Tag Archives: growth

The revenue leak starts after the sale

Most SaaS founders know revenue is leaking somewhere.

They can see it in the numbers.

Renewals are harder than they should be.
Expansion is slower than expected.
NRR starts to drift.
Customers look fine until they suddenly are not.

So the business looks at the usual suspects.

The renewal process.
The onboarding journey.
The sales handover.
The health score.
The CSM cadence.

All useful places to look.

But often, they are not where the leak starts.

The leak starts earlier.

It starts the moment a customer signs and nobody clearly owns whether they achieve what was promised.

The deal is not the outcome

A signed deal feels like progress.

And it is.

But for the customer, nothing has been realised yet.

  • They have not bought a contract
  • They have not bought access to software
  • They have not bought an onboarding plan

They have bought an outcome.

That might be faster reporting, lower risk, reduced manual work, better visibility, higher productivity or stronger revenue performance.

Whatever it is, someone inside your business needs to own whether the customer gets there.

  • Not loosely
  • Not culturally
  • Not “the team”

Actually own it.

Because when everyone owns the customer outcome, nobody does.

Where the gap opens

The gap opens between what sales commits and what the customer experiences.

  • Sales sells the promise
  • Onboarding gets the customer live
  • Customer Success runs the cadence
  • Support handles the issues
  • Product tracks usage
  • Finance watches the renewal number

But who owns the customer getting what they paid for?

That is the uncomfortable question.

Because in many SaaS businesses, the answer is vague.

  • Everyone is involved
  • Nobody is accountable

And that is where churn starts to build.

  • Not at renewal
  • Not when the customer complains
  • Not when usage drops

Much earlier.

It starts when the business loses sight of the original promise.

Usage is not proof of value

This is where many SaaS teams fool themselves.

A customer can be onboarded and still not be successful.

They can log in and still not see value.

They can attend QBRs and still not believe the product is critical.

They can use the software and still struggle to explain the commercial impact.

Usage matters.

But usage is not the same as value.

Activity is not the same as progress.

A completed onboarding is not the same as a customer who has achieved what they were sold.

That distinction matters because renewals are not won by activity.

They are won by evidence of value.

Customer Success cannot fix this alone

When retention weakens, companies often assume they have a Customer Success problem.

Sometimes they do.

But often, they have a post-sale ownership problem.

Customer Success cannot fully own value if the sales promise was never captured properly.

It cannot prove impact if success criteria were never agreed.

It cannot drive expansion if the customer never reached first value.

It cannot rescue a relationship if the business treated the sale as the finish line.

CS has a critical role.

But post-sale value is not a department.

It is a commercial operating discipline.

That means sales, onboarding, product, support, finance and leadership all need to be aligned around the same question:

Did the customer get what they paid for?

A simple test

Ask five questions after every deal closes:

  1. What outcome did the customer buy?
  2. What did sales promise or imply?
  3. Who owns first value?
  4. How will we prove value has been realised?
  5. When will leadership know if the customer is off track?

If the answers are vague, you have found the leak.

Not a theoretical leak.

A commercial one.

The kind that shows up later as slow adoption, weak expansion, renewal risk and declining NRR.

The real ownership question

The best SaaS businesses do not treat the sale as the finish line.

They treat it as the start of the value obligation.

That is the shift.

From “we sold it” to “they realised it”.

From customer handoff to customer ownership.

From activity tracking to value evidence.

So the real question is not:

“Do we have a Customer Success team?”

Most companies do.

The better question is:

Who in your business owns what happens after the sale?

If the answer is unclear, that is where the revenue is leaking.

The AI Tourist Effect

There’s a number circulating right now that should make every SaaS founder and leader sit up.

AI-native SaaS products have a median gross revenue retention rate of 40%. For context, the B2B SaaS median is 82%. That’s not a rounding error – it’s a 42-point gap and it’s prompting a lot of people to conclude that AI-native products are fundamentally harder to retain.

They’re wrong. And the data proves it.

What “AI Tourist” Actually Means

ChartMogul coined the phrase “AI tourist” to describe what’s driving this churn pattern. Users sign up because the product looks interesting, the demo is slick and the pricing is low enough to not require a procurement conversation. They experiment for a few weeks, hit a wall – maybe the use case isn’t quite right, maybe a competitor ships something shinier – and they’re gone.

This isn’t a story about bad AI. It’s a story about how people buy things they don’t need to commit to.

When the barrier to entry is $19 or $29 a month, the barrier to exit is equally low. There’s no contract to navigate, no internal stakeholder who championed the purchase, no workflow that breaks if the tool disappears. The customer signed up alone and they’ll leave alone.

That’s the AI tourist. They came for a look around. They were never planning to stay.

