Breaking Down Experience Optimization Platforms (EOP): How to Prioritize Experiments

Redefining the Digital Customer Experience

Nailing the online shopping experience for your customer is key to success – which is exactly what Experience Optimization Platforms (EOPs) were designed to help with. 

As a whopping 86% of shoppers are willing to pay for a better customer experience, making the digital atmosphere both approachable and conducive to conversions is key to securing a competitive edge in today’s market.  

Businesses are no longer just competing on product or price, but on the quality of the digital experience they offer. This means optimizing your websites accordingly has never been more important.

Many brands may not know where to start when it comes to curating the perfect online shopping experience, but the solution is simple. Experience Optimization Platforms (EOPs) serve as a comprehensive answer to create, test, and personalize your user experiences at scale. 

In this article, we’ll break down what an EOP is, explore a core strategic framework, and provide actionable guidance on how to prioritize experiments for maximum impact.

What is an Experience Optimization Platform (EOP)?

An Experience Optimization Platform (EOP) is a software solution that helps businesses analyze, test, and personalize digital customer interactions across apps, websites, apps, and additional points of contact with the user. 

Through a unique combination of informated-based insights, experimentation (like A/B testing), and AI-driven personalization to continuously improve the overall customer experience – Experience Optimization Platforms can help brands to optimize according to their user needs. 

This can result in improved audience retention and in turn, stronger conversion rates, which creates an environment for long-term brand loyalty and success. 

The overview cards below will reveal some of the hallmarks qualities and characteristics of Experience Optimization Platforms:

Why is it important to use an Experience Optimization Platform?

Using an Experience Optimization Platform (EOP) can allow for a robust, integrated suite of tools that allows businesses to expand operations and revenue with ease. This is because EOPs are a “one-stop-shop” for A/B testing, personalizing user journeys, and safely rolling out new features.

Additional benefits of Experience Optimization Platforms include:

• Data-driven Decisions: Data revealed from testing with EOPs can centralize experimentation to make informed choices.
• Improved Customer Loyalty: EOPs can create relevant experiences that keep users coming back.
• Increased ROI: Information from experiments done with EOPs can allow brands to focus their efforts on changes that directly impact key business metrics.
• Increased Average Order Value (AOV): By personalizing the user journey and optimizing the experience, EOPs can lead to an increase in the average amount spent per order.

What is the main difference between an EOP vs. Single-Point Solutions? 

The main difference between EOPs and Single-Point Solutions (point solutions) is that EOPs are best for a multifaceted approach to testing and experimentation, whereas point solutions are specialized tools or software designed to solve one specific problem.

The battle cards below will further break down the differences between EOPs and point solutions: 

How EOPs Benefit 3D Framework: Drive, Delivery, and Development

One of the most beneficial parts to using Experience Optimization Platforms is how they can propel brands to achieving the “3 D’s”.

Better known as drive, delivery, and development – the “3 D’s” in business serve as a strategic model for organizing optimization efforts. 

Drive: Fueling Strategy with A/B Testing

Drive in the “3 D’s” is about using a targeted approach to validate ideas through experimentation. In laymen’s terms, drive is the “driving force” for optimization and consequential testing or experimentation.

The main tools used for “drive” include:

• A/B testing
• Multivariate testing
• Split URL testing

One of the overarching benefits of drive in business is that it can help to mitigate risks, as brands will be able to quickly learn from user behavior and build a foundation of proven ideas.

Example: A retail client who tests two different versions of their product page layout, and finds a winning version through A/B testing which leads to an increase in “add to cart” clicks.

Delivery: Crafting Customized Experiences with Personalization

The second component of the “3 D’s” is when brands refine their method on how to create and execute action plans and tailored experiences to better align with business objectives.

This is where AI-powered personalization, such as using audience segmentation with tools like Emotions AI, can help to provide more dynamic content by basing user experiences on behavior, location, and real-time activity. 

In turn, “delivery” increases engagement, conversion rates, and average order value by showing the right message to the right user at the right time.

Example: A travel website that delivers real-time promotions for last-minute hotel deals to visitors whose browsing history shows exit-intent, which results in a lift in bookings.

Development: Innovating Safely with Feature Management

The last stage of the “3 D’s” is “development”, which centers on building a community of practice and using feature management to reduce the risk of rolling out new features.

This can be done through a variety of tactics such as feature flagging, progressive rollouts, or KPI-triggered rollbacks. During the development stage, businesses can enable product and engineering teams to innovate faster, test new features with specific user segments, and prevent negative impacts on the overall user experience.

Example: A SaaS company rolling out a new dashboard feature to only 10% of its user base to first keep an eye on early results. After closely monitoring the potential feature adoption and verifying performance metrics, they could confidently release this feature to the rest of their users. 

How to Prioritize Experiments: From Ideas to Impact

With all of the different types of testing and experimentation, many brands face a problem with prioritization – not knowing which test is their next best move. 

