Product Experimentation: What Is It And Why Does It Matter?

Product experimentation lets you measure the impact of product changes you’re planning to make. It consists of testing small tweaks at scale and using the results to learn, iterate, and optimize. 

It can be a frustrating practice, especially for those who don’t love the possibility of failure inherent to all trial-and-error processes. But when done right, experimentation leads to innovative and successful products. 

This guide is an introduction to product experimentation, including what it is, why you should do it, and what makes for an effective experiment. 

What is product experimentation?

Product experimentation (or 'product experiment', or 'product testing') is a systematic and data-driven approach to improving products by testing different variations or features before launching them to all users.

It includes testing hypotheses (ideas for improving your product) and seeing whether users respond to them in the way you’d hoped (such as by converting more often or adopting a feature). It helps teams validate specific ways to validate product decisions, reduce risks, improve the user experience (UX), and deliver incremental changes that improve important metrics. 

What are the different types of product experiments?

The most common forms of product experiments are

• A/B testing: this method involves running 2 different versions of a product, website, app, or feature to determine which performs the best with users. It tests elements of your website that affect a visitor’s decision to convert—such as page structure, sign-up forms, and calls to action (CTAs).

• Multivariate testing: similar to A/B testing, but with multiple variables changing at the same time. This is most useful when you’re testing multiple components, and you're trying to find a combination of variables to drive the results you’re looking for.

• Funnel testing: this method involves making changes across multiple pages to see how they affect users’ progress through the customer journey. This is most useful when you have components that need to stay consistent across pages or are testing new paths or shortcuts in the user journey.

• Split testing: similar to A/B testing, except instead of having the 2 web pages competing against each other, the traffic is equally split between existing variations. This methodology is mainly used in instances where changing all assets at once can be costly, and there are potential SEO penalties for having multiple versions of a page.

The 5 components of a great experiment 

When it comes to planning your experiment, the sky’s the limit. You can run tests on pretty much any site element: new features, changes to UX, copy, images…but to generate valuable insights, you’ll need to include these 5 components:

1. The problem

A good experiment solves a real user problem. Use data analysis, market research, and product experience (PX) insights to identify user problems and prioritize your roadmap with reliable user data. For example, some users find the CTA hard to find on mobile. 

2. The (possible) solution

What change can you offer that might solve this problem for your users? Form it into a hypothesis. Be open-minded: there’s a chance your experiment will flop, but that may inspire other ways to solve the problem you identified. For example, I hypothesize that if we make the mobile CTA sticky, it’ll prove easier for users to find. 

3. The benefit to the user

What is the outcome you’d like to see for your users? How might this change help users achieve their goals? For example, users might find a sticky CTA easier to find and click, helping them achieve their goals on our product.  

3. The users

Who are you trying to help? Good experiments begin with a clear understanding of users' current behavior, and a definition of the cohort who will experience the test. For example, this test will run for mobile users who come to our product pages. 

5. The benefit to your metrics

How will you measure success? Good experiments are built around a metric you want to improve. Meaningful data and feedback about the impact of your product changes are the ‘secret sauce’ of a valuable product experiment. For example, we’ll judge his test by its impact on our mobile CTA click rate.

💡 Pro tip: by combining Contentsquare’s product analytics and voice of customer feedback tools, you can spot ideas for customer pain points to turn into hypotheses for experiments:

• Use surveys to gather insights into moments users experience frustration

• Monitor changes to your important metrics (that might flag opportunities for optimization) with a custom product dashboard

• Watch session replays of users dropping off during the sign-up flow to try and identify why they decided to exit 

• Use Journey Analysis to visualize your customer journey information intuitively. It’ll flag which pages users most often drop out from, allowing you to investigate further.

3 preconditions for effective product experiments

Before you actually launch your experiment, there are a few practical and cultural considerations to take care of. Ensure these preconditions are in place to give your experiment the best chance of success.  

1. Set realistic experimentation goals

To embrace a product experimentation culture, you need to take risks, be curious, and accept the possibility of failure. The main goal behind any experiment is to improve your product for your users in the long term: if a hypothesis is proved incorrect, that’s still a valuable lesson to be documented and (quietly) celebrated.   

2. Get buy-in and team alignment 

The most innovative companies have embedded experimentation into their culture and regularly test new features, improvements, and products. 

As a product manager, ensure your whole team—including senior stakeholders—values creative approaches to product improvement and understands that experimentation is a worthwhile time investment.