The Price Point Data Is Striking

Here’s where the conventional narrative falls apart.

ChartMogul’s data segments AI-native SaaS products by price point, and the retention picture is almost entirely determined by what you charge – not what the AI does.

Products priced above £200 (roughly $250) per month see 70% gross revenue retention and 85% net revenue retention. That’s essentially the same as traditional B2B SaaS. Products priced between $50 and $249 per month see 45% GRR and 61% NRR. Products priced below $50 per month see 23% GRR – meaning nearly 80% of revenue churns out within a year.

Same technology. Same category. Entirely different retention profile.

The variable isn’t the product. It’s who’s buying it, how they’re buying it and what’s at stake if they stop.

Why This Matters for CS Teams

If you’re a leader at an AI-native company and your retention numbers look ugly, the temptation is to reach for customer success playbooks. More onboarding touchpoints. Better health score models. Proactive outreach at 30 days.

Some of that will help at the margins. But if your core problem is that you’re selling a $29/month tool to individuals who don’t have a business outcome attached to it, no customer success motion fixes that. You’re putting a retention programme on top of a churn machine.

The commercial diagnosis here is uncomfortable but important: the customer success function can’t compensate for a flawed go-to-market model.

What you can do – and this is where customer success genuinely earns its seat in the room – is make the business case for moving upmarket. The data is unambiguous. When AI-native products sell to genuine business buyers at $250+ per month, they retain like traditional SaaS. The AI isn’t the risk. The self-serve, consumer-grade pricing model is.

What Moving Upmarket Actually Looks Like

Moving upmarket isn’t just raising prices. It’s a set of decisions about who you sell to, how they buy and how deeply embedded your product becomes in their actual workflows.

A few things tend to shift when you go from self-serve consumer to B2B buyer.

There’s a procurement process, which means there’s an internal champion. That person’s reputation is partly tied to the tool working. They don’t cancel without a conversation first.

There’s an integration layer. Your product connects to their CRM, their Slack, their ticketing system. Ripping it out takes effort. Switching costs go up.

There’s an outcome attached. The business bought the tool to achieve something specific – reduce support volume, increase renewal rates, speed up onboarding. You can measure it. You can show progress. That’s the foundation of a genuine retention conversation.

None of this happens at $25 or £25 a month. It happens when the deal is significant enough that both sides take it seriously.

The Lesson That Extends Beyond AI-Native SaaS

The AI tourist effect isn’t just a problem for AI-native companies. It’s a warning signal for any SaaS business that’s drifted toward self-serve growth without examining the retention consequences.

The economics look attractive at first. Low CAC, fast time-to-revenue, no sales headcount required. But if you’re churning 60%-70% of revenue annually, you’re running a leaky bucket – and growth is just masking the leak.

The companies that will build durable NRR in this environment are the ones embedding themselves into critical business workflows, selling to buyers who have accountability for outcomes and building customer success motions that tie directly to measurable value.

That’s not a new idea. But the AI tourist data gives it a specificity that’s hard to argue with.

The Practical Takeaway

If you’re a customer focused leader in an AI-native company, here’s the question worth putting to your leadership team: are the customers we’re churning the ones who were ever going to stay?

If the answer is no – if you’re churning self-serve, low-ACV, low-commitment buyers at the bottom of your customer base – then the retention conversation needs to start with pricing and ICP, not onboarding sequences.

The AI isn’t the problem. The market motion is.

Get that diagnosis right and the customer success playbook becomes much more straightforward.

Want to Talk Through What This Means for Your Business?

If you’re a SaaS leader wrestling with retention in an AI-native product – or advising a company that is – I work with customer success and revenue teams to build operating models that hold up under board scrutiny.

Book a 30-minute conversation and let’s look at the actual numbers together.

Or follow me on LinkedIn where I write about this kind of thing every week – commercial customer success, retention mechanics and what’s actually changing in the post-sale world.

Sources: ChartMogul SaaS Retention Report – The AI Churn Wave (2025/2026); ChartMogul The New Normal for SaaS Retention

Most SaaS companies don’t have a sales problem – they have a value delivery problem

Your sales engine is running.

Pipeline looks healthy. New logos are coming in. Revenue targets appear achievable.

But your NRR is telling a different story.

Somewhere between contract signature and renewal, growth is leaking.

Customers are going live but not expanding. Adoption exists but commercial momentum stalls. Customer Success teams are busy, yet leadership still struggles to clearly connect post-sale activity to retention and expansion outcomes.

This is one of the most common problems in SaaS right now.

And most companies feel it long before they can properly articulate it.

Why SaaS growth leaks after the sale

Most SaaS organisations are heavily optimised around acquisition.

Sales, marketing and product investment often dominate strategic conversations because they are easier to measure in the short term. Pipeline growth feels visible. New ARR feels tangible.

