How to Conduct a Product Experiment: Tips, Tools, and Process

Try to guess the potential impact of increasing customer retention by 5%. Maybe, the revenue would grow by 10-15%? In fact, just a 5% customer retention rate boost can grow your profit by 25% to 95%. What's more, 82% of companies agree that retention is cheaper to execute than acquisition. If you own a business, we bet you'd agree. 

Always refining your product to meet and exceed customer needs is one of the best ways to keep customers coming back for more. Understanding how users behave can turn a good product into an essential one.

By experimenting with your product and systematically testing changes and new features, you can gain valuable insights. A/B tests, usability studies, and multivariate analysis turn every adjustment into a data-driven decision.

We'll explore the key framework of a product experiment and show how it:

• reduces risks;
• drives innovation;
• improves user experience.

Let's see how structured experimentation can send your product to new heights.

What Is Product Experimentation?

Product experimentation is the process of trying out different tweaks and features to see how they affect user behavior and business results. It's systematic, data-driven, and can be done using a wide variety of methods, including:

• A/B tests;
• usability tests;
• multivariate testing;
• focus groups;
• user interviews
• click tracking;
• funnel testing;
• and other tricks.

Basically, it's a mix of numbers and user feedback, where you look at everything from tiny design changes to adding brand-new features.

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What Is a Product Experimentation Framework?

In short, it's a defined and validated framework to perform an efficient product experiment. Clearly, it's just a fancy way of saying there's a structured method to all this testing madness. It includes creating product hypotheses, testing, and evaluating them to make smart, data-driven decisions that improve the product experience (PX).

Even if your hypothesis doesn't pan out, every experiment teaches you something valuable. And the structured steps of a product experimentation framework ensure you're always learning how to make the product better. 

Why Is Experimentation Important for Product Development?

Implementing an experimentation framework comes with awesome benefits for your product team. Here are a few worth noting.

• Reduced risks. Testing changes in a controlled setting helps you dodge any nasty surprises that might mess up the user experience or hurt business performance.
• Improved decision-making. You get solid, data-based insights from product experiments, so you're not just winging it. Say goodbye to guesswork.
• Enhanced user experience. Seeing how users react to changes lets you tweak features for top-notch usability.
• Increased innovation. The framework keeps the creative juices flowing, pushing for continuous improvement and fresh ideas, which are the basis of agile MVPs and iterative development in general.

Sounds handy, right? We're going to cover this itch of curiosity and lay down when and how to approach product experimentation.

When to Hold Product Experiments

Running product experiments is a consistent process and can take part at any stage of the product development life cycle. It's super important at different stages and for various reasons. We'll bring up a few use cases.Before you dive headfirst into running experiments, there's some groundwork to cover:

1. Do some initial research (market research, competitor analysis, and so on).
2. Get to know your target audience. 
3. Understand their needs.
4. Make sure your ideas are solid before you start testing (i.e., go through proof of concept).

Next, imagine you're crafting a new feature. It's the right time to experiment. You need to test different aspects of it—the name, design, user experience, and functionality. Use methods like A/B testing or even a fake door test to see what clicks with users and what doesn't.

Need to optimize your user interface? Another product experimentation opportunity. You gather feedback on your UI changes to help you implement the most appealing and effective design. This is done by:

• hosting live website tests;
• prompting users within the product;
• conducting surveys;
• testing product prototypes.

At some point, you will also need to finalize your startup pricing strategy and set prices for your offerings. Experiment with various price points (maybe a discount here, an odd-even pricing model there) to find out what draws the most customers.

Your product's copy will benefit from experimentation, too. You need to ensure it's clear and engaging. Test it through surveys, five-second tests, and opinion scales to see what resonates best and improves user understanding and conversions.

Thus, you can optimize the user experience, foster continuous innovation, and minimize risks at any stage of product planning, from the discovery phase to development, packaging, and selling. All through experimentation.

Types of Product Experiments

Now let's walk through the product experimentation methods and guess when each of them will be the most actionable. Here we go!

Usability Testing

Picture yourself watching someone use your product for the first time. Usability testing is all about observing how users interact with your product to ensure it's easy and intuitive to use.

You've probably gone a long way from UX discovery and drafting UX wireframes to polish the design of your product. But you can look at metrics like path completion and task completion rates and gather qualitative insights. For instance, you might identify friction points in a new onboarding flow and make necessary changes.

