SaaS CRO: Best & Worst Experiments To Run In 2026

SaaS CROs are at their very best when they’re running a ton of different experiments.

I’ve seen firsthand how revenue experiments can look great on paper, but ultimately fail to really move the needle.

The problems usually start when all of these experiments are clustered around acquisition touchpoints. Meanwhile, the retention side of the business (the bit you should probably focus on) is left essentially untouched.

All that effort and the downstream numbers don’t budge.

This is coming up way more than it should.

I’m always looking for A-players and I think half the battle, as a SaaS CRO, is just deciding which experiments to prioritize and deprioritize.

I want to walk you through what I'd recommend focusing on as a SaaS Chief Revenue Officer, and where I see the biggest untapped opportunity is probably right now.

SaaS CROs Are Wasting Time On The Wrong Experiments

It makes sense for us to start with the ones I’ve seen cause the most damage. This tends to be where teams spend the most time and come away with the least!

Homepage Headline Testing

Conversion rate optimization on the homepage headline is probably the most overrepresented experiment type I come across.

This isn’t the high-leverage activity you think it is.

The signal it produces is usually rather thin!

Here’s what will happen…

A SaaS CRO finds a headline variant that bumps sign-ups by 3-4% and they declare it a win.

The problem is, when you look at those sign-ups three months down the line, the retention story hasn’t changed at all.

If your headline testing isn't connected to a hypothesis about who you're attracting and whether those people are a good fit for your product… this isn’t a serious experiment. Scrap it. Move on.

Pricing Page Button Copy

Another one I see a lot. "Start your free trial" versus "Get started free" versus "Try it now" is the kind of experiment that generates activity without generating much insight.

Again, there are circumstances where this matters. As a category of experiment, it tends to attract a lot of attention relative to what it teaches you.

Feature Announcement Emails

I think people often forget that open rate and click rate on a feature announcement email tell you almost nothing about whether anyone used the feature or found it valuable.

You can’t think of feature announcement emails as retention experiments, even if you want to treat them like that.

Here’s What I Want To See SaaS CROs Testing

Okay, now for the stuff I’d really like to see you prioritize over the coming days and weeks.

Onboarding Sequences Segmented By Use Case

I’ve got some useful framing for you to think about…

If you're sending every new user through the same onboarding flow regardless of their job title, company size, or the reason they signed up, that's a significant experiment waiting to happen.

I've found that the teams that segment onboarding by use case, even crudely at first, see earlier time-to-value and meaningfully lower early churn.

The hypothesis makes a lot of sense... different users need to reach different first outcomes.

Testing whether a tailored path gets them there faster is useful SaaS CRO work.

Proactive Check-Ins For At-Risk Accounts

You can run a proper experiment here. I want you to take a cohort of accounts showing low engagement signals and test whether a targeted check-in from a human, or a well-timed automated nudge, changes the trajectory.

You should measure it against a control group and you'll learn something.

The SaaS Chief Revenue Officer instinct I'd want to see is the one that asks which interventions change lifetime value, not just which ones change open rates.

Pricing Plan Communication

Not button copy, but the substance of what you're communicating about value at each plan tier.

I've seen teams run some good experiments here where they test different framings of what the upgrade gets you.

The Experiment Most SaaS Teams Aren't Running

I'm going to be direct here, because I think this is the most important part.

The cancellation flow is the most underleveraged experiment surface in SaaS and most teams either don't have one, or they have a static one that hasn't been touched since someone set it up 18 months or so ago.

When a customer moves to leave, they're often willing to tell you exactly what went wrong if you give them a structured way to do it.

Testing different cancellation flows, the order of the questions, the offers you present, the reasons you provide as options… is genuine SaaS CRO work with a direct line to revenue.

Here's what a well-structured cancellation flow experiment looks like...

You start by testing the reasons you offer. Are you giving customers language that accurately reflects why they might leave, or are you forcing them into categories that feel approximate?

The quality of the reason data you collect depends entirely on this.

Then you test the offers! A customer who says they're leaving because of price gets a different offer than one who says the product is missing a feature they need.

Testing whether a pause option retains more of a specific segment than a discount option is exactly the kind of downstream experiment a SaaS Chief Revenue Officer should care about.

You then need to look at what people who decline your offers go on to tell you. That data is some of the richest product feedback you'll collect anywhere.

Raaft is great for collecting this and it only takes 30 minutes to set up.

When a customer tries to cancel, Raaft presents them with a targeted offer based on their plan and their stated reason for leaving, while capturing structured feedback that feeds directly into your product and pricing decisions.

A customer who accepts a discount and stays is telling you something.

And then, if you see a customer who declines and walks out anyway, that’s telling you something different but equally important!

Most SaaS teams don't realize this data was available to them the whole time.

What A Good SaaS Chief Revenue Officer Really Does

It's worth remembering that conversion rate optimization, done well, is about understanding what makes customers stay and why they leave.

Moving sign-up rates up by a fraction of a percentage point probably isn’t a good use of your time.

You should instead focus on experiments connected to lifetime value.

Those are going to help you understand which customers are most likely to churn and why.

You can then see where your product is falling short of the promise you made at sign-up.

If you're working as a SaaS Chief Revenue Officer, or advising one, the questions I'd start with are... what does your cancellation flow currently tell you? Is that data structured enough to act on?

If you don't even have a cancellation flow, that's the first experiment I'd run.

As far as I’m concerned, everything else can wait.

Raaft makes this ridiculously simple. You get started for free. There's no development work involved and the data starts collecting immediately.

By the time you're reviewing your next round of experiment results, you'll have a layer of insight that most of your competitors are probably still missing.