Contentsquare helps you build a compelling case for your experiment ideas 

To get buy-in on a specific experiment idea, use Contentsquare’s experience analytics. Send engineers a session replay of a user getting stuck, rather than documenting the problem in wordy tickets, or send teammates a heatmap to show them where users click.

3. Establish processes and tools

You need to establish processes and tools to facilitate experimentation. Create a method for running an experiment and analyzing and implementing its results. By training everyone on how experiments work and sharing the same tools, you build trust in the process and the results.

What are the benefits of product experimentation?

Product experiments let you validate your ideas and initiatives with real, unbiased insight about what your users need. Companies that embrace product experimentation are able to capture highly accurate data about their customers and use it to:

1. Save money and resources  

Company time is money: investing development hours in product changes is a financial decision. Product experimentation de-risks this decision and offers numerical insights into whether the changes you plan to work on are likely to pay off. 

In many cases, experimentation data allows you to estimate the impact a feature change will have on your key metrics with a fair degree of accuracy—which is invaluable for budget-savvy teams.  

2. Improve team cooperation  

There’s no arguing with the results of a well-executed product experiment. Hard numbers save frustrating conversations where team members debate whose gut instinct about a potential new feature is better aligned with what users actually want. 

Experimentation culture also promotes good ideas over team hierarchy, leading to a flatter and more cooperative company culture: if a junior team member has a hypothesis that leads to a successful experiment, they will have initiated a feature change that the whole team will get behind and collaborate on. 

3. Give unorthodox ideas a chance 

Because experiments are, by nature, reversible, they’re an opportunity to test ideas that are bolder than you’d dared try otherwise.

For example, maybe you think your idea to create a new feature from scratch is great, but you're worried your customers may not use it. Gathering data from experiments helps guide the direction of the product and feature iterations. 

If the result is successful, it's a clear sign that you should put more effort into implementing your idea across a wider level. If not…no worries. It’s easier to turn off an experiment than to write off an entire feature launch. 

4. Align your product roadmap priorities with user needs

Experimentation lets you make data-backed decisions and better prioritize your product roadmap so it resonates with users and aligns with business goals. 

If an experiment for a new feature is a resounding hit with users, you have all the evidence you need to rearrange your schedule and push forward developing that ASAP. If an experiment shows that fixing a low-impact bug doesn’t affect your user experience or key metrics much…you don’t have to feel bad leaving it for a rainy day.  

When to run product experiments—and when not to

A culture of experimentation establishes a feedback loop with your customers. It moves beyond conversions or acquisition, to improving adoption and retention so your product becomes indispensable in your customers’ lives. 

However, not everything can (or should) be tested. Here are a few instances when a product team should run experiments:

• When you need to understand how your product could do an even better job of satisfying customers 

• To understand how your customers' needs have changed since you launched your product

• To validate ideas for feature improvements with reliable data 

• To troubleshoot issues with reliable user insights 

…and times when experiments won’t be helpful:

• To establish product-market fit or assess whether a product makes sense to build, use product validation instead

• If you’re just looking for successful tests. Overemphasizing the importance of successful experiments may cause employees to focus on low-risk, low-reward hypotheses and avoid testing innovative ideas that may fail.

• If opinions are valued more than data. Nothing stalls innovation faster than a so-called HiPPO or ‘highest-paid person’s opinion’. Empirical results from experiments must prevail when they clash with strong opinions, no matter whose opinions they are.

• To make strategic management decisions. Some things are almost impossible to conduct tests on—for example, strategic calls on whether to acquire a company.

Use strategy, experience, and leadership to drive your team forward through the moments where experimentation can’t be used. In time, you’ll start knowing when to use an experimentation tool and when to trust your gut over the available data.

Contentsquare makes experiments more successful

Product experiments settle debates over whether a particular idea is a good choice for customers and help the whole team support important product changes. For that reason, it’s crucial that experiments—and the user insights that inspire them—are easy for everyone to review and understand. 

Contentsquare offers sharable, visual experience analytics to help you generate ideas for and analyze results from your product experiments. Get inspired with user-centric insights, discover opportunities, reduce assumptions, increase confidence, prioritize fixes, get buy-in from stakeholders and align with your team—all while using just one product. 

To sum up, you can benefit from

• Heatmaps, which help you collect data on how people use pages of your site after a change and can be paired with A/B testing

• Session Replay, which lets you dig deeper into how users behave on a page, and watch what happens when they get stuck or before they exit

• Journey Analysis, which shows you how users move through your important product flows, so you can see where they drop out and spot ways to prevent this 

• Surveys and Interviews, which give you insight into users’ thoughts or feelings on your product—or about your experiment in particular

FAQs about product experimentation