we said, okay, we're just going to focus on a few simple things and it did better, but it still never really got us there. And then we just said, look, we're going to approach this differently. We're going to rely on salesforce as our system of record and our CRM as our system of record and customer data capture. We're not going to have them capture data in multiple places and then we're going to get really good at pointing them in the right direction. And that's where we did the whole analysis exercise that really turned into this next generation of our approach. That, again, made the team happier because they were spending less time entering data and less time kind of running around trying to chase just activity based, busy work. And they knew exactly what was important and what was expected of them. Right. And it just turned out to be a much better model and that was really the inspiration for Reeve. Man. Amazing. [00:17:50] Adil Saleh: It's all about pivots, smart pivots that you do and you fail early, you fail fast. And that's how that's a part of the game. And that's all the technology is all about. You got to make sure you keep knocking the door at all times. [00:18:04] Reef.ai: An Automated Customer Success Platform for Post Sales Teams [00:18:04] Adil Saleh: So now one question, since we have spoken so much to these Vpfcs and that's why we are throwing these questions. I'm sorry if you're getting overwhelmed or it's landing so basic or generic for you, but I would love for you to address these. We hear VPs of CS super reluctant on choosing on a technology that is going to give them, let's say a VP of CS needs a reporting dashboard. He doesn't care about how the metrics for his customer success manager, how is managing the book of businesses, how is creating his custom view, staying on top of touch points, having actionable insights or retention reporting, all of those things. So how REIT stands as a standalone platform for a CS organization starting from VP of CS to a Customer Success Manager that is managing a book of business, let's say 2030 customer. [00:19:06] Brent Grimes: Yeah, happy to jump into that. So I do think it requires a little bit of a leap of faith in terms of letting go of this idea that you need a heavy customer success platform. Right. I think once you embrace that, there's an opportunity to say, okay, maybe there's not a need for us to have a separate source for entering data about customers and maybe we can rely on what I talked about before. There's a lot of existing machine generated data that is actually a better predictor of priorities than a lot of the human input data. So if you can embrace this model and say, look, we are actually going to go a different direction and go down this road of what we call kind of an automated customer success platform or really customer platform. Right. Because in our model, it's not just CS teams using this, it's account managers and renewals managers. The whole idea is you don't work with existing customers as an individual, you work as account teams. Right. And I think this is one of the nuanced differences that I talked about in terms of there's stark differences between new customer acquisition and managing and growing existing customers. And the teaming aspect is a big part of this. Right. So Reef is not a functional based system. It's really meant to bring these cross functional teams together to work in service of the customer. So the idea is that why implement something that's going to create a big burden on the team? When you can connect a system like Reef that will automatically score your customers, give you visibility across a bunch of different data sources, whether it's product, telemetry or marketing engagement or support engagement, and make sense of that and help you understand where those opportunities are and where those risks are. And then also allow you to then prioritize and then drive workflow based on the decisions that you make as an individual. That's a bet that we made, is that it's not about automating a bunch of activities, it's about putting the intelligence in the hands of the individual CSMS, the managers, the executives, allowing them to see, okay, here are the customers that are consuming at the highest level. And not only today, but we're predicting where they're going to be by the end of their contract. And here's customers that are ripe for growth. So I'm going to drive my own workflow, set my own priorities, whether I'm an individual or maybe a manager that's doing it for their team to say, okay, based on the intelligence that I've discovered, here are my priorities for the next two weeks in terms of things that are going to move the needle, in terms of net retention. Right? Or on the other side, here are some risky customers that are under consuming. Let's not wait until we get to renewal. Let's actually get in there, make sure that we're driving new use cases, getting them achieving value, so that we can have a good conversation when we get to that renewal period. So it's really this idea of embracing this lighter weight, exception based model that includes both the visibility and the accountability and allows you to lean on the data that you already have. Cool. [00:22:10] Adil Saleh: And then it can stay as a source of truth for post sales teams, be it account manager, all these CS team support teams, they don't have to move back and forth between the CRM and platform like Reef. [00:22:28] Brent Grimes: Exactly. It consolidates everything into both a 360 degree view of each customer to understand, okay, can I get a complete picture across revenue and sales information? I can look at their product engagement and consumption information, I can look at pipeline opportunity, I can look at support information and history and understand is there risk related to support or marketing engagement. So you get the full picture. You can also zoom out and