A/B Testing (Split Testing)

When a chef tries out two different recipes for a new dish, he splits the audience into two groups, each tasting a different version. This is A/B testing, also called split testing. You show each group a different page, product, or MVP design version to see which one performs better.

For example, you might test two versions of call-to-action button texts on your landing page to see which one gets more clicks. A/B tests show what actually improves user engagement and conversion rates.

Multivariate Testing

Think of multivariate testing like mixing and matching different ingredients to find the perfect recipe. Here, you simultaneously test multiple variables to find the best-performing combination such as versions of a new onboarding flow to find out which one gets users to complete it more often. You might analyze its different elements like colors, button placement, and step order to discover the optimal setup.

Multivariate testing seems similar to A/B testing, right? It's true, but with one difference: A/B testing deals with something single (for example, a button design), while multivariate covers different combinations of more than one thing (as mentioned, colors, messages, steps, etc.).

Tree Testing

Tree testing evaluates how intuitive your product's information architecture or navigation structure is. It helps you understand user mental models and how easily they find information. For instance, such product experiments can be used for determining if users expect to find a blog under "Resources" instead of "More".

Fake Door Testing

Imagine setting up a sign for a non-existent lemonade stand to see if people are interested. Fake door testing gauges user interest in a new feature or product before you fully develop it. You present a call to action for a feature that doesn't exist yet to validate its potential. It's much simpler than a concierge MVP and may be helpful, for instance, when adding a new option on a website and tracking clicks to measure interest.

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User Interviews

Imagine having a one-on-one chat with your users. User interviews involve conversations to gather qualitative insights about their experiences and preferences. You ask open-ended questions or let users speak aloud while navigating the product. For example, this can be done when discussing user feedback on new features, asking about usability improvements, or running extensive product-market fit surveys.

Beta Testing

You release an almost finished version of a feature to a select group to assess its effectiveness. This helps identify final issues, nurture user relationships, and build advocates. For instance, such product experimentation is often applied for testing a new feature with engaged customers to gather feedback before a full launch. It's a rather safe path somewhere in between a soft and hard launch.

Click Tracking

Imagine tracking footprints in the snow to see where people go. Click tracking records and analyzes user clicks to gain insights into user behavior and optimize the experience. For example, you might tag UI elements, audit clicks, and perform data analysis to track engagement with a call to action and determine its effectiveness.

Funnel Testing (Conversion Rate Optimization)

During the funnel testing, you analyze each step in the user journey to improve the effectiveness of your product or in-app funnels. By identifying where users drop off and optimizing those steps, you boost conversion. For instance, this is done when evaluating the onboarding process to see where users lose interest and then you make changes to keep them engaged.

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What a Good Product Experiment Focuses On

A solid product experimentation strategy makes sure experiments give you useful, actionable insights. This involves several key elements and a structured approach. Let's break down the essential aspects and steps for an effective product experiment strategy.

Clear Hypothesis

Experimentation in product management starts with a well-defined hypothesis. It clearly states what you're testing and predicts the expected outcome. For example: 

‍"We believe that changing the call-to-action button color from blue to green will increase the click-through rate by 10%."

Specific Objectives

Your experiment should have specific, measurable objectives to evaluate success. Think of goals like improving user engagement, conversion rates, retention, or feature adoption.

Defined Metrics

Identify key performance indicators (KPIs) that measure the success of your experiment. For instance, for a new onboarding process, relevant metrics might include completion rates, time to first value, and user retention after one week.

Controlled Environment

Ensure you isolate variables to make sure results are due to the changes being tested. Use control groups and randomization to minimize bias.

Sufficient Sample Size

Make sure your sample size is large enough if you want to achieve statistical significance during product experimentation. This reduces the margin of error and increases reliability. A small sample size might lead to misleading conclusions. Testing tools like Opimizely usually come with calculators for this purpose.

Segmentation

Segment users to gain more detailed insights, like how different user groups respond to changes. For example, a feature might boost engagement among new users but not affect long-term users.

Clear Documentation

Document the experiment design, hypothesis, methodology, metrics, and expected outcomes to ensure clarity and transparency. This facilitates replication and verification of results.

Actionable Insights

The goal is to generate insights that inform product decisions, whether the hypothesis is proven or disproven. Provide clear guidance on the next steps based on these insights.