Post-sale execution is different.

The warning signs usually appear gradually:

  • Renewals become reactive
  • Expansion becomes unpredictable
  • Onboarding drags
  • Customers stay “active” without achieving meaningful outcomes
  • Customer Success becomes overloaded with activity but commercially unclear

Over time, growth slows despite continued acquisition investment.

That is when leadership teams start asking harder questions about retention, customer value and operational efficiency.

The gap between adoption and customer value

One of the biggest mistakes SaaS companies make is confusing product usage with realised value.

A customer logging in regularly does not automatically mean they are successful.

Many organisations measure:

  • logins
  • feature usage
  • meeting volume
  • ticket response times

But customers do not renew because they attended QBRs.

They renew because the product helped them achieve a business outcome that mattered.

That gap between activity and realised value is where many SaaS businesses quietly lose expansion opportunities.

The strongest Customer Success organisations understand this clearly. They align onboarding, adoption and ongoing engagement around measurable customer outcomes rather than internal process metrics.

Why Customer Success becomes commercially unclear

In many SaaS businesses, Customer Success evolves reactively.

The function grows quickly as customer numbers increase, but ownership boundaries often remain vague.

Sales owns revenue.

Support owns problems.

Product owns features.

Customer Success ends up sitting somewhere in the middle trying to hold everything together.

The result is predictable:

  • unclear commercial accountability
  • inconsistent customer experiences
  • fragmented definitions of value
  • poor cross-functional alignment

This is why some CS teams appear extremely busy while leadership still struggles to see measurable commercial impact.

The issue is rarely effort. It is operating design.

We recently discussed this exact shift on our podcast Breakthrough SaaS Growth with The Jasons in our episode From Customer Success to Customer Growth – The Next Evolution of SaaS, where we explored why Customer Success is increasingly evolving into a commercial growth function rather than simply a post-sale support layer.

How AI is exposing weak post-sale execution

As I covered in my article on AI-enabled Customer Success, the companies gaining advantage are not simply automating support tasks. They are redesigning how customer value is delivered.

Not because AI itself is causing churn, but because it exposes operational weaknesses much faster than before.

Weak onboarding becomes visible earlier.

Poor adoption patterns surface sooner.

Customers expect faster time-to-value and more proactive engagement.

Companies that simply automate broken post-sale processes will struggle.

The organisations gaining advantage are the ones redesigning how customer value is delivered in the first place.

They are using AI to:

  • identify churn risk earlier
  • improve customer visibility
  • reduce onboarding friction
  • surface expansion opportunities
  • scale proactive engagement

But the technology only works when the underlying operating model is aligned around customer outcomes.

AI does not fix value delivery problems.

It exposes them.

What high-performing SaaS companies do differently

The strongest SaaS companies treat post-sale execution as a growth function, not a support function.

They align sales, product and Customer Success around shared customer outcomes.

They focus on:

  • faster time-to-value
  • measurable business impact
  • operational clarity
  • scalable customer engagement
  • retention and expansion as board-level metrics

Most importantly, they understand that sustainable SaaS growth does not break at acquisition.

It breaks after the sale when customers stop progressing.

By the time NRR starts falling, the underlying problems have usually existed for months.

Sometimes years.

That is why the companies outperforming right now are not necessarily the ones automating the most.

They are the ones aligning their organisation around realised customer value.

Many SaaS companies already know something is breaking post-sale. The challenge is diagnosing where the operational gaps actually sit.

That’s typically where a Customer Success advisor can help bring clarity.

Most SaaS Companies Don’t Need A Bigger Customer SuccessTeam

Why Hiring Another CSM Rarely Fixes Churn

Most SaaS companies respond to churn the same way.

They hire…

  • Another CSM
  • Maybe a Head of Customer Success
  • Sometimes a VP

It feels like progress, but it rarely fixes the real problem.

Because churn is not always a capacity issue.

More often, it is a design issue .

Infographic to download and save below…

The Real Problem

If your customer success function is not clearly driving retention and expansion, adding more people usually creates more activity.

More calls
More QBRs
More dashboards
More internal updates

But not necessarily better outcomes and often, no clear link to revenue.

That is where many SaaS companies get stuck.

They build a bigger customer success team before they have built a proper customer success model.

Where A Customer Success Advisor Fits

A customer success advisor does not simply add more hands.

They help fix the operating model.

That usually means:

  • defining what customer value actually looks like
  • aligning sales, customer success and product around that value
  • building a repeatable system for retention and expansion
  • creating earlier visibility of renewal risk
  • making customer success commercially accountable

This is not about doing more.

It is about doing the right things consistently.

The Pattern I See Repeatedly

Across SaaS companies, the pattern is often the same.

