The Reef Current

There’s a lot of noise around AI agents these days. But when I talk to executives, it’s clear that most companies are just starting to dip their toes in AI waters. They’re eager to explore the potential but uncertain about how to get from their current state to a fully realized, AI-agent-led future. And there’s a paradox: while leaders are feeling the pressure to cut costs and do more with less, they’re simultaneously asked to drive higher revenue performance. As a result, we see ambitious plans built on assumed productivity gains from AI—but often without a realistic blueprint to capture those gains and no clear plan to fund it.  For those companies that aim to reap real, outsized benefits sooner and more predictably, achieving an AI-agent-driven future won’t happen by chance. It’ll require a targeted approach, grounded in strategic execution, data, and iterative learning. And where near-term revenue gains can fund this investment in AI, those opportunities should be prioritized.

Brent Grimes on the TECHtonic podcast, hosted by TSIA

Brent Grimes, Founder and CEO at Reef.ai joins the hosts ⁠⁠Kristi Faltorusso⁠⁠, ⁠⁠Jon Johnson⁠⁠ & ⁠⁠Josh Schachter on the Unchurned Podcast⁠⁠. Brent shares insights on outcome-based scoring for customer health and the power of leveraging data for predictive modeling in customer success.

If you’re relying on a general health score to run your business, you’re leaving substantial retention and growth revenue on the table. In the world of Customer Success, Account Management, Support, and Services, traditional health scores have long been the go-to metric for assessing customer relationships. We’ve all used them. Sometimes successfully, and other times, with mixed results. These conventional metrics often fall short. Not due to lack of intent, but because their broad strokes fail to paint the detailed picture needed to drive specific actions and outcomes. Why are Traditional Health Scores Dead? As a seasoned CS leader, I've grappled with the shortcomings of traditional health scores more times than I can count. While they seem promising on paper, they often struggle with: Accuracy: Are "green" customers *truly* never churning? Are "red" customers *always* at risk? Actionability: A general health score of 62 doesn't inherently tell you what actions to take. Impact Measurement: How do we know if our interventions *actually* made a difference? While traditional health scores may have a time and place, the industry is quickly evolving to ML-powered Outcome-Based Scoring. What is Reef’s Outcome-Based Scoring? At Reef, we've pioneered a more nuanced approach that aligns closely with driving specific revenue outcomes: Outcome-Based Scoring (OBS) . This method represents a shift from a generalized score to multiple, highly tuned ML-powered scores tailored to specific challenges and opportunities within customer management from churn mitigation to growth. Instead of relying on one holistic score that attempts to do too much, we're developing targeted scores backed by data science and tied to specific revenue outcomes. It's like having a suite of specialized tools instead of a one-size-fits-all approach. What are Some Outcome-Based Scores in Action? Our data scientists are constantly experimenting with different machine learning models to optimize for each revenue outcome. Let's dive deeper into three examples: Big Deal Finder: Reef analyzes your best customer expansions over the recent past to identify common traits among customers who expanded. Based on these learnings, Reef isolates current customers who share these traits and are likely to produce more growth pipeline that converts at a higher rate and closes at a higher rate for a higher sales price. Reef feeds targeted leads to Sales and CSMs and delivers ABM targets to Marketing. Churn Predictor: While many companies have moved towards churn prediction models, Reef automates recommendation delivery, keeps the model up-to-date, and continuously improves the model over time. It provides CSMs and Renewal Managers early warnings about potential churn, allowing for preemptive action. Product Downgrade Blocker: Some companies don’t have a full churn problem, but struggle with partial churn or downgrades of specific products. Reef can optimize a model to predict these downgrades and alert the right team member 6-9 months in advance of renewal, while there’s still time to change the outcome. 

