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What is an experimentation loop?

Article originally published in June 2023 by Stuart Brameld. Most recent update in June 2023.

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Definition of an experimentation loop

An experimentation loop is a continuous process of testing, learning, and iterating marketing strategies to optimise performance and achieve desired outcomes. For marketers, this involves designing and implementing experiments, collecting and analysing data, drawing insights, and making data-driven decisions to refine marketing tactics. By consistently going through this loop, marketers can identify the most effective approaches, uncover new opportunities, and adapt to changing market conditions, ultimately driving growth and maximising return on investment.

An example of an experimentation loop

Here is an example of how it works:

1. Define Objective: Increase the number of new subscribers for Growth Method by 20% in the next quarter.
2. Formulate Hypothesis: Offering a 14-day free trial will attract more potential customers and lead to an increase in new subscribers.
3. Identify Key Metrics: Number of new subscribers, conversion rate from free trial to paid subscription, and churn rate.
4. Design Experiment: Implement a 14-day free trial option on the Growth Method website and track the number of sign-ups, conversions, and churns.
5. Execute Experiment: Launch the 14-day free trial offer and monitor the key metrics for a period of three months.
6. Analyze Results: Compare the number of new subscribers, conversion rate, and churn rate before and after the introduction of the free trial.
7. Draw Conclusions: If the results show a significant increase in new subscribers and a positive conversion rate, the hypothesis is validated, and the free trial offer can be continued. If not, a new hypothesis should be formulated and tested.
8. Iterate: Based on the conclusions, either continue with the current strategy or develop a new hypothesis and repeat the experimentation loop.

How does an experimentation loop work?

An experimentation loop works by continuously testing, analyzing, and optimizing marketing strategies to achieve the best possible results. Marketers begin by identifying a hypothesis or a specific aspect of their campaign they want to improve. They then design an experiment to test this hypothesis, such as an A/B test comparing two different ad creatives. Once the experiment is conducted, marketers analyze the data to determine which variation performed better and why. Based on these insights, they can make data-driven decisions to optimize their marketing efforts. This process is repeated in a cyclical manner, allowing marketers to constantly refine their strategies and maximize their return on investment.

Expert opinions and perspectives

Here are how some of the world’s best marketing and growth professionals think about an experimentation loop.

  • “The only way to win at content marketing is for the reader to say, ‘This was written specifically for me.’ The way to get there is to continuously iterate your content, and the only way to do that is to adopt an experimentation loop.” – Jamie Turner, Founder of 60 Second Marketer
  • “Test fast, fail fast, adjust fast.” – Tom Peters, American writer on business management practices
  • “Innovation needs to be part of your culture. Consumers are transforming faster than we are, and if we don’t catch up, we’re in trouble. The best way to catch up is through an experimentation loop.” – Ian Schafer, Founder and CEO of Deep Focus

Questions to ask yourself

As a modern growth marketing or agile marketing professional, ask yourself the following questions with regard to an experimentation loop:

  1. What is the primary goal or objective of this experiment, and how does it align with our overall marketing and growth strategy?
  2. What are the key performance indicators (KPIs) that will help us measure the success of this experiment, and how will we track and analyze them?
  3. What resources (time, budget, personnel) are required to execute this experiment, and how can we ensure that it is implemented efficiently and effectively?
  4. How will we validate the results of this experiment, and what criteria will we use to determine whether it should be scaled, optimized, or discontinued?
  5. What learnings can we gather from this experiment, and how can we apply these insights to future marketing and growth initiatives?

Additional reading

Here are some related articles and further reading around an experimentation loop that you may find helpful.

  1. The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses
  2. Experimentation Works: The Surprising Power of Business Experiments

See how this topic is trending on Google Trends here: https://trends.google.com/trends/explore?date=all&q=experimentation

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