look at segments of customers. So cohorts of customers. You can look at an individual territory, you can look at a region or an industry and visually understand which are my high performing customers that are ready to grow, which are my at risk customers, which are the ones in the middle and make those really quick decisions and understand the forest as well as the trees. [00:23:17] Reef.ai's Data Integration Practices and Cost Model [00:23:17] Adil Saleh: Very interesting. [00:23:18] Adil Saleh: And you mentioned product use insight. Of course it's going to be an integration. So how easy is that process? Is that plug and play? Because that's one question that these have. What they say that along with us talking to the co founders and talking to these decision makers, we need a data Ops team. We need someone technical that can help us integrate the right data field to be able to successfully integrate the product unit insights, which is a very vital part when managing the lifecycle of the customer. [00:23:52] Brent Grimes: Yeah, that's a great question. It's one of the things I'm most excited about, too. So I spent a lot of time in the integration API space, right. So MuleSoft, I've seen the good, bad and the ugly in terms of integration projects. And I think it's one of the things that's made it really difficult for platforms like this historically is that traditionally it's been kind of cumbersome and difficult to do the data connectivity. So there's been a lot of advancement over the last five years that has really lowered the bar and made it much faster and easier to connect to a lot of different data average. So we have pre built connectors to most of the source data. Right. So CRM. So think salesforce and HubSpot and others think product telemetry. So if you're feeding your product data into pendo or heap or amplitude, we can pick it up. We can also just connect directly to your product data warehouse. So whether it's feeding into an S, three bucket or BigQuery, it's actually very easy for us to get read only access to the data that we need and ingest product data that way. Right. Pulling in just one moment. [00:25:01] Adil Saleh: Brent, while you're speaking about are you speaking about native integration via script? [00:25:07] Taylor Kenerson: Via so it's just essentially we are just taking the data from its current source, right? So if it's Salesforce, we're just connecting in a read only fashion into Salesforce, you would just give Reef permission to connect into your Salesforce entrance instance. We would pull everything and then we do all of the transformation mapping to the Reef data model. If you have Zendesk for support, same kind of thing. Right? And then on the product side as well. So we have pre built connectors to pendo and amplitude and heap. But even if you aren't using one of those aggregators, we can connect directly to your product data warehouse. And again, the difference is we do the heavy lifting in terms of the integration. So you give us essentially either API keys or permission to connect to your system, and then we will do the first cut at that mapping, do a validation step with you to make sure that we're interpreting things the right way. But our typical data onboarding process is about two to three weeks and it requires about one to 2 hours of investment for our customers. [00:26:16] Adil Saleh: Is that from someone technical on your customer side, like data ops team engineer? [00:26:21] Brent Grimes: It's typically like an operations person that kind of understands the way that their systems are set up. If we do need to go directly to, let's say, a product data warehouse, then we might work with someone on the product side to make sure that we're getting the right permissions and getting access to the data in the right way. [00:26:38] Adil Saleh: Got you. And is there any sort of fee for this hands on onboarding where you're doing the heavy lifting? Yeah, we have catalyst, I guess, charging for it. [00:26:49] Brent Grimes: We have a very modest implementation fee for if you have kind of standard connectors and then if it is a more custom data integration, then there's a small fee on top of that. But again, it's a drop in the bucket in terms of the overall cost model. Just something to make sure that we have some basic resource coverage during the implementation phase. Got you. [00:27:12] Adil Saleh: I appreciate your answer on that because a lot of these folks that come up asking these questions and I've been on the other side have my responsibility get those answered. [00:27:20] Data Security as a Priority for Reef.ai [00:27:20] Adil Saleh: I have one last question. You can go on with that. Taylor. Last question is regarding your entire data structure at the back end. We know that a lot of these customer success tool, we also a technology company, they don't go with the sock two right from first year or starting off. So since you're capturing data natively with these customers, are you guys planning on having SOC 2 Type or you already have this license? [00:27:51] Brent Grimes: Yeah, so we are SOC 2 Type, type two certified, and it's an investment that we made very early on. I mean, frankly, based on the data that we're getting access to, it's kind of table stakes for us. And we don't just work with very early stage startups. Right. We have customers that are late stage startups, 7100 million dollar arr who are very serious now about data security and have their own requirements. So in order for us to be in the game, we had to make that investment early. And we have a very strong, my co founder Corey has a very strong background in data security and has been kind of leading the charge and just our whole development philosophy is not just building for today, but really building for scale and building with security in mind. Right. [00:28:50] Adil Saleh: Amazing. [00:28:51] The Future of Customer Success in Startups [00:28:51] Taylor Kenerson: And just one more question before we wrap. We've asked this to a lot of people, Brent, but really curious to get your two cent here, what advice would you give to someone that wants to embark on their own startup journey? And based on your experience, what would you say to people that are interested in taking this journey, maybe starting their own product or joining a team at a very early stage? [00:29:20] Brent Grimes: Yeah, so for me it's really finding something that bothers you or that you feel is broken or missing and just not letting go of it. Right. And I think the scariest part is, okay, you think that there could be something better out there or there's a gap or an opportunity, but it's scary to think about. Okay. How do I take that first step or how do I get started? And I'm a huge believer for my whole life. My philosophy is that if you're passionate about something and you believe in something, you owe it to yourself to just take that first step. And then even if you don't know where it's going to go, the road will open up in front of you and all of a sudden you see more of the path and you have these options. It seems big and scary if you try to think about all the steps down the road, but if you really just were convicted about taking that first step and it may not lead exactly where you thought, but it's still going to be an awesome experience that shapes who you are as you develop. So I'm a huge believer in taking the leap and life will take care of the rest and you'll figure it out. And if you grind hard enough, you're going to make something of it. [00:30:30] Adil Saleh: You want it bad enough, you'll get it someday. [00:30:33] Brent Grimes: Yeah. And then I think if I think about how that's applied, then it's kind of an interesting time for customer success. I know there's a lot of this is a customer success kind of friendly podcast. And it's a weird time in customer success because there's a lot of layoffs, there's a lot of even teams being let go. So I think we're at this inflection point in customer success where we've seen generation one of customer success, which is what I would say I talked about is the kind of linear customer success model which is, hey, we're moving from a model of licensed sales where you can sell to a subscription base and not have to care about what happens post sale. And now you have to care, right? So one way to handle that is just cover every customer, make sure things don't fall through the cracks. And I think what's happened now is companies like Salesforce and Snowflakes and others have sent a message to the market that's like, look, that model is no longer viable as a cost model, right. And we have to get more resource efficient in terms of the way that we think about customers. And I think it's scary in some ways, but I think it's actually a really big opportunity because if you think about SaaS, really, the number one metric that's an indicator of the health of a SaaS business is net retention. Net dollar retention is more important than probably anything else that a company can measure. But if you think about it, in most organizations, there's not someone that really owns that net retention number, right? You have maybe a sales leader that owns the growth side of things. They may own renewals. You may have a customer success person that owns renewals, right. But I think there's an opportunity for customer success to really step up and understand net dollar retention at a nuanced level and really be the expert for their organization to drive both understanding of net dollar retention as well as performance around net dollar retention that will attach customer success to something that is absolutely mission critical in a company. So I think as this next generation of customer success comes to light, I think the more that customer success can lean into being the expert and the owners of net dollar retention within their organizations, that's going to be a place that is going to be critical as companies grow and scale that's not easily kind of removed or cut back because there is such a hard tie to company success. Right. So I think it's an exciting time. So I think the more that individual practitioners and customer success and managers can invest in really starting to understand the mechanics of net retention and how what they do day to day really drives impact and even measure their ability to impact net retention. I think that it's going to set the customer success industry up for a really good next phase of growth and maturity and really establish a long term position as a kind of high leverage stakeholder in the company. Absolutely. [00:33:42] Brent Grimes: New wave of CS. [00:33:44] Taylor Kenerson: Yes. [00:33:44] Adil Saleh: And we'll have more startups like Pickup that will raise good amount of funding to fuel their marketing. Because at this time this past year, including later half of last year and this one, this has been the hardest time what I've seen when it comes to VCs and raising funds. It's been pretty tough time on startups. When they focus on measurable steps towards net dollar retention, that solves the game and that's going to be the next game. I agree, for sure. [00:34:16] Taylor Kenerson: Absolutely. [00:34:18] Insightful Conversation with Brent Grimes [00:34:18] Brent Grimes: Thank you so much, brent, we so appreciate you and the time that you decided to take with us today. And we can't thank you enough for all the insights you shared. Thank you. [00:34:27] Adil Saleh: Absolutely. I love the energy. And thank you very much for being so genuinely insightful. [00:34:33] Taylor Kenerson: Yeah, thank you. Really good to chat with you guys. Enjoyed it and I hope all your listeners do too. [00:34:39] Brent Grimes: Thank you, Brandon. [00:34:40] Taylor Kenerson: Have a beautiful day. You too. Bye.

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