Iterative Approach

Experiments should be part of an iterative process, continuously refining your understanding or testing new hypotheses based on results. Implementing a constant testing environment on your product is the best practice right now. 

Ethical Considerations

Ensure your experiments are ethical and don't negatively impact user experience. Respect user consent and privacy, and minimize potential negative impacts.

These key elements are everything you need to make your product experiments and strategy effective, produce data-driven decisions, optimize user experience, and foster continuous innovation.

The Product Experimentation Process Step-by-Step

Now, let's move from words to action. We overview the product experiment process and explain how to set up a product experiment.

1. Define the Goals and Hypotheses

First things first, nail down clear, measurable goals for what you want to achieve with your experiments. Then, create hypotheses that spell out the expected outcomes and why you think they'll happen.

Example: "We believe that simplifying the onboarding process will increase the completion rate by 20% because it will reduce user confusion."

2. Set Key Performance Indicators (KPIs)

Next, figure out the metrics that will show if your experiments are a hit or a miss. Make sure these KPIs match up with your goals.

Example: Track the onboarding completion rate, task completion time, or user satisfaction scores if this data is relevant.

3. Select Appropriate Methods

Pick the right experimentation methods to fit your goals, whether it's A/B testing, usability testing, or another approach. Ascertain the methods suit the type of data you need to collect for consequent data analytics.

Example: Use A/B testing to compare different versions of a feature or usability testing to gather detailed user feedback.

4. Plan and Execute Experiments

Craft a detailed plan for each experiment, covering the design, sample size, duration, and tools needed. Then, follow the plan and execute the experiments.

‍Example: You can use tools like VWO or Optimizely to set up and run experiments, ensuring accurate data collection.

5. Analyze the Results and Iterate

Take a close look at the product experimentation data you've collected to see if your hypotheses were on the money or not. Use these insights to make smart decisions about product changes.

Example: If the onboarding completion rate increases, roll out the successful changes to all users. If not, go back to the drawing board with your hypothesis and experiment design.

6. Communicate Findings and Next Steps

Share the results of your experiments with your team and stakeholders. Talk about what the results mean, document and log your findings, and plan the next steps based on what you've learned.

‍Example: Present the experiment results in team meetings, highlighting key learnings and proposed actions.

Product Experimentation Tips

And for sure, the key to success is to learn from the best and their tips:

1. Use control groups to isolate the impact of your changes. This ensures the results stem from the experiment itself and not external factors. As such, Facebook uses control groups extensively in its A/B testing to accurately measure the effect of new features and changes.
   
   
2. Focus on areas with significant potential impact. Prioritize experiments that can drive key business metrics like conversion rates or customer retention. For instance, Amazon prioritizes experimentation on its product pages, where even small improvements can lead to substantial increases in sales.
   
   
3. Always prioritize user experience when designing and running experiments. Ensure tests enhance usability and satisfaction without negatively impacting users. You can tell Apple rigorously tests new features in a way that prioritizes the overall user experience.
   
   
4. Automate the experimentation process to scale efforts and reduce manual work. Utilize platforms and tools that support automation. For example, Spotify uses automated testing platforms to run multiple streaming experiments simultaneously.

Let's see what platforms got to the golden pantheon of platforms to perform a product experiment.

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Useful Product Experimentation Tools

Product experiments software facilitates the design, execution, and analysis of tests. These tools help optimize product features and user experiences based on data-driven insights.

It is worth noting, though, that some tools like Mixpanel or Amplitude serve for slightly different purposes than tools like Omniconvert or VWO. We've put down such differences in the table below.

Here are some popular platforms for product experiments that can help you run yours effectively:

Great Products Aren't Born, They're Made

At the end of the day, the product experimentation process is the key to creating innovative and user-friendly things. By following a structured framework, you can cut down on risks, make better decisions, and keep improving the user experience. The insights from these experiments are pure gold. They help you make data-driven choices and innovate.

Whether you're tweaking current features or diving into new markets, a solid experimentation strategy makes sure your product not only meets but exceeds user expectations and business goals. 

Ready to start experimenting and level up your product? Upsilon is here to plan and launch your products smoothly. Our experienced team can give you a hand in lots of ways, depending on the stage you're currently at. As such, we provide MVP development services as well as team augmentation services for growth-stage businesses. Plus, we always help integrate tools like Mixplanel, as data analysis is integral for successful product creation. So feel free to reach out to discuss your needs!