Optimizely recently hosted a webinar on Optimizely's 24 Summer Product Roadmap. It provided insights on the Optimizely One platform’s recent and ongoing updates, and key themes shaping up Optimizely’s product strategy for individual products, especially its experimentation capabilities. This blog summarizes some of the key takeaways from the event from Optimizely’s 24 product roadmap webinar: Experiment breakout session. The roadmap for other products will be covered in Part 2 blog.

 The webinar started with the following updates on the Optimizely Data Platform:

• Real-Time Segments now available: The capability allows users to create real-time segments in the Optimizely data platform based on first-party or third-party data from other CDPs for personalized targeting, run targeted experiments, and deliver impactful personalized campaigns.  Thereby, allowing businesses to build custom audiences by segmenting them based on their preferences and behaviors, easily adapt to changing market trends and user behavior by delivering content in real-time, and leverage this new data for testing and personalization.
• New Integrations for Impactful Experimentation: Furthermore, the Optimizely Data platform would offer new integrations with various other systems including salesforce CRM and marketing cloud, Shopify to help businesses gain a comprehensive view of the customers. It will also allow users to automate workflows by providing connectors to platforms like Marketo, Demandbase, 6Sense, and other systems.
• New Centralized Login System: Opti ID is a new login system that works across all Optimizely products. It allows users to manage rules, and permissions, and easily switch between Optimizely products for a more cohesive user experience across all the products. This ensures a consolidated authentication process, seamless cross-product authorization, and navigation, and provides a centralized administration for users, roles, and permissions.

Followed by the platform updates, the webinar provided a quick recap of 2023 for its Optimizely's Experimentation product features:

• Continued Investment in Experimentation: In 2023, Optimizely released over 70 new products, features, or enhancements to experimentation and continues innovating its capabilities in 2024.
• High Experiment Volume: The platform delivered over 3.9 billion "optimized experiences" in 2023. The company focuses on growing this number by enhancing its experimentation and personalization capabilities as well as broadening its product portfolio.
• AI Copy Generator: This feature within the web experimentation Visual Editor allows users to easily create variations of any piece of content for the experiment.

Next, the following key focus areas of Optimizely’s Product Roadmap for 2024 were covered in detail:

Workflows: Optimizely aims to streamline the entire experimentation process, including research, ideation, collaboration, design, and experiment creation within the Optimizely platform.

• Experimentation Collaboration in FX (in beta): This will help in collaborating and managing the entire experiment lifecycle in one place. The roadmap places a strong emphasis on experiment collaboration, aiming to streamline the entire experimentation process for large-scale programs.
• Live calendar views:  users can collaborate and build, design and launch experiments on time, easily orchestrate the programs and customize views for stakeholders. The calendar can also be embedded into other collaboration tools like Confluence to increase the visibility of the experimentation program. 
• Intelligent Idea Intake Forms: The platform also offers the idea intake form to take ideas from the teams or products and infuse those with the experiments. The test brief templates to ensure experiments are created to meet the testing standards. These templates capture required information like hypothesis, location, and business goals for better collaboration.
• Automated Workflows: These templates can be used in workflows for automated experiment creation steps and assign tasks to specific team members (product managers, designers, developers, etc.). This includes incorporating approval stages for quality control and compliance.
• Design Collaboration: The feature enables direct collaboration on experiment design variations within the platform eliminating the need to email design documents. This means users can annotate and discuss design elements directly in Optimizely, streamlining communication and feedback loops. It connects with collaboration tools Figma, InVision, and Lucid to facilitate real-time communication.
• Opal Chat: Provides a copilot experience, which acts as a virtual assistant, answering questions on various topics related to experimentation, including technical aspects (SDK implementation), strategic approaches (experiment prioritization frameworks), and more, and saves time by eliminating the need for external searches or consultations.
• Winner Rollouts: Enables safe rollouts of winning variations to all users directly from Optimizely (web experimentation) without developer involvement.
• Experiment Feature Flag Scheduling: Allows users to schedule changes to the feature flags, experiments, and targeted deliveries, and automates the entire rollout scheduling.
• AI copy generator V2: It enables users to select any visual editor element and then generate alternative copies. While AI is a major focus, Optimizely prioritizes user control as it strategically leverages AI to streamline and shorten workflows launch more experiments at scale.
• AI Variable Suggestions: Mirroring the approach with the AI copy generator, Optimizely is enhancing feature experimentation. A powerful tool within feature flags, variables allow granular control over various aspects of a feature (e.g., image displayed, button text) without developer involvement. To streamline experiment design, Optimizely is introducing AI-powered brainstorming. Based on your hypothesis, the AI will suggest relevant variables to consider, allowing you to easily add them to your feature flag. This feature empowers users to create more meaningful experiments while retaining control over the process.

Analytics: Optimizely is committed to improving analytics capabilities to help users gain deeper insights from their experiments to facilitate quick learning from experiments.

