96+ A/B testing use cases and examples, sorted by industry (with actual results)

We pulled 96+ real experiments from 12 industries. Not tips or best practices. The actual tests, results, and use cases.

Opal Experimentation University graduation stories: Class of July '26

Meet the Class of July '26. 62 marketers spent five days building AI agents inside Opal Experimentation University. See what problems they solved with agents.

5 ways to wow in your first 90 days as a product and experimentation leader

Start strong, build trust fast, and prove you’re exactly who they needed.

Test and Learn key takeaways

AI and feature experimentation: Maximizing value of AI solutions

Enterprises are rightfully cautious about the possible pitfalls and risks associated with deploying AI. The solution? Feature experimentation.

1:1 Personalization: How to create omnichannel experiences at scale

Learn what 1:1 personalization is, why it's important, and how to use robust data collection and analysis to deliver a personalized customer experience.

Five best A/B testing tools for product managers in 2024

Treating experimentation as an afterthought is a mistake. Because what if the wrong idea was built from the start? For success, you need to integrate A/B testing into your product development process. See how.

Pricing page: 6 tips to optimize and convert under pressure

Your pricing page isn't just about making it pretty. It's about simple pricing, onboarding well, and adding value through use cases instead of slashing prices.

Understanding and implementing guardrail metrics: Your system's safety net

Guardrail metrics catch what your success metrics miss. See how to balance primary metrics with safety nets that catch problems before they impact your revenue.

The 10 biggest challenges of product marketing

Product marketing comes with a host of challenges. Some say product marketing should lie with the sales department, while other pin marketers for the task. On the other end, some people believe it's more or less the same as a product manager's job. So, even before we uncover the challenges of…

Personalization strategy roadmap: Reach the right person, at the right moment

See how the combination of customer data, powerful testing, and real-time website personalization is transforming the possibilities of the digital world.

Why experience optimization needs a platform, not point solutions

Organizations once used experimentation to validate ideas. Today, they use optimization systems to continuously learn and improve every digital interaction.

Personalization and data: A brief overview of compliance and best practices

Personalized marketing is in a place where the line between "delightfully tailored" and "creepily invasive" is thinner than the fine print on your privacy policy. See how to navigate data regulations, one personalized experience at a time. 

Warehouse-native analytics: The future of data-driven experimentation

See how warehouse-native analytics enable organizations to test against true business outcomes, while keeping entire data in-house and maintaining governance.

50 mobile app development tips for acquisition, engagement and retention

It’s more important than ever to stand out from the crowd. To be talked about. To be remarkable. The question is: How do you develop a mobile app that is so valuable that people use it every month? Every week? Or better yet – every day?

How to engage more users and improve app performance using mobile app A/B testing

One of the tools app developers and mobile product managers are increasingly adding to their toolkits is A/B testing. Here are three simple yet effective in-app tips if you're just getting started with the process of future-proofing your mobile app and improving your retention rate.

Intro to canary deployment: Ensuring smooth rollouts and minimizing risks

Canary deployments can be a useful proposition. By gradually rolling out the new version to a small percentage of users, you can identify and address any problems before they affect everyone. See how to use it to reduce the risk of problems in production.

AI ethical issues you should consider as a digital business to stay out of trouble

Using AI for bouncing off ideas and copy-pasting AI output to completely automate your content creation process is not the same thing. Here're AI ethical issues you should consider...

Product delivery: How to use experimentation to deliver features without risks

It's more important than ever to deliver products that meet customer needs. But how do you do that without risk and improve product delivery? You do it by building a test and learn culture. Here’s how you can implement it at your company. 

How to build a culture of experimentation

Having a culture of experimentation in place can help you build and execute experiments that impact the bottom line. Here's a list of 6 measuring pillars you can use to learn more about the customer journey and have confidence in your a/b testing methods based on statistical results.

Personalization strategy: A roadmap to create an effective plan in 2024

From segmentation to AI-rich optimization capabilities, the combination of customer data, powerful testing, and real-time website personalization is transforming the possibilities of the digital world. See how.

101 A/B testing ideas to improve conversions

101 A/B testing ideas to optimize each part of your digital experiences including homepage, category pages, mobile pages, website search results, and more.