While it’s true that mature optimization programs generate more ideas than can be tested, knowing when and where to play your experimentation cards is just as valuable. In other words, brands struggle more with deciding which tests to run first as opposed to coming up with a sufficient number of testing ideas. This presents the challenge of not knowing which of your ideas to pursue first. 

To solve this, there are prioritization frameworks which can provide an objective, structured way to rank and determine the best order to test ideas. This allows brands to move beyond gut feelings and one step closer toward information-based decisions. 

Here’s a breakdown of two prioritization frameworks that are used with Experience Optimization Platforms: 

PIE Framework

PIE, which stands for potential, importance, and ease, refers to a basic, structured method for prioritizing various experiments. 

Here’s the meaning behind each letter in PIE:

• Potential: How much improvement can this test deliver?
• Importance: How valuable is the traffic on the pages you want to test? (i.e., high-traffic or high-value pages)
• Ease: How easy is the test to implement, both technically and operationally?

How does PIE work?

PIE framework and prioritization is determined by scoring each potential test or variation according to these categories, usually on a scale between 1 and 10. The method with the highest score is typically the first test to be run. 

ICE Framework

ICE, which stands for impact, confidence, and ease, refers to another lightweight, organized method to help teams determine the best order for their various testing initiatives.

Here’s the meaning behind each letter in ICE:

• Impact: If this test is a winner, what will the impact be on key metrics?
• Confidence: How confident are you that this test will produce a positive result? (According to data, user research, past tests, etc.)
• Ease: How easy is it to launch this experiment?

How does ICE work?

ICE framework and prioritization is decided by rating tests on a scale between 1 and 10 based on the three main facets of ICE: their potential impact, how confident the brand is it will be successful, and how easy it would be to implement. These numbers are then tallied up for a final score, revealing which test should be first in line for experimentation. 

Best Practices for Bold Implementation

Regardless of which prioritization framework you use in conjunction with your Experience Optimization Platform of choice it’s important to use the best practices in experimentation to ensure optimal results. 

These are some of the most effective experimentation practices:

• Create a Centralized Backlog: This refers to making sure that all of your ideas are organized in one place.
• Score as a Team: This involves stakeholders from different departments such as marketing, product, UX, and dev teams to get diverse perspectives.
• Align with Business Goals: This requires ensuring your highest-priority tests directly map to your current company-wide objectives like OKRs or KPIs.

Building a Culture of Experimentation

Beyond tools and frameworks, the overarching benefit of using an Experience Optimization Platform is not only to test ideas with fluidity – but inhabiting the idea that long-term success is more sustainable when there is a shift in how companies view experimentation.

Some of the key, cultural principles that EOPs usually foster include:

• Embracing “Failed” Tests: Working with Experience Optimization Platforms can curate an environment where every result, win or lose, is a valuable learning opportunity.
• Democratize Idea Generation: EOPs encourage everyone in the company to submit ideas to the testing backlog.
• Share Results Widely: Teaming up with EOPs allows brands to better communicate the outcomes and learnings from experiments across the organization. This can also build momentum and excitement for the product while also demonstrating value.

Conclusion: Your Path to Optimization Maturity

Remember, the power of partnering with an Experience Optimization Platform is boosting your strategic value through the use of the 3D framework and structuring the prioritization process for testing and experimentation.

Optimization is not a one-time adventure that stops when a test is released to the public, but a long-time project that subscribes to a continuous cycle of learning and improvement. By teaming up with your EOP of choice, your brand can create a community where the drive to experiment and evolve becomes embedded in every decision and customer interaction.

Evaluating your current optimization process and identifying even one area where you can improve your approach to optimization, whether it’s adopting a framework or simply starting a testing backlog – could be the start of creative and constructive progress.

Are you ready to dare down the path to your next bold idea?

FAQs

Still have questions about experience optimization platforms? Here are the answers you need.

Why is it important to use Experience Optimization Platforms (EOPs)?

EOPs help businesses continuously improve their digital experience with insight-led testing, personalization, and more. This can lead to improved conversions, better customer satisfaction, more efficient decision-making, and long-term brand loyalty.

What are some of the most important tools to look for when choosing an Experience Optimization Platform?

Key tools organizations should look for when seeking a new Experience Optimization Platform include A/B testing, personalization engines, behavioral analytics, and customer data integration. Also, AI-driven recommendations and journey orchestration are becoming increasingly crucial for scaling and automating optimization efforts.

Are EOPs better than point solutions?

EOPs are usually the more effective choice for organizations seeking a unified, scalable approach to optimization across multiple channels. However, point solutions can still be useful for businesses with a very specific initiative to be solved or with a limited scope.

Why is AB Tasty a good choice as an Experience Optimization Platform?

AB Tasty is an excellent platform for experimentation as we offer a wide variety of tools and services from server-side and client-side testing, multivariate testing, traditional A/B testing, and AI-powered features to improve personalization like AdaptiveCX and Emotions AI.