Tag Archives: customer value

Why Customer Success Needs a “State of AI” Report

If you’ve spent any time on LinkedIn recently, you’ll have seen no shortage of posts about AI and Customer Success.

Some predict the end of the Customer Success Manager. Others claim AI will transform everything overnight. Most fall somewhere in between.

The problem is that there’s very little agreement on what’s actually happening.

After dozens of conversations with Customer Success leaders, SaaS executives and founders over the past year, I’ve noticed something interesting.

We’re all talking about AI.

We’re just not talking about the same thing.

Some teams are experimenting with meeting summaries and email drafts.

Others are building AI into customer workflows.

Some are measuring productivity.

Others are trying to rethink their entire post-sales operating model.

These are completely different conversations.

What seems clear is that AI has moved beyond experimentation. It is becoming part of day-to-day Customer Success.

The more interesting questions are no longer whether teams should use AI, but how they should use it and what impact it is really having.

From where I sit, a few themes keep appearing.

  • AI is removing repetitive work but increasing expectations.
  • It is exposing weak processes rather than fixing them.
  • It is making commercial judgement more valuable, not less.
  • It is forcing Customer Success leaders to rethink what great performance actually looks like.

I don’t think the biggest story is that AI is replacing Customer Success.

I think it’s changing what good Customer Success looks like.

That’s a much more interesting conversation.

Over the coming months, I’m going to capture the patterns I’m seeing through my advisory work, podcast conversations and discussions with Customer Success leaders.

The goal is simple.

To build a practical picture of how AI is really changing Customer Success, separating the hype from what’s happening in real SaaS organisations.

I’d love to hear what you’re seeing too.

What’s been the biggest change in your Customer Success team since AI became part of everyday work?

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.

Unlocking Customer Lifetime Value: The Key to Long-term Success

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Introduction:

Customer Lifetime Value (CLTV) holds the key to long-term success in business. Unraveling the potential of CLTV is crucial for building lasting relationships and driving sustained revenue growth.

Understanding CLTV:

Customer Lifetime Value is not solely about revenue but about fostering enduring value for customers. It is a vital metric for gauging an organization’s growth and prosperity. For instance, consider a subscription-based service like Netflix, where a loyal customer who subscribes for years contributes substantially to the company’s CLTV.

Viewing Value from Different Angles:

CLTV is more than just revenue; it encompasses different perspectives of value. Identifying and aligning with the customer’s definition of value is crucial. An example could be a luxury car brand that offers exceptional customer service, providing value that extends beyond the purchase.

Applying CLTV in Practice:

Measuring CLTV beyond revenue involves assessing advocacy, referrals, and recommendations, which are immensely valuable. Forecasting CLTV requires a careful consideration of customer segments and past profiles. For example, a software company may analyze user adoption metrics to predict long-term value.