Websites and applications that load quickly and deliver seamless experiences not only enhance user satisfaction but also drive conversions. To achieve these goals, organizations turn to experimentation platforms like Optimizely Experimentation to fine-tune their digital assets. In this thought leadership blog post, we will explore the key performance indicators (KPIs) for performance optimization, the impact of Optimizely Web Experimentation and client-side experimentation, and why Optimizely server-side experimentation shines as the superior choice. We will also delve into the significant value of enhancing performance through experimentation.
Defining Performance KPIs
Before diving into the impact of experimentation on performance, let's first establish the key performance indicators that matter:
- Page load time: The time it takes for a web page to fully load and become interactive.
- Page speed score: A comprehensive assessment of a webpage's loading speed, considering various elements like images, scripts, and CSS.
- Bounce rate: The percentage of visitors who leave a webpage without interacting due to slow loading times.
Conversion rate: The percentage of visitors who take a desired action, such as making a purchase or filling out a form.
User experience (UX): The overall satisfaction of users while interacting with a website, encompassing factors like navigation, responsiveness, and visual aesthetics.
Optimizely Web Experimentation: With great power comes great responsibility.
While Optimizely Web offers a powerful platform for A/B testing and experimentation, it predominantly operates on the client side. Client-side experimentation, although effective for making rapid changes to user interfaces and content, can sometimes introduce performance bottlenecks:
Flicker effect: When variations load asynchronously, users might experience a flicker as the original and variant content swap, leading to a poor user experience.
Mobile considerations: On mobile devices, client-side scripts can be especially taxing, as they may require more processing power and network bandwidth, leading to slower load times and reduced conversions.
Optimizely Performance Edge: As fast as it gets client-side
Optimizely's Performance Edge solution focuses on optimizing the performance of A/B tests by reducing latency and improving the loading speed of variations. This is achieved through the use of content delivery networks (CDNs) and edge computing technology.
Edge delivery: Performance Edge leveraged edge servers located closer to end-users to deliver A/B test variations, reducing the time it takes for users to receive and render content. This resulted in faster and more responsive web pages.
Latency reduction: By serving A/B test variations from edge servers, Performance Edge aimed to minimize latency and page load times, creating a smoother and more seamless user experience.
Improved testing accuracy: Faster delivery of A/B test variations meant that users could be exposed to the correct experiment variations more quickly, reducing the risk of inaccurate test results due to delays in content delivery.
Global scalability: Performance Edge was designed to scale globally, ensuring that A/B tests could be conducted efficiently across various regions and time zones, providing consistent and optimized user experiences worldwide.
Optimizely Feature Experimentation: Zero latency, full responsibility
Optimizely's Server-Side Experimentation (SSE) is designed to address the performance concerns associated with client-side experimentation:
Seamless content delivery: Variations are served from the server, ensuring a smooth and flicker-free user experience.
Enhanced mobile performance: SSE is particularly advantageous for mobile optimization, as it reduces the burden on the device's resources and minimizes data transfer.
Improved SEO: Faster page loading times positively affect search engine rankings, making SSE a great choice for organizations focused on organic traffic growth.
The tools in summary
Optimizely Web Experimentation focuses on providing best in class visual editor, making light weight changes a breeze. While Optimizely Web Experimentation decreases the necessity for developer resources, it should be used responsible. As organizations build a successful testing program the often seek to add developer resources to the testing team, and often transition to running some experiments through Performance Edge, or Feature Experimentation Solutions.
Optimizely Performance Edge focuses on a balance between the best features of Optimizely Web, while prioritizing speed and code/asset delivery. By utilizing the lates CDN technology and edge computing we can often make experiments and experiences much more performance. Organizations that are focusing on delivering content from the edge often choose to use the Optimizely Performance Edge solution selectively, above the fold, or on critical pages such as checkout where speed and performance are paramount.
Optimizely Feature Experimentation is focused on enabling the developer to create experiments and experience with no overhead latency. While you lose the ability to create experiments in a simple visual editor, you eliminate the impact to performance, and unlock deeply complex use cases by taking the SDK based approach test experiment delivery. For example, testing different vendors or 3rd party solutions to drive the best return on spend in your tech stack is a use that case is suited for Optimizely Feature Experimentation, over our other solution offerings.
In the world of digital experiences, performance optimization is paramount. Optimizely, with its client and server-side experimentation solutions, empowers organizations to enhance their digital performance. While Optimizely Web Experimentation is valuable for UI and content testing, Performance Edge and Feature Experimentation stand out as the superior choice when performance is more critical..