Growth experimentation framework for B2B teams

Introduction

I have been testing since 2010, before most B2B companies even knew what a growth experiment was. I am CXL certified in experimentation, I built the testing programme for NU.nl (the largest news site in the Netherlands), and I have run A/B tests for dozens of brands across SaaS, e-commerce, and lead generation.

Most companies either skip testing entirely or run random experiments without a clear plan. Both waste time. The ones that grow fastest have a simple system: a backlog of ideas ranked by potential impact, a clean process for running tests, and a habit of documenting what they learn so every experiment builds on the last.

This playbook gives you that system. You will learn how to collect and prioritise experiment ideas, write hypotheses that actually teach you something, set up tests properly, and turn results into repeatable wins. No statistics degree required, just discipline and curiosity.

Chapters

1

Building your backlog

Random testing wastes time and teaches you nothing. Learn how to collect experiment ideas systematically and prioritise them based on potential impact so you always know what to run next.

Read chapter

2

Creating strong hypotheses

Most experiments fail before they start because the hypothesis is vague or untestable. Learn how to write hypotheses that are specific enough to prove or disprove and tied to metrics that matter.

Read chapter

3

Setting up experiments

A winning test means nothing if the setup was flawed. Learn how to configure experiments properly in VWO, ad platforms, and email tools so your results are actually valid.

Read chapter

4

Analysing and acting on results

Statistical significance is just the beginning. Learn how to interpret results correctly, avoid false positives, and turn winning experiments into permanent improvements across your growth engines.

Read chapter

5

Run your monthly experiment cycle

Execute the full experiment loop each month: select from your backlog, launch, monitor, close, and document what you learned.

Read chapter

6

Reprioritise backlog by impact and effort

Re-score your experiment backlog each quarter using updated data so you always run the highest-leverage tests first.

Read chapter

7

Compound learnings across experiments

Build a knowledge base from past experiments so new tests build on proven insights instead of starting from scratch every time.

Read chapter

8

Scale winning experiments across channels

Take validated wins from one channel and systematically test whether they work in others to multiply the impact of what already works.

Read chapter

Run growth experiments

tools

VWO

VWO provides A/B testing, personalisation, and behaviour analytics to optimise website conversion rates through data-driven experimentation.

Rating

From

€

393

per month

Explore tool

My review

Hotjar

User behaviour analytics platform showing heatmaps, session recordings, and feedback from real website visitors. Understand exactly how people use your site.

Rating

From

€

per month

Explore tool

My review

Microsoft Clarity

Microsoft Clarity provides free session recordings, heatmaps, and user behaviour analytics without traffic limits or time restrictions.

Rating

From

€

per month

Explore tool

My review

Notion

Flexible workspace for docs, wikis, and lightweight databases ideal when you need custom systems without heavy project management overhead.

Rating

From

€

per month

Explore tool

My review

Books

Lean Startup

Eric Ries

Rating

A disciplined approach to experiments. Define hypotheses, design MVPs and learn before you scale.

My review

Hacking growth

Sean Ellis

Rating

A practical framework for experiments and insights. Build loops, run tests and adopt a cadence that ships learning every week.

My review

Wiki

Sample size

Calculate how many users you need in experiments to detect meaningful differences and avoid declaring winners prematurely based on insufficient data.

Read concept

P-value

Interpret experiment results to understand the probability that observed differences occurred by chance rather than because your changes actually work.

Read concept

Minimum viable test

Design experiments that answer specific questions with minimum time and resources to maximise learning velocity without over-investing in unproven ideas.

Read concept

Hypothesis testing

Structure experiments around clear predictions to focus efforts on learning rather than random changes and make results easier to interpret afterward.

Read concept

Control group

Maintain an unchanged version in experiments to isolate the impact of your changes and prove causation rather than correlation with external factors.

Read concept

Statistical significance

Determine whether experiment results reflect real differences or random chance to avoid making expensive decisions based on noise instead of signal.

Read concept

A/B testing

Compare two versions of a page, email, or feature to determine which performs better using statistical methods that isolate the impact of specific changes.

Read concept

Monthly Recurring Revenue (MRR)

Track predictable monthly subscription revenue to monitor short-term growth trends and make faster decisions than waiting for annual revenue reports.

Read concept

Growth hacking

Deploy fast, low-cost experiments to discover scalable acquisition and retention tactics, learning through iteration rather than big bets.

Read concept

Other playbooks

Win bigger deals

Increase the average value of your initial contracts through better packaging, value framing, anchoring, and negotiation.

Read playbook

Convert more pipeline

The full journey from first meeting to signed contract. How to improve conversion at every stage of your sales pipeline so more opportunities become revenue.

Read playbook

Sales sequences

Build and automate sales follow-up sequences that keep deals moving through your pipeline without manual chasing.

Read playbook

Go-to-market strategy

Define your ideal customer profile, craft positioning that differentiates, and choose the channels that reach buyers when they are ready to act.

Read playbook

Lead qualification

Build a scoring and qualification framework that separates genuine buying intent from casual interest, so sales invests time where it counts.

Read playbook

Project delivery

The operational wrapper for every consulting engagement. Covers kickoff, communication rhythms, progress reviews, and handover so nothing falls through the cracks.

Read playbook

Run growth experiments

Introduction

Chapters

1

Building your backlog

2

Creating strong hypotheses

3

Setting up experiments

4

Analysing and acting on results

5

Run your monthly experiment cycle

6

Reprioritise backlog by impact and effort

7

Compound learnings across experiments

8

Scale winning experiments across channels

Run growth experiments

tools

VWO

Hotjar

Microsoft Clarity

Notion

Books

Lean Startup

Hacking growth

Wiki

Sample size

P-value

Minimum viable test

Hypothesis testing

Control group

Statistical significance

A/B testing

Monthly Recurring Revenue (MRR)

Growth hacking

Related topic

Growth leadership

Other playbooks

Win bigger deals

Convert more pipeline

Sales sequences

Go-to-market strategy

Lead qualification

Project delivery

Keep reading