Linear is a purpose-built issue tracking and project management system designed for software engineering teams. It prioritizes high-performance synchronization and keyboard-driven workflows to streamline the product development lifecycle from initial triage to feature release.
$12
per month per user
Optimizely Feature Experimentation
Score8.4 out of 10
N/A
Optimizely Feature Experimentation unites feature flagging, A/B testing, and built-in collaboration—so marketers can release, experiment, and optimize with confidence in one platform.
N/A
Pricing
Linear
Optimizely Feature Experimentation
Editions & Modules
Basic
$12
per month per user
Business
$18
per month per user
Enterprise
Custom
No answers on this topic
Offerings
Pricing Offerings
Linear
Optimizely Feature Experimentation
Free Trial
No
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Required
Additional Details
Discount available for annual billing.
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More Pricing Information
Community Pulse
Linear
Optimizely Feature Experimentation
Considered Both Products
Linear
No answer on this topic
Optimizely
Verified User
Chose Optimizely Feature Experimentation
In other companies, all of the feature flag controls were done locally and it got messy after a while. There was no much control on who was doing what. With Optimizely Feature Experimentation, it is clear what feature flags are enabled and which ones are not. It is easier to …
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Linear is particularly well suited for teams that need a fast, intuitive way to organize and prioritize work across multiple projects. In my experience, it's been especially useful for tracking client work by priority, assignee, and project, while providing clear visibility into ownership and progress. Its clean interface makes it easy.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Based on my experience with Optimizely Feature Experimentation, I can highlight several scenarios where it excels and a few where it may be less suitable. Well-suited scenarios: - Multi-Channel product launches - Complex A/B testing and feature flag management - Gradual rollout and risk mitigation Less suited scenarios: - Simple A/B tests (their Web Experimentation product is probably better for that) - Non-technical team usage -
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
It is easy to use any of our product owners, marketers, developers can set up experiments and roll them out with some developer support. So the key thing there is this front end UI easy to use and maybe this will come later, but the new features such as Opal and the analytics or database centric engine is something we're interested in as well.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Linear is missing documentation features like Jira Confluence. We can use Notion but it would have been great if Linear offered more comprehensive solution
Eventhough we can manage releases with projects, it is hard to manage them when there are multiple projects being released at the same time. The initiatives feature kind of handles this but if we can assign tasks to a release that would be awesome
Being able to invite guests without costing extra money. Platforms like Clickup allow you to invite a limited no of guests without costing extra money.
Linear is not good if you are software services company and want to manage multiple client projects. Linear is built for product teams.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Would be nice to able to switch variants between say an MVT to a 50:50 if one of the variants is not performing very well quickly and effectively so can still use the standardised report
Interface can feel very bare bones/not very many graphs or visuals, which other providers have to make it a bit more engaging
Doesn't show easily what each variant that is live looks like, so can be hard to remember what is actually being shown in each test
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
I already spoke to this in a previous question but, if you've ever used Jira, Linear should feel quite natural. It is a project management tool rooted in issues/tickets to which you can also add sub-tasks and various details. There is some customization but Linear has attempted to shape its offering as the most essential features necessary for this type of work.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
Easy to navigate the UI. Once you know how to use it, it is very easy to run experiments. And when the experiment is setup, the SDK code variables are generated and available for developers to use immediately so they can quickly build the experiment code
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
When we are using jira it felt light the application itself is very heavy usage and the UI feel like boring and features were not good as compared to Linear. As QA when shifted to Linear i felt huge difference in process of ticket creation and tracking compared to jira and sometimes Jira would get stuck, but Linear didn't.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
When Google Optimize goes off we searched for a tool where you can be sure to get a good GA4 implementation and easy to use for IT team and product team. Optimizely Feature Experimentation seems to have a good balance between pricing and capabilities. If you are searching for an experimentation tool and personalization all in one... then maybe these comparison change and Optimizely turns to expensive. In the same way... if you want a server side solution. For us, it will be a challenge in the following years
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. TR verified that a representative sample of customers was invited. More Info
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
We have improved various metrics throughout the course of our experimentation program with Optimizely and therefore sharing numbers is tricky. Essentially we only implement versions of the product that perform the best in terms of CVR, revenue/visitor, ATV, average order value, average basket size and so forth dependent on the north star we are trying to move with each release.
A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info