  • Sales sells one version of value
  • The customer expects something slightly different
  • Customer success tries to bridge the gap
  • Product is not always close enough to what is happening after the sale
  • Leadership only sees the issue when churn appears

By then, the problem has usually been building for months.

Why This Matters Now

AI is making this more obvious.

It is now easier than ever to:

  • automate activity
  • generate insights
  • scale customer outreach
  • produce reports
  • identify signals

But none of that fixes a broken model.

In fact, AI can make the problem worse.

If the customer success model is unclear, AI simply helps you scale unclear work faster.

That is not transformation. That is organised noise.

What Good Looks Like

When customer success is working properly, the business feels different.

Retention becomes more predictable.

Expansion becomes systematic, not opportunistic.

Customer success has a clear commercial role.

Sales, product and CS are aligned around the same customer outcomes.

Leadership trusts the numbers because the numbers connect to reality.

That is the shift from customer success as support to customer success as a growth engine.

Practical Takeaway

Before hiring another CSM, ask one question:

Do we know exactly how customer success drives revenue in our business?

Not in theory.

In practice.

  • By segment
  • By customer stage
  • By renewal risk
  • By expansion opportunity
  • By measurable value delivered

If the answer is not clear, another hire will not fix it.

It may simply make the current problem more expensive.

Final Thought

If you are trying to improve retention or make customer success more commercially accountable, the real work usually starts before the next hire.

It starts with the model.

The team can only scale what the business has designed properly.

👉 Customer success advisor

What is AI-enabled Customer Success (and how to do it properly)

Introduction

AI is everywhere right now. Every SaaS company claims to be using it. Every Customer Success team is being told to adopt it.

But most teams are layering AI onto a weak Customer Success model and hoping it fixes the problem. It won’t.

AI doesn’t fix Customer Success. It exposes it.

So what does AI-enabled Customer Success actually mean and how do you do it properly?

What is AI-enabled Customer Success?

At its core, AI-enabled Customer Success is simple.

It’s using AI to help customers achieve outcomes faster and more consistently at scale.

Not more emails. Not more dashboards. Not more activity.

Better outcomes.

That means:

  • Identifying risk earlier
  • Spotting expansion opportunities sooner
  • Guiding customers to value faster
  • Helping teams focus on what actually drives revenue

AI should amplify good Customer Success. Not replace it.

Where most companies get it wrong

Most teams start in the wrong place.

They ask…

“How can we use AI in Customer Success?”

Instead of…

“Where are we failing to deliver value today?”

So what happens? They add…

  • AI-generated emails
  • Automated health scores
  • Chatbots that answer basic questions

It looks impressive but nothing really changes.

Churn doesn’t move. Expansion doesn’t grow.

Because the underlying problem hasn’t been solved.

The value story is still unclear.

The real shift: from activity to outcomes

AI only works when your Customer Success model is built around outcomes.

Not activity.

That’s the shift most companies haven’t made yet.

Traditional CS focuses on:

  • Touchpoints
  • QBRs
  • Adoption metrics

AI-enabled CS focuses on:

  • Customer outcomes
  • Value realisation
  • Commercial impact

If you can’t clearly define the value your customer is getting, AI has nothing useful to optimise.

Where AI actually adds value

When used properly, AI can transform how Customer Success operates.

1. Early risk detection

AI can analyse usage patterns, engagement signals and behavioural trends to spot risk before it’s visible. Not when the customer is already leaving, but months earlier.

2. Expansion signals

The best growth opportunities are already in your customer base.

AI helps identify:

  • Underused features
  • Teams ready to scale
  • Accounts with growing demand

This turns expansion from reactive to proactive.

3. Personalised guidance at scale

Customers don’t want generic playbooks. They want relevance.

AI can tailor onboarding, recommendations and next steps based on how each customer actually uses your product.

4. CSM focus

Your CSMs shouldn’t be chasing data.

They should be driving conversations that lead to outcomes.

AI can remove the noise so they focus on:

  • Value conversations
  • Commercial alignment
  • Growth opportunities

How to do AI-enabled Customer Success properly

This is where most companies struggle.

Here’s the right order.

1. Define customer outcomes clearly

Start here.

What does success look like for your customer in commercial terms?

Revenue growth? Cost reduction? Efficiency?

If you can’t answer this, stop.

AI won’t help.

2. Fix your value story

Your CSMs need to articulate value in a way that resonates with the customer and their CFO.

Not features, not usage

Value.

3. Align your data

AI is only as good as the data behind it.

That means connecting:

  • Product usage
  • Commercial metrics
  • Customer goals

Most companies have this data. It’s just not connected.

4. Redesign your operating model

This is the big one. AI doesn’t sit on top of your model.

It changes it.

