What is an Experimentation Platform? Uses of Experimentation Platforms

Every business requires constant changes and updates to stay at par with the ongoing technologies and match customers' needs. 

It is possible to gain higher revenues and conversion leads by doing this.

Therefore, it is necessary to follow some strategies and perform experimentation to achieve the same. 

Experiments are designed to attain solid data to analyze the result of a change. It assists in avoiding guesswork and relying on credible statistics and information. 

Hence, experimentation should be an essential part of your business strategy. Several top companies follow this approach and test to fetch the best results. However, very few of them experiment systematically and efficiently. To know more, read ahead.

This article provides a detailed analysis of:

• What is an Experimentation Platform?

• The Experiment Process

• Experimentation Platforms used by Top Companies

• Uses of Experimentation Platforms

• Conclusion 

Let's begin!

What is an Experimentation Platform? [Definition]

Experimentation is the gold standard to test the performance of your website and execute appropriate changes. It helps to curate scientifically-valid experiments to understand the effect of proposed changes to analyze the customer's behavior. Furthermore, managing several interacting experiments within an experimental framework becomes easy and feasible. 

It provides you with additional benefits that comprise monitoring the performance live, comparing the testing approaches, and analyzing what drives the website's performance. 

Good experimentation requires the healthy and efficient collaboration of teams such as data science & analytics, engineering, design, marketing, CRM, etc. 

In addition, various experimentation platforms provide you with tools and techniques. Such tools help perform the experiments and boost revenues by analyzing issues and presenting solutions. Experimentation is a challenging task that requires good research and hard work. 

Therefore, reliable and credible experimentation platforms can help with making this process easier and more beneficial. 

The Experimentation Process

There are some essential steps in the experiment process followed by every experimentation platform. Here, we have listed a detailed description of the same. Take a look:

• Design and review

• Implementing the changes

• Execution stage

• Analyzing and decision-making

1. Design and review

The first step is to formulate an experiment design and document it. It is often termed an experimental flight plan. This design plan consists of various objectives, such as what is the goal? How to plan it? And why are you implementing the change? 

Share this plan or document across all the teams. It also involves effective planning with the help of mutual understanding and analysis. There are various elements to carry out tests on, such as:

• Titles and headers: Changing the titles based on SEO research and analysis can create a difference. You can change the font size, color, style, etc.

• Call-to-action: CTA buttons are highly effective and enhance the conversion rates by prompting users to take any action that may lead to a purchase.

• Landing pages: It is an excellent option to create different landing page versions, introduces them to customers, and record their responses.

• Navigation: Navigation increases the engagement of users on your website. Hence, it's the most effective option to maintain the customer on the page.

• Images: Images play a prominent role in attracting users. It gives an overview of the page and products. There is an option to add alt image attributes that help in SEO.

• Algorithms: Try curating new and effective algorithms for testing purposes.

Often, there may occur several iterations in the planning process. However, it is only for the best and will deliver the most effective results.

2. Implementing the ideas

Implementation requires proper research and testing of new ideas. The entire team involving engineers, designers, and business units must check in and analyze. 

In addition, the data engineers must focus that variants of original pages are assigned to the users as per the plan, instrumentation of metrics is done, and the data is reaching the data warehouse. These experiments focus on several modular components of your website. 

Following a structured implementation strategy makes it easy to put ideas in one place to achieve the desired targets. 

3. Execution stage

After mutual discussion, the team must apply the new ideas to real-time users and record the metrics. This stage is the actual test. It gives a detailed overview of whether the customers adapt to the changes/variations. In addition, optimization and several guardrail metrics such as website loading speed are observed intricately. 

If any problem occurs during this phase, the experiment halts there and then. 

The execution stage shows the actual effects of your variations. 

4. Analyzing and decision making

According to the experiment flight plan, the accumulated data is analyzed through the lens of team experts. The experimental analysis further decides whether to discard or implement the ideas on your website. 

This stage juggles between analysis and decision-making. It is the final stage of the experimentation process, where the results are brought into action. 

Experimentation platforms used by the Top Companies

Web companies and businesses mostly use evident experimentation platforms such as A/B testing. However, large MNCs or companies inhabit massive experimentation programs. Therefore, these companies require platforms to handle a wide array of testing problems at once. 

We have curated a list of the experimentation platforms used by the big companies to gain effective results. Take a look:

• Google - Overlapping Experiment Infrastructure

• Microsoft - Bing Experimentation System

• LinkedIn - XLNT 

1. Google - Overlapping Experiment Infrastructure

Google's experimentation platform follows the mantra of being 'more, better, faster. Adhering to this approach, the team evaluates every minor change that affects the customers at regular intervals. These changes are not just limited to user-visible changes like modifications to a user interface but also range to changes such as different machine learning algorithms that may affect ranking or reach.

• More: Scalability and flexibility are required to run multiple experiments simultaneously. Every experiment needs different configurations to measure the effects of a test effectively. Some experiments need to change the overall traffic strategy, whereas some only require a change in a subset of traffic. Therefore, their platform guarantees both scalability and flexibility while experimenting. 

• Better: Google's experiment infrastructure does not run flawed experiments on the live audience. The team immediately stops such experiments from further execution. It also uses standardized metrics for the fair conduct of experiments.

