The Art of Experimentation for Product Managers 👨‍🔬

Bhavya Singh
7 min readAug 8, 2023

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Ben is a PM, Ben is obsessed with Experimentation, Be like Ben :)

Hello beautiful fellas,

Let’s talk about Experimentation! What is it, you ask? Well, it’s a powerful tool that every PM should be obsessed with. It’s all about discovering what works and what doesn’t, & using that to make better decisions.

But why should PMs care about Experimentation? How can they do it? And how can they gain the maximum value out of it? In this article, we’ll explore all these questions and more. We’ll also discuss how to automate Experimentation and turn it into a continuous discovery spaceship. 🚀

Welcome to the daily product management show! 📺 I’m your host, Bhavya, and I’ll be bringing you fresh insights on product management every day! 👋

You experiment = You win

Experimentation is a crucial component of product management, allowing product managers to test different ideas and approaches to identify the most effective solutions and gain valuable insights into their target audience. In this article, we will explore the art of experimentation for product managers, why it is important, how to do it effectively, and provide real logical examples to illustrate each method.

What is Experimentation for Product Managers?

Experimentation for product managers involves testing different ideas and approaches to identify the most effective solutions and gain valuable insights into the target audience. By conducting experiments, product managers can create products that resonate with users and drive business growth

It is the application of scientific principles to establish causation between changes to a product and their outcomes. It involves running structured tests to discover unbiased learnings and uncover the real cause of changes in metrics, even when they are too small to be measured independently.

Why Experiment?

Experimentation is important for product managers for several reasons:

  1. Data-Driven Decision Making: Experimentation allows product managers to make informed decisions based on real user data rather than relying on assumptions or guesswork. It provides concrete evidence to support product decisions and reduces the risk of making costly mistakes.
  2. Continuous Improvement: Through experimentation, PMs can iterate and improve their products over time. By testing different ideas and approaches, they can identify what works and what doesn’t, leading to continuous optimization and refinement.
  3. User-Centric Approach: Experimentation helps product managers understand how customers use their products and identify ways to improve the user experience. By gathering insights from experiments, product managers can tailor their products to better meet the needs and preferences of their target audience.
  4. Validating Assumptions: We as PMs often make assumptions about our target audience, market fit, and product features. Through experimentation, they can validate these assumptions and make data-driven decisions.

How to Conduct Effective Experiments?

To conduct effective experiments, it is important to follow a structured approach. Here are the key steps:

  1. Define the Objective: Clearly define the objective of the experiment. What specific question or hypothesis are you trying to answer? For example, “Will adding a chatbot feature improve user engagement?”
  2. Formulate a Hypothesis: Based on the objective, formulate a hypothesis that states the expected outcome of the experiment. For example, “Adding a chatbot feature will increase user engagement by 20%.”
  3. Design the Experiment: Determine the experimental setup, including the control group and the treatment group. The control group represents the current state of the product, while the treatment group represents the variation being tested. For example, the control group may not have the chatbot feature, while the treatment group does.
  4. Collect and Analyze Data: Implement the experiment and collect relevant data. Use analytics tools to measure the impact of the variation on key metrics. Analyze the data to determine if the hypothesis is supported or refuted.
  5. Draw Conclusions: Based on the data analysis, draw conclusions about the impact of the variation on the desired outcome. Did the experiment support the hypothesis? What insights can be gained from the results?
  6. Iterate and Learn: Use the insights gained from the experiment to inform future product decisions. If the experiment was successful, consider implementing the variation permanently. If not, iterate and test new variations based on the learnings.

But is there method to this madness?

Here is a wide list of experiments you can consider, based on your specific case and objectives:

  1. A/B Testing: Compare two versions of a feature or design element to determine which one performs better.
  2. Prototype Testing: Create prototypes and conduct user testing to gather feedback and identify areas for improvement.
  3. Pricing Experiments: Experiment with different pricing models, discounts, or packaging options to determine the optimal pricing strategy.
  4. User Experience (UX) Testing: Evaluate the usability and effectiveness of your product’s user interface through testing and observation.
  5. Metric optimization:
    Conversion Rate Optimization: Experiment with different elements on your website or app to increase conversion rates.
    Onboarding Flow Optimization: Test different onboarding flows to increase user activation and retention.
    Messaging and Copy Testing: Test different messaging and copy variations to optimize communication with your target audience.
  6. Channel Experiments: Experiment with different marketing channels to identify the most effective ones for reaching your target audience.
  7. Localization Experiments: Test different language and cultural adaptations to optimize your product for different markets.
  8. Retention Experiments: Experiment with different strategies to improve user retention, such as personalized recommendations or loyalty programs.
  9. Gamification Experiments: Test the impact of gamification elements on user engagement and behavior.
  10. Search Engine Optimization (SEO) Experiments: Experiment with different SEO strategies to improve your product’s visibility in search engine results.
  11. Social Media Experiments: Test different social media strategies and content formats to increase engagement and reach.
  12. Referral Program Experiments: Experiment with different referral program incentives and messaging to increase user referrals.
  13. Usability Testing: Conduct usability tests to identify and address usability issues in your product.

Real Examples of Experimentation

To illustrate the different methods of experimentation, let’s look at some real-world examples of companies/products that employed experimentation to achieve success:

Netflix: Netflix is known for its data-driven approach to product development. They constantly run experiments to optimize their recommendation algorithms and user interface. For example, they may test different variations of the homepage layout to determine which design leads to higher user engagement and retention.

Spotify: Spotify uses experimentation to improve its personalized music recommendations. They test different algorithms and features to understand what resonates best with users. For instance, they may experiment with different ways of suggesting new songs or creating personalized playlists.

Amazon: Amazon is a pioneer in using experimentation to drive product innovation. They conduct thousands of experiments every year to optimize their website layout, product recommendations, and pricing strategies. For instance, Amazon Prime was launched as an experiment to test whether customers would pay an annual fee for free two-day shipping and other benefits. The experiment was a success, and Amazon Prime has since become a key driver of Amazon’s growth.

Airbnb: Airbnb’s dynamic pricing implementation is a great example of the power of experimentation. By testing different pricing strategies and algorithms, Airbnb was able to optimize the pricing of listings based on factors such as demand, seasonality, and location. Through experimentation, Airbnb was able to determine the most effective pricing strategies that maximized revenue for hosts while remaining competitive in the market. This allowed them to continuously refine their pricing algorithms and provide a better experience for both hosts and guests.

The best experiment guides for PMs that I’m a fan of 💛

I’m a product manager myself, and I know how hard it can be to find good resources on the topic. That’s why I started writing this blog.

I hope you found this article helpful. If you have any questions or feedback, please feel free to leave a comment below. And if you’d like to stay up-to-date on my latest articles, please follow me.

See you in the next one 👀

Happy PM-ing! 🚀

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Bhavya Singh

Product Manager Generalist | B2B/B2C SaaS | ISB | Hyper focussed PM on Growth & UX. https://www.linkedin.com/in/bhavyasingh | Comment on any blog for a 1:1 call