  • Lower-value activities should be automated
  • High-value conversations should be elevated
  • Roles and responsibilities should shift

5. Start small and scale

Don’t try to transform everything at once.

Pick one area:

  • Onboarding
  • Risk detection
  • Expansion

Get it working. Then scale.

The bottom line

AI-enabled Customer Success isn’t about tools. It’s about focus.

If your Customer Success team is already aligned to outcomes, AI will accelerate growth.

If it isn’t, AI will expose the gaps.

That’s why some companies are seeing real results and others are just adding noise.

Final thought

The question isn’t…

“Are we using AI in Customer Success?”

It’s…

“Are we delivering real, measurable value to our customers?”

Because if you’re not, AI won’t save you – iIt will just make it more obvious.

Need more help?

If you’re rethinking how Customer Success drives retention and expansion in an AI-driven world, that’s exactly where I focus.

Happy to share what’s working and what isn’t.

Why SaaS Growth Breaks After the Sale (and How to Fix It)

Introduction

Most SaaS companies think they have a pipeline problem.

They don’t.

They have a conversion problem after the deal.

Revenue doesn’t just come from winning customers. It comes from what happens next. – adoption, value realisation and expansion.

And this is where growth quietly breaks.

The Real Problem Isn’t Sales

SaaS leaders spend a lot of time optimising:

  • Lead generation
  • Conversion rates
  • Sales efficiency

But once the deal is signed, things become far less structured.

The assumption is simple:

“We’ve sold the value, now the customer will realise it.”

In reality, that rarely happens consistently.

Where Growth Actually Breaks

Growth doesn’t fail at the point of sale.

It breaks in the gap between:

  • What was sold
  • What is delivered
  • What the customer actually achieves

This shows up in familiar ways:

  • Slow or partial adoption
  • Customers using features but not achieving outcomes
  • Expansion opportunities that never materialise
  • Churn risk appearing late in the lifecycle

By the time it’s visible, the damage is already done.

The Hidden Revenue Leak

Every SaaS business has a flow:

Sale → Adoption → Value → Expansion

If that flow is not connected and managed:

Revenue is lost.

Not always immediately.

But over time:

  • Deals don’t expand
  • Renewals become harder
  • Growth becomes unpredictable

This is why many companies feel like they are working harder for the same results.

Because they are.

Why Customer Success Alone Doesn’t Fix It

This is often labelled as a Customer Success issue.

It isn’t. It’s a system issue.

Common problems include:

  • Weak handover between sales and post-sale teams
  • No clear definition of what “value” actually means for the customer
  • Lack of ownership for outcomes
  • Misalignment between sales, CS and product

Customer Success can’t fix this in isolation. Because the problem doesn’t sit in one team.

What High-Growth SaaS Companies Do Differently

Companies that scale efficiently do one thing well:

They control what happens after the sale.

That means:

  • Clear alignment between sales, CS and product
  • Defined customer outcomes from day one
  • Strong ownership of value realisation
  • Early visibility of risk and opportunity
  • A structured path to expansion

In these organisations, growth feels more predictable. Because it is.

How to Fix Where Growth Breaks

If you want to improve growth, start here:

1. Define Value Clearly:

What does success look like for the customer? Not usage. Not features. Outcomes.

2. Strengthen the Handover:

Make sure context, expectations and goals carry through from sales into delivery.

3. Track Leading Indicators:

Don’t wait for churn. Track adoption, engagement and value signals early.

4. Align Teams Around Outcomes:

Sales, customer success and product need to be aligned around customer success, not just their own metrics.

5. Build a Path to Expansion:

Expansion should not be opportunistic. It should be designed into the lifecycle.

Final Thought

Most SaaS companies don’t struggle to win customers. They struggle to turn those customers into long-term, expanding revenue.

That’s where growth really happens. And that’s where it often breaks.

Call to Action

If growth feels harder than it should, it’s worth asking a simple question:

Where does it break after the sale?

Why Your Customer Success Strategy Could Be the Difference Between Growth & Churn

Most SaaS founders know they need a customer success strategy. Far fewer have one that’s actually working.

You’ve got product-market fit. You’re closing deals. The pipeline looks healthy. But somewhere between “signed contract” and “renewal conversation,” things are going wrong. Customers aren’t getting value fast enough. Churn is creeping up. And your team is too busy fighting fires to figure out why.

Sound familiar?

The problem usually isn’t your product. It’s that nobody owns the post-sale experience with the same rigour and expertise that your sales team owns the pipeline.

That’s where a well-designed customer success strategy changes everything and why more SaaS founders are bringing in senior customer success (CS) expertise earlier than ever before.

What a Customer Success Strategy Actually Means

Let’s be clear about what we’re talking about, because customer success gets used to mean a lot of different things.

