Rethinking Customer Success: Beyond Lifecycles, Toward Motion

Why I'm Writing This

This article is part of a broader journey: as I work toward deploying a functional AI agent for Customer Success, one that doesn’t just automate tasks, but understands and supports the real motion of CS work, I’ve had to step back and redefine how I see the discipline itself. This series documents that process. It’s part exploration, part blueprint. And it starts here: by rethinking what Customer Success is really trying to do.

Customer Success (CS) has become one of the most critical disciplines in modern SaaS and B2B business models. Customer Success Managers are tasked with everything from onboarding and adoption to expansion and retention. Yet despite this scope, the frameworks we use to define CS are still limited, stuck in outdated paradigms that don't reflect the complexity or the opportunity of the role.

Traditional frameworks lean on lifecycle stages: Onboard, Adopt, Mature, Renew, Expand. They look neat in a deck and they’re not wrong, but they carry three flawed assumptions:

• Linearity: One stage cleanly hands off to the next.

• Finality: “Adoption” or “maturity” is something you finish.

• Uniformity: All customers travel the same road, just at different speeds.

In a world of single-SKU SaaS circa 2010, that worked. In 2025, most vendors are platform-based. They span multiple products, personas, integrations, and goals. Real journeys branch, loop, and collide.

Adoption isn’t a phase, it’s a heartbeat. Stop hearing it, and your deal flatlines.

When CS teams organize too rigidly around stages, we see predictable problems. Click to explore a few of the most common patterns.

Seven Pitfalls of Stage-Locked Customer Success

1. Stage Myopa

• How it shows up: declaring onboarding complete once the tech is live regardless of value

• Consequence: early churn; shallow usage

2. Renewal Crunch

• How it shows up: Starting value storytelling 90 days out from renewal

• Consequence: fire-drill discounts; lost ARR

3. Zombie Metrics

• How it shows up: teams celebrate logins even if workflows stay broken

• Consequence: false sense of health; surprise escalations leading to churn

4. Change Blindness

• How it shows up: customer strategy shifts, but the success plan doesn’t

• Consequence: misaligned outcomes; sponsorship loss

5. Persona Drift

• How it shows up: CS stays focused on initial users or champions, even as new decision-makers emerge

• Consequence: renewal blockers; invisible objections

6. Automation Without Judgment

• How it shows up: rigid playbooks run on stage triggers, not customer reality

• Consequence: irrelevant outreach; customer frustration

7. Lifecycle Paralysis

• How it shows up: teams wait for customers to “reach the next stage” before acting

• Consequence: missed opportunities for help, upsell, or recovery

These pathologies aren’t just theoretical, they’re distilled from the real challenges voiced by CS practitioners across the industry. What’s new here is the structure: a shared language to diagnose them and a foundation to move beyond them.

I understand the intent behind lifecycle models, which is to create scalability and repeatability, but the current templatization often flattens the rich, nonlinear, human experience of driving value.

I needed a model that accounted for the real, fluid motion of CS, not just the map but the movement. That’s what led to the CS Motion Framework. It had to be more than a response, it needed to act as a safeguard. A system that not only addresses these challenges, but actively prevents them from becoming embedded in how CS teams operate. It doesn’t replace lifecycle thinking, but it exposes what really drives it: the ongoing, dynamic loop of pulling insight and pushing progress.

The Need for Motion

I propose a shift: away from stages and toward motion. Customer Success is about driving movement. Not just movement through a journey, but movement in capability, in behavior, in organizational change. This is where the real value lies, in helping customers move from where they are to where they need to be, from a clearly defined current state to a measurably improved one.

This idea of motion brings with it a fundamental reorientation:

• From milestones to momentum

• From static models to dynamic systems

• From outputs to outcomes and eventually to income

  
  

To operationalize this, I introduce a new construct: the CS Momentum Loop.

The CS Momentum Loop: From Input to Income

Imagine a loop that moves through four stages (fig.1):

1. Input - the investments made by both CS and the customer: time, resources, attention, decision-making, change management. These are the seeds.

2. Output - the immediate, observable results of these inputs: completed onboarding, features deployed, users trained, metrics tracked. These are the activities.

3. Outcome - the actual business impact: increased efficiency, better customer experience, reduced churn, improved performance. These are the reasons the product exists.

4. Income – the financial manifestation of outcomes. This includes:

   • For the vendor - expansion revenue, renewal, increased product usage: the direct commercial returns.