• Metrics Filtering:  This new feature allows users to analyze experiment metrics in greater detail by breaking them down into subcategories. It provides a more granular understanding of how experiments impact different parts of the business.
• BigQuery Data Sharing : This feature leverages Optimizely's partnership with Google, and has native support for BigQuery. This integration enables real-time access to all data collected by Optimizely through Google's data sharing capabilities. It allows teams to conduct further analysis using their existing analytics or data science tools, fostering increased data trust. With real-time data availability, users can verify if their information is being optimized effectively within Optimizely.
• Google Analytics Partnership: Optimizely is further strengthening its partnership with Google Analytics. In addition to the existing GA4 integration that automatically generates in-depth experiment reports within GA4, Optimizely will soon allow users to leverage audience segments defined in Google Analytics for targeting directly within Optimizely experiments. This eliminates the need for manual data transfer and streamlines the process of using existing audience segments for experiment targeting.

Enterprise Scale: Optimizely aims to provide support for large experimentation programs.

• Flag and Environment Permissions: As experiment programs scale with more teams and users, this feature allows for more precise permission management. Users can define who can view, edit, or launch individual experiments or feature flags, down to the individual entity level. This granular control is particularly valuable in regulated industries or when granting extensive power through feature flags. It empowers users to mitigate risks associated with large-scale experimentation programs.
• Onboarding Guides: Many organizations experience frequent turnover or require ongoing training for new personnel. To address this, Optimizely is investing in comprehensive in-product guidance. This includes expanding the existing Opal copilot experience with additional help content, along with dedicated getting started guides and walkthrough videos. These resources will equip new users to confidently run experiments within the platform.
• Experiment Program Reporting: Users will gain insights into experiment volume, success rates, and comparative data against their peers. This functionality will allow organizations to track team contributions, assess overall program value, and identify areas for improvement.
• Contentful Integration: Launched a year ago, the product lacked a refreshed integration with Contentful, a popular content management system (CMS). This update, scheduled for this quarter, streamlines the process for existing Contentful users. They will now benefit from native integration with feature experimentation, enabling direct experiment launches from within Contentful. This enhanced integration aims to accelerate experimentation velocity for Contentful users.

Developers: The platform will offer a differentiated developer experience to speed up the experimentation program.

• Next Generation Web Experimentation: Recognizing developers as the core user base, they're introducing "next-generation web experimentation." This feature addresses the current slowdown caused by a reliance on JavaScript snippets. By moving processing to the network edge, Optimizely aims to deliver the world's fastest web experimentation solution. This translates to significant website speed improvements as experiment changes are applied directly at the network edge, before reaching users. Additionally, user assignment and experiment changes occur at the edge, reducing the amount of JavaScript delivered to websites. This innovative approach eliminates the need for developers to rebuild or create new projects within Optimizely.  The update seamlessly integrates with existing projects and experiments, minimizing disruption for developers.
• Dynamic Selector Support: Optimizely is introducing "dynamic selector support" within the visual editor. This intelligent feature empowers developers to implement experiments without requiring developer involvement for every single change on websites with dynamic selectors.
• Change History Webhooks: Webhooks allow real-time notification of any changes within Optimizely's feature experimentation tool. This enables developers to integrate Optimizely with various external systems. For example, imagine receiving a Slack notification upon launching a specific experiment or any experiment within a project. Webhooks can be used with tools like Zapier or IFTTT to automate workflows triggered by events in Optimizely. This functionality empowers developers to streamline processes, such as automatically verifying experiment configuration or notifying teams about potential issues.
• 1 click Project Migration:  A user-friendly one-click migration tool is available to seamlessly transfer projects from the legacy full-stack solution to the new feature experimentation product.
• Growing List of Experimentation: Optimizely offers new list of integrations within the Feature Experimentation settings. Users can explore a wider range of options, enabling direct activation or finding connection instructions through the provided documentation.

After covering the new updates for all four key areas including Workflow, Analytics, Enterprise Scale and Developers across the Optimizely One Platform, the session was opened for a Q&A round.

According to Shruti Jadhav, Principal Analyst at Quadrant Knowledge Solutions, “Optimizley has well prioritized its focus areas for product improvements and investments across four key areas including- workflow, analytics, collaboration, and developers that directly impact the speed of the experimentation program. Its new features for experimentation collaborations for managing the entire experiment lifecycle in one place, “next generation web experimentation” capabilities to offer a differentiated developer experience to speed up the experimentation program, as well as extensive availability for third-party integrations, helps Optimizley platform to deliver targeted, optimized, and sophisticated experiences at scale.”

Optimizely's 2024 roadmap doubles down on experimentation and personalization, with a focus on streamlined workflows, AI-powered features, and deeper analytics. This comprehensive approach, coupled with enterprise-grade features and a developer-centric experience, positions Optimizely as a leader in helping businesses unlock the full potential of experimentation and deliver optimized customer experiences at scale.  

[This blog is the 1^st Blog in a Two-Part Series around the Topic – ‘Optimizely Unveils Product Roadmap for H2 2024’]

Author: Shruti Jadhav, Principal Analyst at Quadrant Knowledge Solutions