A genuine customer success strategy isn’t just a support function with a friendlier name. It’s a deliberate, proactive approach to helping customers achieve their goals using your product – so that retention, expansion and advocacy happen as a natural result.

Done well, it covers:

  • Onboarding: getting customers to value fast, not just technically set up
  • Adoption: ensuring the right people are actually using the product in the right way
  • Health monitoring: spotting risk before it becomes churn
  • Expansion: identifying when customers are ready to grow their investment
  • Advocacy: turning happy customers into a growth channel

Each of these requires strategy, not just good intentions. And building that strategy takes experience that most early-stage SaaS companies simply don’t have in-house yet.

The Speed Problem Most Founders Underestimate

Here’s what tends to happen.

A founder recognises that customer success needs more attention. They hire a customer success manager – usually someone reasonably junior – and hope things improve. Six months later, they’re still firefighting. The CSM is doing their best, but they don’t have the frameworks, the instincts or the experience to build a function from scratch.

So the founder goes back to market, this time looking for a VP or Chief Customer Officer. That process takes three to six months. The right person is expensive and by the time they’re onboarded and up to speed, another six months have passed.

In that time, customers have churned. Revenue has been lost. And the window to build something proactive has narrowed.

Speed to impact matters. Every month without a clear customer success strategy is a month where churn risk is growing quietly in the background.

Why Senior CS Expertise Changes the Pace

When you bring in someone with genuine seniority in customer success – not a generalist, not someone still learning the craft, but an operator who has built and led CS functions before – the pace of change is completely different.

They don’t need to figure out what good looks like. They’ve seen it. They’ve built it. They know the playbooks, the pitfalls and the levers that move the metrics that matter.

In the first few weeks, a senior CS leader will typically:

  • Audit your current customer journey and identify where value is being lost
  • Benchmark your churn and retention data against what’s typical for your stage and sector
  • Define your Ideal Customer Profile from a success perspective, not just a sales one
  • Build or refine your onboarding process to accelerate time-to-value
  • Create health scoring that gives you genuine early warning of at-risk accounts
  • Put commercial rigour around renewal and expansion conversations

That’s months of guesswork and trial-and-error compressed into weeks. And for a SaaS business where net revenue retention is one of the key metrics investors scrutinise, that speed matters enormously.

The ROI Conversation Founders Need to Have

There’s a conversation most SaaS founders haven’t had clearly enough with themselves: what is poor customer success actually costing you?

It’s easy to see sales costs. Marketing spend is visible. But the cost of churn tends to be underestimated because it’s often slow and diffuse.

Think about it this way. If your annual contract value is £50k and you’re losing five customers a year who could have been saved with better onboarding and health monitoring, that’s £250k of recurring revenue gone. Not once – every year, because that churn compounds.

And that’s before you factor in the expansion revenue you’re not generating. Most SaaS businesses have significant untapped growth sitting in their existing customer base. Customers who could be using more of the product, upgrading their tier, or expanding across teams – if only someone was having the right conversations at the right time.

A customer success strategy for SaaS founders isn’t a cost centre. Built properly, it’s one of the highest-leverage growth investments you can make.

What This Looks Like in Practice

The model that’s gaining real traction among growth-stage SaaS companies is bringing in experienced CS leadership on a part-time or project basis – getting senior strategic input without the full-time executive price tag or the long hiring timeline.

This works particularly well when:

You’re scaling past £1m ARR and churn is becoming a board-level concern: You need strategic clarity fast, not a six-month hiring process.

You’ve just closed a funding round: Investors will want to see a credible customer success strategy alongside your growth plan. Having someone senior who can articulate and execute that gives you confidence in both directions.

You’re building your CS function from scratch: A senior operator can design the structure, hire the right people, build the playbooks and hand over a functioning team — rather than leaving a junior hire to figure it out alone.

You need an outside perspective: Sometimes you’re too close to your own customers to see clearly where the friction is. An experienced CS leader brings pattern recognition from dozens of other SaaS businesses.

The Metrics That Tell You This Is Working

A well-executed customer success strategy moves measurable numbers. Here’s what to track:

Net Revenue Retention (NRR): this is your north star. World-class SaaS businesses run NRR above 120%. If yours is below 100%, revenue is shrinking from your existing base even if you’re still closing new deals.

Time to Value (TTV): How long does it take a new customer to get genuine value from your product? The shorter this is, the better your long-term retention. CS done well accelerates this.

Customer Health Score: A composite metric that tells you which accounts are at risk before they tell you themselves.

Churn Rate: Both logo churn (number of customers lost) and revenue churn (MRR or ARR lost). These tell different stories and both matter.

Expansion Revenue: What percentage of your growth is coming from existing customers? This is one of the most efficient growth levers available to you.