When you found a startup, you get to worry about a lot of things. One thing that was not on my radar was what to call Reef.ai employees. Now that we’re here, it’s actually a pretty big decision. It creates identity, community, and has a direct influence on company culture. And once you commit, it’s really hard to change course. At Reef.ai, we had some unique challenges. We’re an AI/ML SaaS business based in Hawaii and we wanted something that captured our culture. The most obvious names had alternative meanings that made them interesting but not ideal choices. (See “Reefers” and “Polyps”) Then we came across “corallites”. What are corallites, you ask? If you’ve ever touched a coral reef, you probably noticed that beneath the anemones, polyps, urchins, and other sea life, there is a hard, stone-like framing that gives the reef it’s strength. These are corallites. Corallites are created by polyps and become a safe home where they can escape from danger. We like this analogy. Reef customers create the need for Reef employees and we provide a safe place where their customer data can help them grow. A reef starts small, often a single corallite. Then, other corallites form and multiply. The reef grows bigger and bigger, not just supporting polyps but creating an entire ecosystem of life around the reef. 5 reasons why we like corallites as a name for Reef.ai employees: 🪸 Corallites grow and connect to become the reef. A single corallite is the original building block of a reef. Additional corallites connect and begin to form a reef. They all build and grow together until there is a rich, thriving ecosystem. This is the story of Reef.ai. 🪸 Corallites sounds a lot like correlates. We’re nerdy, we ♥️ data, scoring is a Reef core value prop, and correlation is a big part of ML scoring. It just fits. 🪸 Corallites are strong and adaptable. A reef’s environment is always changing, and a reef has to quickly adapt to thrive and grow. When we hire new corallites, adaptability is one of the key traits we look for. 🪸 Corallites are secure. Corallites protect life in a reef from predators. Connecting, improving, and creating data is at the heart of what Reef.ai does for our customers. We take keeping it secure seriously. 🪸 Corallites are fun. Or, so we’ve heard. :) So now, we’re not just Reef.ai employees, we’re Corallites! Interested in becoming a Corallite? Follow us on LinkedIn and DM us. We're hiring.

The healthscore serves as a common foundation for customer success strategies, yet it is often misinterpreted and mishandled due to a lack of recognition regarding the challenges of effective customer scoring. Many individuals view a healthscore as a numerical or categorical (red, yellow, or green) assessment resulting from calculations involving various inputs, weighted according to their perceived impact on customer well-being. While this perspective isn't entirely inaccurate, it only scratches the surface. A customer score and its underlying scoring model are akin to the visible tip of an iceberg; there exists a substantial amount of work beneath the surface required to develop an accurate score that can be continually enhanced.

In all my years in customer success, sales, and presales roles, the best performing territories with the most successful customers in the top performing companies all had something in common. They absolutely nailed account teaming. Teams didn’t just work well together, they codified how they worked together, they defined and embraced their roles supporting the customer, and they held each other accountable. It was music and their customers thrived. Why invest in account teaming? Because better account teaming equals better net retention. A 2021 McKinsey study showed that the top SaaS companies prioritize net retention and invest as much into existing customers as acquiring new customers. Exceptional account teaming doesn’t happen by accident. In fact, the reason it’s a competitive advantage is because it’s not very common. Most organizations invest a lot of time, resource, and technology into operating well within a function but invest very little in working well across functions. There is often a lot of discussion about how it needs to get better, but very little real action or investment to make it better. Do you agree? Is good account teaming really important or is it overrated? Here is a simple framework for effective account teaming: Document your common objectives. Start with how your customer defines success and derives value. Then included how success is measured for account team members, collectively and individually. Objectives can include customer adoption or value realization goals, ARR growth and retention goals, etc. Clarify your roles. One of the hardest things to get right in account teaming is making it clear what everyone’s roles are. Roles should be clear to other account team members and more importantly, to customers. Align your team members with customer contacts and strengthen independent relationships. Codify who does what, when. Account teams will work together on lots of different actions with customers. These actions can be organized into thematic playbooks for objectives like mitigating churn risk, increasing engagement, building growth pipeline, onboarding new customers, etc. A specific team member may be primarily responsible for an objective but multiple team members will contribute actions towards the objective. Track progress against objectives and make it transparent. Codifying a playbook is a great start. Keeping track of who has done what and what is left to accomplish is also critical to consistent execution and scale. Transparency creates natural accountability because individual team members don’t want to let the team down so they make sure their actions are done. Review and improve . Meet on a regular cadence to review your customer and individual objectives, review status against active playbooks, and to discuss individual customers. It is important to create an environment where people can be open and honest about what’s working and what’s not working. Teams with a high level of trust that can be honest with each other, will perform better. How does this “music” appear in real life. Imagine this, a CSM notices a new pipeline opportunity for an existing customer, Globex Corp has been created. The CSM digs in and sees that there has been a stagnation in adoption by Globex and their overall engagement level has dropped in the past quarter. The CSM, AM, and presales engineer meet to flag the pipeline risk and agree on a plan of action. They agree that the CSM will lead an adoption boost sprint to rebuild momentum with the customer and get their consumption moving in the right direction. Once that’s accomplished, the presales engineer will lead a value analysis sprint to prove current value and project future value as Globex grows on the platform. Then, and only then, the AM is in a strong position to lead an expansion sprint to capture the value that’s been created in the form of additional ARR. This is the type of interaction and coordination that makes a great account team. If you like this framework, you can get started immediately. Get together as a team, discuss the 5 principles of the framework and decide and document how you’re going to work differently. Most technologies focus on solving problems within a function. Reef was purpose-built to build bridges across teams for exceptional account teaming. Reef cuts out busywork and focuses your teams on what matters most: customer outcomes and net retention. If you’d like improve your account teaming, we’d love to talk to you and show you Reef. It’s lightweight and easy to get started.