   • For the customer - realized ROI: whether that’s time saved, costs reduced, productivity increased, or risk mitigated. Income is not just what comes back to us, it’s also what accrues to them.

The brilliance of the loop is that when value is realized, when income occurs, it enables reinvestment: new inputs. The cycle continues. Momentum compounds.

Time-to-Value in This Model

A key variable here is time. Specifically:

• Time to Perceived Value: The moment the customer feels progress or benefit, even if informal.

• Time to Quantified Value: When outcomes are measurable, e.g., efficiency improved by X%.

• Time to Financial Value (Income): When ROI is realized and recognized.

CS plays a critical role in accelerating all three, but especially in managing the lag between output and outcome.

Defining the Work of CS: The CS Input Model

If motion is the goal, what does CS actually do to create it?

What we call “Customer Success” is often a blend of conversations, analysis, alignment sessions, and project nudges. But if we want to build systems — human or machine — that truly support this work, we need to define it more precisely.

That’s what led me to the Input Model.

At its core, the Input Model reframes CS activity as a library of meaningful actions, not just tasks or updates, but deliberate motions that move the customer from one state to another. These inputs are selected, sequenced, and adapted based on the current context, it's a real system of motion. And the key insight is this: not all motion is equal.

Some inputs are pull actions, designed to gather insight, uncover friction, or validate understanding. Others are push actions, intended to move the customer forward through enablement, influence, or structure. These motions happen across two domains: people and data, and the combination is what fuels momentum.

But what makes the Input Model powerful isn’t the list, it’s the intelligence behind it. A CSM, or an AI assistant, can’t just choose actions randomly. The real value comes from sequencing: choosing the right motion, at the right moment, given where the customer is and what they’re trying to achieve. This is where experience and context or in the case of automation, intelligent orchestration, matter most.

That’s what transforms the Input Model from a playbook into an engine. Each selected action contributes to the CS Momentum Loop driving outputs, outcomes, and eventually income. But choosing that motion depends on knowing where the customer is now, and what kind of value is possible next.

That’s where the Enhance x Increase Matrix comes in.

Mapping CS Motion: The Enhance x Increase Matrix

Before introducing the matrix, it's worth recognizing that Enhance and Increase are not just labels, they represent real decisions customers make and investments they commit to.

Think of them as two axes on a map:

• Enhance (vertical axis) - deepening usage: making what’s already deployed more effective.

• Increase (horizontal axis) - Expanding deployment: more products, features, or licenses.

  
  

This isn’t just a static map based on anecdotal inputs or surface-level segmentation. The Enhance x Increase Matrix should be powered by deep insight, built from a wide range of behavioral, transactional, and contextual data points. Its relevance depends on robust data synthesis: usage patterns, stakeholder behavior, support history, outcomes achieved, and even sentiment trends. As the directional entry point of the CS Motion Framework, it needs to be both strategic and grounded in evidence. Only then can it reliably guide where effort should be focused to drive value.

Plotting customers along these two dimensions helps us visualize where they are, what kind of support they need, and where the opportunity lies. Both are needed to create value. But in practice, many organizations prioritize Enhance before they consider Increase. They want to see existing investments deliver results before expanding further.

The Enhance x Increase matrix helps us prioritize and identify opportunities:

CS aims to move accounts diagonally upward, from their current state to a more advanced one, deploying more where it makes sense but, more importantly, ensuring usage drives real outcomes. This motion feeds the CS Momentum Loop, and each iteration of the loop helps drive the trajectory upward through the matrix (fig. 3).

A New Foundation for CS and for AI

As we build more sophisticated systems, including AI agents to support or even automate aspects of CS, we must start with clarity.

You cannot automate what you haven’t defined. You cannot scale what you haven’t mapped.

This motion-based framework provides that clarity, it's both the blueprint and the guiding principles.

Together, these components form the CS Motion Framework: a blueprint, a compass, and an engine built not just for teams, but for machines too. The Enhance x Increase Matrix helps systems understand where value lies, the Input Model defines the actions that drive it, and the Momentum Loop explains how it builds over time. It’s a structure that humans can lead and AI can learn.

In the next articles, I’ll break down each component: the Input Model, the Matrix, the Loop in practice, how AI could support the next evolution of Customer Success, and what I’m building to make that support real.

If you’ve ever felt that traditional CS frameworks don’t reflect the depth and complexity of your work, this new approach might be the clarity you’ve been seeking.

Let’s stop managing stages. Let’s start managing motion.