If you can’t confidently report on all of these right now, that’s a signal. Not a criticism – just useful information about where to focus.

The Founder Shift That Makes This Work

One final thing worth calling out…

The founders who get the most from senior CS expertise are the ones who treat customer success as a strategic priority, not a support function. They bring their CS leader into commercial conversations, not just post-sale ones. They share data openly. They make decisions based on customer health, not just pipeline.

That shift in mindset – from “CS is something that happens after the sale” to “CS is central to how we grow” – is often the thing that separates businesses with strong NRR from those still fighting churn.

The good news is you don’t have to figure that out alone. The expertise exists. The playbooks are proven. And the impact, when you bring in the right experience at the right time, can be felt faster than most founders expect.

Ready to build a customer success strategy that actually moves the metrics? Let’s talk

AI in Customer Success: A Practical Guide for SaaS Leaders

AI is reshaping customer success. Not by replacing people, but by changing how decisions are made.

For SaaS companies, growth no longer depends on sales alone. It depends on what happens after the deal. This is exactly how I approach customer-led growth.

Retention, expansion and customer value are now the real drivers of revenue.

AI is accelerating that shift.

What AI In Customer Success Actually Means

AI in customer success is not about automation for its own sake.

It’s about improving how teams:

  • Identify risk earlier
  • Spot expansion opportunities
  • Guide customers towards value
  • Focus on what actually matters

The goal is not more activity. It’s better decisions.

Why AI Is Changing SaaS Retention & Growth

Traditional customer success models rely on:

  • health scores
  • manual check-ins
  • reactive engagement

These approaches are limited.

They depend on lagging indicators and human bandwidth.

AI changes this by:

  • analysing usage data in real time
  • identifying patterns across customers
  • surfacing signals before problems are visible

This shifts customer success from reactive to proactive and is already visible in how teams are evolving, as outlined in how AI will impact customer success teams.

Where AI Really Creates Value

The real impact of AI in customer success comes from a few specific areas.

Risk detection:

AI can identify churn risk before the customer feels it. Changes in behaviour, usage drops or engagement patterns can be flagged early, giving teams time to act.

Expansion signals:

AI can highlight where value is already being created. This allows teams to focus expansion conversations on real outcomes, not assumptions.

Time to value:

AI can guide the next best action for customers. This reduces friction, shortens onboarding and helps customers reach value faster.

Focus & prioritisation:

Customer success teams often manage too many accounts with too little time.

AI helps prioritise where attention is needed most, improving both efficiency and impact.

What Most Companies Get Wrong

Adding AI on top of a weak customer success strategy does not fix the problem.

It amplifies it.

Common mistakes include:

  • unclear definition of customer value
  • misalignment between sales, product and customer teams
  • over-reliance on generic health scores
  • focusing on activity instead of outcomes

If you don’t know what value looks like for your customer, AI won’t solve that.

How To Implement AI In Customer Success

The starting point is not technology. It’s clarity.

1. Define customer value clearly

What outcomes does your customer care about? Revenue, efficiency, risk reduction, growth. Be specific.

2. Align teams around those outcomes

Sales, product and customer success need to agree on what success looks like. Otherwise, AI will surface data but not meaning.

3. Use AI for signal, not noise

Focus on:

  • risk indicators
  • expansion triggers
  • usage patterns

Avoid drowning teams in dashboards.

4. Combine AI with human judgement

AI prepares. Humans decide. The best teams use AI to reduce uncertainty, not replace thinking.

Final Thought

AI does not fix customer success. It exposes whether you understand customer value. The gap between average and high-performing teams is about to get much wider.

Want To Go deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

AI in Customer Success: Stop Chasing Efficiency & Start Driving Outcomes

Most Companies Are Using AI The Wrong Way

Most companies are using AI to move faster but very few are using it to create better customers. And that’s the gap.

AI in Customer Success is being treated as an efficiency tool. Automate tasks, reduce workload and scale coverage. Useful, but limited. Because speed without direction doesn’t create value.

What AI-Enabled Customer Success Should Actually Do

The best teams have shifted the question.

Not: How can AI save time?
But: How can AI improve customer outcomes?

That shift changes everything.

In practice, it looks like this:

  • AI identifies risk before the customer feels it
  • AI highlights expansion opportunities based on real usage
  • AI reduces time to value through next best actions
  • AI removes noise so CSMs focus on commercial impact

Not more activity, better decisions.

The Real Problem: AI Is Scaling Weak Strategies

This is where most SaaS companies get stuck. They add AI on top of an unclear Customer Success model. And AI does what it always does.

It scales what is already there.

If your definition of customer value is weak, AI won’t fix it.

If your teams are not aligned, AI will amplify the noise.

If your data is messy, AI will generate more confusion than insight.

