ROADMAP & RELEASES
Latest updates for Feature Experimentation
From feature flagging to testing and release management, check out all the latest-and-greatest coming (and recently released) to Optimizely Feature Experimentation.
Now streaming!
Our Summer '25 Product Roadmap Series.
Get a first look at what’s coming from Optimizely, shared by our product leaders in a fresh, on-demand format. The perfect fit for your busy summer schedule!
Start with the ultimate Optimizely One Intro to the Series which even includes some Opticon teasers. Then head over to our sessions which span all the hottest topics of the summer: AI, Analytics, Testing & Personalization, Content, and Commerce.
And now on to our product updates...
Change Approvals
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Change Approvals safeguard the quality and safety of feature flag and experiment changes, ensuring that every update is thoroughly vetted before release.
- Approval Workflows: Set up granular approval actions for individual flags and experiments to maintain control over changes.
- Team-Based Safeguards: Assign the right team members to approve or reject changes, adding a layer of accountability.
- Streamlined Collaboration: Use intuitive workflows to manage and track approval processes, facilitating smooth teamwork.
- Change Rationale: Accept or reject proposed changes with clear justifications, ensuring transparency.
- Email Notifications: Keep requesters, approvers, and "watchers" informed with timely email updates throughout the approval process.
Optimizely Edge Agent
Run experiments entirely at the edge as simply as possible, without the need to implement SDKs or compromising on performance, scalability, or flexibility.
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Minimize Latency and Flicker: Reduce latency and eliminate flicker by running experiments entirely at the edge.
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Simplify with Edge SDK: Avoid complex SDK implementations using our comprehensive Edge SDK with built-in decision caching.
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Serverless Scalability: Deploy the Agent in a serverless environment, easing infrastructure scaling concerns and improving efficiency.
- Request to join the beta here.
Metric Impact Report
The Metric Impact Report enable teams to quantify the value of their experimentation efforts and make data-driven decisions.
- Quantify Experiment Impact: Measure the cumulative lift or conversions for a given metric based on the results of completed experiments.
- Project Financial Outcomes: Estimate potential revenue increases from positive experiments or calculate loss avoidance from negative outcomes.
- Comprehensive Reporting: Use detailed reports to understand the full impact of your experimentation strategy, helping teams optimize future efforts.
- Sign up for the beta.
Metrics Module
Metrics module simplifies and enhances metrics management by allowing you to create reusable metrics templates that can be applied across multiple experiments. This reduces repetitive work and ensures consistency in experiment tracking.
- Create Once, Reuse Everywhere: Define a metric once and apply it to different experiments without the need to recreate it each time.
- Streamline Metrics Management: Improve efficiency by managing metrics centrally, reducing manual effort and the risk of discrepancies.
- Role-Based Access: Control who can create, modify, and apply metrics based on user roles and permissions, ensuring secure management.
- Consistency Across Experiments: Ensure accurate comparisons and insights by reusing the same metrics templates across various experiments.
Contextual Bandits
Unlock true AI-powered 1:1 personalization.
- Reduce guesswork and drive conversions by serving your visitors the most optimal and effective experience for them
- Customize bandit algorithms to automatically personalize user experiences
- See which attributes were used to decide which variation to show users
- See how each variation performed, and see traffic allocation over time per variation
Screens are for illustrative purposes only and subject to change.
'Fixed Horizon' & Bayesian Stats Engine: coming soon
A widely-used methodology for analyzing experiment results over the duration of a set period of time, the 'Fixed Horizon' Stats Engine will offer an additional model for customers in regulated environments and/or with well-defined traffic over specific time durations.
- Idead for regulated environments
- Supports pre-defined test durations
- Enables consistent, auditable analysis
Bayesian Stats Engine is a powerful alternative for teams looking for more flexibility and faster insights that offers continuous learning and probability-based decision making. This approach helps you:
- Evaluate expeirment performance at any time without a fixed end date
- Make informed decisions with probabilistic results
- Adapt faster to changing data and business needs
Together these engines give you the freedom to choose the right analysis method for yoru experiments, whether you need strick timing or flexible, ongoing insights.
Screens are for illustrative purposes only and subject to change.
Variable Pick List
Simplify experiment setup and reduce errors with Variable Picklist, designed to empower your entire team. Non-technical users can select from a pre-approved list of variable values, making experiment configuration and targeted rollouts safer and faster. This means:
- Quick and easy selection through dropdown menus tailored to your variables
- Consistent, reliable inputs that keep your experiments and flags running flawlessly
- Marketers, PMs and other teams can independently set up experiments
- Reduced reliance on developers, so your team can iterate faster
That's all for now! Scroll down to see what features are generally available now.
Read our Release Notes for more information on all releases.