Stuck in the past Since the early days of CRM in the 90’s, activity management has evolved remarkably little. Tasks still have notes and due dates. The workflow to assign them has gotten a bit fancier but very little has changed otherwise. I’ve worked for or with CRM systems over much of my career. And I don’t ever remember a time when activity management worked well. For a few, small scale projects, the process of defining, assigning, monitoring, and reporting on activities allowed us to keep tabs on what was getting done but it took a lot of work and we never had a good grip on whether the activities were actually effective. There’s got to be a better approach. Step 1: Learning from the product world One of the major failings of activity management is that activities are not really time-bound. They have due dates, but when that due date passes, the activity lives on, possibly showing up on a “naughty” report but otherwise it’s likely piling up with other tasks to create a mountain of unresolved guilt for whomever is responsible. Individual tasks lose their importance as human nature kicks in and users stay as far away from the mountain of guilt as possible until their manager steps in. There is a much better approach and it’s already widely used, just not on the go-to-market side of the house. Product orgs learned long ago that by embracing agile principles and organizing activities into time-bound sprints is a much more effective way to set priorities, assign actions based on those priorities, and track those actions to completion. When a sprint expires, actions are not allowed to hang out in the ether unresolved. Actions must be closed or reprioritized and included in a future sprint. This prevents actions from piling up and losing their focus and meaning. Step 2: Quantifying the impact of actions The biggest opportunity to improve activity management is by helping organizations not only understand whether actions are being completed but understanding how strongly the completion of those actions correlate to important business metrics. The traditional approach to activity management completely misses this. It’s all about “did it get done” and not about “did it work”. By capturing a before and after picture for every customer who is the recipient of an action, you can begin to correlate which actions actually move the needle and which actions are a waste of time. New levers for activity management The combination of organizing actions into time-bound sprints plus quantifying the impact of actions and sprints, enables a new, more effective set of levers for activity management. First, there a core set of metrics that emerge: Completion rate ARR ▵ Pipeline ▵ These metrics enable visibility and understanding that didn’t previously exist. You can begin to answer the questions like: Is performance low because: A. The completion rate was low and people did not follow through on their assigned actions? or B. The completion rate was high but the actions did not have the intended impact? Understanding this will inform how to coach your team to improve performance. If “A”, then the team needs to focus on prioritizing and following through on their assigned actions. If “B” then you need to assign different, more effective actions in the future. Additionally, you can view and rank all actions by their correlation to important metrics. Then you can identify the most impactful actions and ensure that your team performs more of the actions that work and less of the actions that don’t. Summary Everyone wants to feel like the work they do makes a difference. The impact of Customer Success individuals and teams no longer has to be vague or ambiguous. With Reef, CS teams can: • Stop wasting time on low-impact actions • Focus on actions that matter • Measure the impact of what they do

I’ve been in customer success for a long time, even before it was called customer success. Prior to the customer success movement and the rise of recurring revenue, there were roles and functions designed to support customers, but they were piecemeal and largely reactive versus proactive. Reactive to Proactive So, when SaaS became a thing and the recurring revenue rose from niche to “the future”, companies realized that they had to do better and customer success was born. It made a lot of sense. Just like businesses used systems to operationalize their approach to sales, marketing, and product development, they needed to operationalize the ongoing management of their customers. They were in it for the long haul and they no longer had the option to sell and run away. Mutual success required that a customer realized value and renewed year after year. As a result, companies needed a dedicated team to be responsible for the ongoing health of customers and they needed systems to support those teams. Software for Customer Success When customer success started, CS teams didn’t have the right tools. Traditional CRM systems were great for customer data capture but they weren’t designed to support the nuance and complexity of managing a customer lifecycle over time. So, the first customer success focused software solutions emerged. These systems defined many now standardized processes and best-practices for managing a customer journey and ensuring customers realize value and renew. It was a huge step forward. It created a common framework for engaging customers over their lifecycle and it looks something like this. You’ll probably recognize it. Most customer success solutions in the market today prescribe a similar approach.