Optimizely warehouse native experimentation vs. Amplitude, Statsig, and Eppo

An honest comparison to help you choose the best warehouse-native experimentation platform for your team - even if that's not us.

Warehouse native experimentation: Why teams don't trust results, and what you need

From ideation to results: AI experimentation is changing how we run tests (for real)

AI workflow agents now handle the work that used to involve waiting at every stage of the experimentation cycle. See how AI can help your A/B testing strategy.

The truth about Optimizely’s impact on A/B testing performance (And how edge delivery changes everything)

How Optimizely's solutions including Web Experimentation, Edge Delivery, and Feature Experimentation balance testing capabilities with performance requirements.

Personalization ROI: How to not waste your time

Stop collecting vanity metrics that prove nothing. This guide shows how to measure personalization ROI across your digital experiences.

Warehouse-native analytics webinar: 5 takeaways for data chasing teams

Our experts showed how integrating directly with your data warehouse can unlock insights that drive real impact, all from your single source of truth. 

AI personalization: How AI outperforms human customization

Letting AI do all the personalization work for you is the simplest way to ensure that you’re being met with customers that are excited to speak with you.   

Behavioral segmentation: A complete guide

Behavioral segmentation observes what your customers do, finding patterns in their journey, and using those insights to group similar behaviors together.

A guide to website redesign: (Kinda) everything you need to know

Looking to update your website for 2026? Here are the signs you should redesign your website and steps for a successful website redesign in the AI-first world.

Customer experience management: Manage journeys, not touchpoints

Customer experience management (CXM) optimizes every detail of the customer lifecycle, from their first encounter with a landing page to the thousandth purchase

The leader’s guide to building and retaining a rockstar experimentation team

Experimentation requires a blend of analytical thinking, creative problem-solving, and technical expertise. See how to hire, structure, and retain top talent.

Landing page optimization in 2025: Personalize to turn visitors into customers

Traditional Landing Page Optimization (LPO) tips don't work anymore. Why? Because your visitors are individuals with unique preferences, behaviors, and pain points. See how landing page optimization is changing.

Failing brilliantly: The secret weapon for experimentation success

When optimizing, there are no failures— only chances to learn and grow. Discover how to extract insights from every test, successful or not, and build a culture of continuous improvement in your experimentation program.

Mastering data-driven decisions: The key to successful product experimentation

Explore the tension between intuition and data. Learn why teams struggle with data-driven decisions and discover how to navigate the complexities.

In-house experimentation platforms are a house of cards

As organizations scale their experimentation efforts, they face a critical decision: Buy an existing experimentation platform or build their in-house solution.

10 product ideation techniques to spark innovation

Nobody wants a new product or feature that's just... meh. Enter product ideation techniques. From classic brainstorming to modern approaches like "painted door tests," each approach helps you transform your ideas into features people will actually buy and use.

5 myths killing your A/B testing and experimentation program

It's very easy to assume what works and what doesn't work on a website. Here are 5 myths that you need to avoid to truly scale your experimentation program.

Content workflow: How AI and specificity is the secret to creating great campaigns

A content workflow involves a series of tasks performed by a team between the ideation to delivery steps. Here's how it can be a content-compounding machine for your content engine.

10 A/B test examples that work (From our analysis of 127,000 experiments)

We analyzed over 127,000 experiments across retail, SaaS, and B2B. Here are 10 best A/B testing examples that drove results and how to make them work for you.

A/B Testing: How to start running perfect experiments

The bigger a company is and the more senior folks are involved, the more people hesitate to experiment. To build a culture of experimentation, you need to rethink your approach. In this article, see more about the science of running perfect experiments and what kind of A/B tests can help you deliver conclusive test results.

How to calculate sample size

It's always hard to measure if your tests have adequate data to show conclusive results. You can fix this massive problem with two simple solutions: a sample size calculator and a stats engine. In this article, see how to calculate sample size, prove results and improve your confidence level.

Conversion Rate Optimization best practices

Most CRO best practices are often influenced by the ideas that focus on taking visitors to the buying moment. This is where experimentation comes into play. In this blog, learn how to test those ideas and find tips to boost conversion rate optimization.