# SaaS Growth Experimentation Course > A three lesson course on running experiments that survive scrutiny: find the constraint, design a readable test, and decide what to scale, with worked examples. Source: https://saas-marketing.net/courses/growth-experimentation/ Topic: SaaS Growth Marketing Type: course-index Published: 2026-09-11 Last updated: 2026-09-11 Publisher: SaaS Marketing (saas-marketing.net) License: CC BY 4.0. Quote or republish with attribution and a link to https://saas-marketing.net/courses/growth-experimentation/ ## Short answer This three lesson course teaches B2B SaaS growth teams to run experiments at low traffic, where classic A/B testing advice breaks down. Lesson one locates the actual constraint in the funnel. Lesson two designs a test that can be read at your sample size, or rules it out. Lesson three sets the decision rule before results arrive. Total time is about 90 minutes, and the materials include an experiment brief, a sample size calculator and a decision rule card. ## Key takeaways - Most B2B SaaS teams cannot reach statistical significance on a landing page test, so the course teaches what to do instead. - Lesson one finds the funnel constraint, because testing anywhere else produces true results that change nothing. - Decision rules get written before the test launches, which is the single change that stops results being argued about. - The whole course runs about 90 minutes across three emailed lessons, one per day. - Expect to cancel roughly half the tests on your current backlog after lesson two. --- Fair warning before you enrol: this course will tell you not to run most of the tests currently on your backlog. Not because the ideas are bad, but because at your traffic level the result would be unreadable and you would ship it anyway based on a 9% lift that was noise. That is the problem the three lessons are built around. ## Who should take this Growth marketers and product managers at B2B SaaS companies with limited traffic. Call it 2,000 to 50,000 sessions a month, a few hundred signups, and a boss who has started asking about experiment velocity. If you run a consumer product with millions of sessions, skip it. Standard experimentation practice works fine when you can detect a 2% lift in four days. The whole design of this course comes from the opposite situation, where a homepage test needs eleven weeks to resolve and the homepage will have changed twice by then. The wider context on where experiments fit sits in [SaaS Growth Marketing](/saas-growth/). Most B2B SaaS experimentation programs are theatre. They report tests run, not decisions changed. If your last quarterly review counted experiments rather than naming what you stopped doing because of one, this course is aimed at you specifically. ## What you will be able to do after each lesson Lesson one is funnel arithmetic, not brainstorming. You will compute the revenue impact of a 10% improvement at each step, and in almost every case one step dominates so heavily that everything else becomes a distraction. Teams routinely discover their constraint is trial to paid, then realise every test they ran last quarter was on the signup form. - Lesson two is where the backlog gets cut. You enter your weekly traffic and baseline conversion rate, and the calculator returns the smallest effect you could actually detect in four weeks. If that number is 35%, no button copy change qualifies, and you need a structurally different test: a new offer, a removed step, a changed pricing display. [Building a growth experimentation program](/guides/growth-experimentation-program/) goes deeper on how to build a backlog that survives this filter. Lesson three is the part that saves relationships. The decision rule gets written into the brief before launch: what result ships it, what result kills it, what result means run it longer. Without that, the post test meeting becomes a negotiation between whoever wants the feature and whoever wants to be right. ## The materials Three files, all editable, all delivered by email as you work through the lessons. - **Experiment brief template.** Hypothesis, primary metric, guardrail metric, minimum detectable effect, decision rule, owner, end date. The [growth experiment brief template](/templates/experiment-brief/) is the same file, available separately if you only want that. - **Sample size calculator.** Input weekly traffic and baseline rate, output minimum detectable effect and required run length. - **Decision rule card.** One page, printed or pinned in Slack, that the post test meeting follows. **40 to 60%** Share of a typical B2B SaaS experiment backlog that fails the power check in lesson two ## How this differs from generic CRO training The core assumption. Standard CRO material teaches you to test constantly and let volume find the winners, which is correct advice at consumer scale and actively harmful at 8,000 sessions a month. Here the advice inverts. Run fewer, bigger tests. Accept that some decisions will be made on directional evidence and label them as such in writing. Use qualitative research, session replay and sales call review to generate hypotheses, because at your traffic the hypothesis quality matters more than the test count. Tooling choices follow from that, and [A/B testing tools for SaaS](/guides/experimentation-tools-saas/) compares what PostHog, Amplitude and the rest actually give a low traffic team. Experiment count is the easiest growth number to report and the least informative. A team running 14 tests a quarter, none powered to detect less than a 30% lift, has generated 14 coin flips and a lot of engineering tickets. Published velocity figures are worth reading as context, not as targets, which is how [experiment velocity benchmarks](/research/experiment-velocity-benchmarks/) frames them. ## What the course does not cover Statistical theory beyond what you need to act. There is no derivation of the t test, no Bayesian versus frequentist debate, and no discussion of multi armed bandits, which are genuinely useful and genuinely irrelevant until you have enough traffic to feed them. It also does not cover SEO testing, which behaves differently because the unit is the page and the feedback loop runs in months. [SaaS SEO Sprint](/courses/saas-seo-sprint/) handles that. And it assumes you already know your funnel definitions; if you do not, take [the SaaS marketing foundations course](/courses/saas-marketing-foundations/) first. ## Time commitment and format About 90 minutes of reading and worksheet time, delivered one lesson per day over three days. Every lesson page is fully readable on the site without an email address. The sign up exists to pace the lessons and send the templates, not to gate content. Realistically, add two to three hours in week one to actually compute your funnel constraint with real data, because pulling clean numbers out of Amplitude or your warehouse is always slower than the arithmetic itself. **How to get value from it** ## Start here Begin with lesson one, or if experimentation is one part of a broader growth remit, read [B2B SaaS growth](/guides/b2b-saas-growth-growth/) for where it sits alongside channel work. For the tactics that get mislabelled as experimentation, [growth hacking for SaaS](/guides/growth-hacking-saas/) is the honest version. Pull your funnel numbers before you start lesson one. The course is close to useless without them. ## Frequently asked questions ### Who is this growth experimentation course for? Growth marketers, product managers and founders at B2B SaaS companies with real but limited traffic, roughly 2,000 to 50,000 monthly sessions. If you have 500,000 sessions a month, standard CRO training applies and you do not need this. If you have 300, the course will tell you to run qualitative research instead and that is a legitimate answer. ### Do I need statistics knowledge to take it? No. The sample size calculator does the arithmetic and lesson two explains what the output means in plain terms. You need to be able to read a conversion rate and hold the idea that a 12% lift on 40 conversions is not evidence of anything. That is the entire prerequisite. ### How is this different from generic CRO training? Generic CRO assumes you can reach significance in two weeks and spends its time on button colours and heuristics. This course assumes you cannot, so it prioritises picking bigger swings, running fewer tests, using sequential decision rules, and accepting directional evidence with a documented confidence level rather than pretending to certainty. ### What materials come with the course? Three files: an experiment brief template with the hypothesis, metric, guardrail and decision rule fields; a sample size calculator that tells you the minimum detectable effect at your traffic; and a one page decision rule card for the post test meeting. They arrive by email alongside the lessons. ### Is the course free? Yes. All three lesson pages are open and readable without a form. The email sign up delivers one lesson a day plus the three templates. Nothing is gated, and there is no upsell to a paid cohort at the end. ### How many experiments should a B2B SaaS team run per month? Fewer than you think. Teams under 20,000 monthly sessions usually get more value from two well powered tests a quarter than from eight underpowered ones a month. Velocity benchmarks are popular because they are easy to report, but a high count of unreadable tests is negative value once you count the engineering hours.