• Faster: The experiment infrastructure is quick to set up and doesn't hog up much time. Even a non-professional can quickly initiate the experimentation. Furthermore, it includes simple iterations and metrics for evaluation. 

Hence, the overlapping experiment infrastructure focuses on keeping the benefits of a single-payer system (users, ease-of-use) and maintains flexibility, scalability, speed, and robustness.

2. Microsoft - Bing Experimentation System

Microsoft's Bing Experimentation System uses the multilayer design approach. 

In this experimentation platform, the assumption is that experiments do not interact. To maintain this, the tool constantly monitors and prevents such interactions. To accomplish the same, experiment configurations define sets of constraints. These constraints ensure that conflicting experiments do not run simultaneously. 

Furthermore, If the experiments are still interacting, then this experimentation platform uses mappings. It creates disjoint sets of users to carry out every experiment.

After all, if the interacting experiments still manage to pass by these preventive measures, the team detects them while they run live. They monitor all the running experiments based on various metrics to find potential pairwise interactions. 

It's not about a few tests but requires running thousands of tests with algorithms to identify the interacting experiments. If found, the team receives an alert. 

The Bing experimentation system has upscaled the results for Microsoft.

3. LinkedIn - XLNT 

XLNT is an experimentation platform opted by LinkedIn. It is an internal end-to-end A/B testing platform and a key component of LinkedIn's continuous deployment infrastructure. 

The XLNT platform generates automated analysis reports. It includes both:

• Percentage delta and 

• The statistical significance information on various metrics

XLNT offers simple design and deployment of various experiments. In addition, it also provides automatic analysis. The platform is generic and covers maximum domains such as mobile and email. 

Moreover, below-mentioned are the key features and highlights of the XLNT platform:

• Scalability: The platform helps handle a wide range of experiments and hence, a large volume of customers.

• Flexibility: XLNT offers flexibility to different teams to address other requirements.

• Usability: It provides an interactive UI to design, deploy, and analyze experiments.

• Integration: The XLNT platform integrates well with the existing infrastructure and ensures smooth working.

Moreover, the XLNT platform makes it possible to test minor small changes at a low cost quickly and easily. It further helps in the identification of features with high ROI, Return-On-Investment.

With this experimentation platform, LinkedIn has soared high!

Uses of Experimentation Platforms

As mentioned previously, there are various steps in the experimentation process. Each step requires meticulous analysis and observation to find out errors. Efficient and credible experimentation platforms help check the process intricately and allow you to achieve pre-defined targets for your website. 

The critical uses associated with a good experimentation platform comprises of the following:

1. Quick results

With the help of experimentation platforms, you can speed up the process of testing. It further delivers actionable results for the elements with the high engagement of users. These platforms even cover short-order optimization of sites, applications, and even low-converting pages.

The automated testing approaches, including implementing innovative techniques to fetch the best results, deliver quick results. 

2. High user engagement and conversion rates

Testing various elements indicates the customer's behavior with your website. Majorly, the elements tested are landing pages, titles, images, CTA, algorithms, etc. The experimentation tools provide you with the most effective strategies to convert visitors into sign-ups and purchases. 

This helps boost the conversion rates and achieve desired revenue targets for your business. 

3. Efficient assignment of subjects

It helps in assigning subjects such as users or sessions to several variants. Doing so ensures that the same subject doesn't receive multiple variants. 

Moreover, the platform helps maintain this assignment as long as the testing continues. After that, it shifts the respective subjects to the assigned variants at run time. 

4. Run the experiment at your convenience 

The platform allows halting the experiment if any bug is reported or guardrail metrics indicate problems. This results in the quick address of issues and faster solutions. 

Hence, there is the freedom to start and stop an experiment at your convenience.

5. Efficiency and effectiveness

It also brings effectiveness and efficiency in flight plans, decisions, and analysis. The planning process is highly optimized and provides ways to avoid sloppy analysis. 

In addition, the tool also guides to implementation of best ideas based on previous results. 

6. Automatic analysis

The experimentation platforms help in the deep inspection and testing of experiments before launching or running them. It further automates the standard protocol analysis to skip p-hacking and early peeking anomalies. 

7. Flexibility, Scalability, Robustness

These tools help boost flexibility, scalability, and robustness in your website. They help to increase the conversion rates and boosts revenues for your business. 

Overall, the experimentation platforms prompt the companies to test and formulate new ideas to soar high. A credible experimentation platform instills the atmosphere of fast and innovative growth of a business. 

Conclusion

If you seek to optimize your website and escalate your growth, experimentation platforms are highly recommended. They are the solution to all your website-related problems. Such tools give you a deep insight into the mechanics of website work and locate errors to give in the best results. 

Moreover, gaining traffic is the ultimate goal of any website or business. But at times, no matter how significant the number is, traffic cant lead to the expected conversion rates. This is where experimentation platforms come to the rescue. All the tools and techniques assists in the progress of a business. 

As explained in the article, they present you with the most effective tools, methods, and automated techniques to optimize your website and gain results. There are a plethora of uses associated with such platforms as well.

This article presented you with an in-depth analysis of the experimentation platform, its structure, and its uses. We hope that the information helps you gain clarity and resolve ambiguities regarding this topic.

Keep learning!