AI doesn’t solve strategy problems. It exposes them.

The Shift That Matters

The move is simple. But not easy.

  • From reactive to predictive
  • From activity to outcomes
  • From account management to value creation

This is where Customer Success becomes commercial, not operational.

What The Best SaaS Companies Do Differently

They are not replacing Customer Success.

They are upgrading it.

  • AI handles the signals
  • Humans handle the decisions

That means:

  • More strategic conversations with customers
  • Better judgement on risk and growth
  • Stronger alignment across CS, Sales, and Product

Human-led. AI-enabled. Outcome-focused.

That’s the model.

Final Thought

If your AI strategy is focused on efficiency, you’ll move faster. If it’s focused on outcomes, you’ll grow faster.

Ask one simple question:

  1. Is your AI improving customer outcomes
  2. Or just making your team busier, faster?

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.

How AI Will Impact Customer Success Teams

For the past two years there has been a loud debate about AI in Customer Success.

  • Will it replace Customer Success Managers?
  • Will AI run renewals?
  • Will customers even want to speak to humans?

These are great questions but they miss the real shift that is happening.

AI will not replace Customer Success. It will expose weak Customer Success teams.

Because when automation removes the operational work, what remains is the hardest part of the role. Helping customers achieve real business outcomes.

The Work That AI Will Remove

A large part of Customer Success work today is operational.

  • Preparing reports
  • Updating dashboards
  • Summarising meetings
  • Chasing internal teams for updates

This is not where value is createdIt is simply the administrative cost of running a customer-facing organisation. AI is already automating much of this work.

AI is changing how customer success teams operate. I’ve broken this down in detail in this guide to AI in customer success.

Modern Customer Success platforms can:

  • summarise customer calls
  • analyse product usage data
  • identify churn risk signals
  • generate account summaries
  • recommend next best actions

According to the Gainsight Customer Success Index, 52% of Customer Success teams already use AI in their workflows, and 91% expect it to significantly impact their strategy.

Source

In other words, the administrative layer of Customer Success is starting to disappear and that is where the real shift begins.

What Remains When Automation Arrives

When AI removes the operational workload, something interesting happens. The role becomes clearer. Customer Success is not about managing activity. It is about creating value.

The companies getting this right focus Customer Success on three things.

(1) Helping customers achieve measurable outcomes:

Not feature adoption. Not product usage. Actual business impact.

(2) Connecting product capabilities to customer strategy:

The best CSMs increasingly look more like advisors than account managers
They understand the customer’s business model and help align technology to it

(3) Identifying growth opportunities

Expansion revenue rarely comes from sales pressure
It comes from customers realising the product is solving real problems
When that happens, growth follows naturally

The Uncomfortable Reality For Many Teams

Many Customer Success organisations were built for a different era. An era where simply maintaining relationships created value.

That model is under pressure. AI will not remove Customer Success roles. But it will remove the work that previously hid weak operating models. Teams that rely on:

  • manual reporting
  • reactive engagement
  • relationship management without measurable outcomes

… will find it harder to justify their role. Because AI can replicate most of that activity.

What AI cannot replace (today) is commercial judgement and strategic thinking.

What Great CSMs Will Look Like In 5 Years

As automation spreads across the industry, the profile of a strong Customer Success Manager will change. Three capabilities will matter far more than they do today.

(1) Business understanding: CSMs will need to understand how their customers actually create value. Industry knowledge becomes more important than product knowledge.

(2) Commercial thinking: Great Customer Success leaders will understand how retention, expansion and customer outcomes connect. They will think like revenue leaders.

(3) Strategic communication: Customers do not need another dashboard walkthrough. They need someone who can translate product capability into business impact.

The role then becomes far less operational and more advisory and strategic.

What Leaders Should Do Now

If you run a SaaS business, AI should not be viewed as a headcount reduction tool inside Customer Success. It should be viewed as a capability shift. The goal is not to remove Customer Success.

The goal is to remove the operational friction around it. This allows teams to focus on the work that actually drives growth. Helping customers succeed.

Because in subscription businesses, customer success is not just a support function. It is one of the most powerful growth levers a company has.

The Real Impact Of AI On Customer Success

The future of Customer Success will not be defined by automation. It will be defined by clarity. Once AI removes the administrative work, the purpose of the function becomes obvious. Customer Success exists to help customers achieve outcomes that make them want to stay. And to expand.

The teams that can demonstrate that clearly will become more valuable than ever.

The teams that cannot will struggle to justify their place.

Because AI does not remove Customer Success, it exposes it.

Want To Go Deeper?

If you’re thinking about retention, expansion or how AI fits into your strategy, I work with a small number of SaaS companies on exactly this.

👉 If you’re rethinking your approach, let’s talk.