Dovetail, headquartered in Sydney, aims to enable the world to create better products and services through deep customer understanding. Dovetail states they empower 45,000+ people, from agencies to universities to Fortune 100 companies, to make sense of their customer research in one collaborative research platform.
$0
for a single individual, channel, and research project
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
Dovetail
Optimizely Feature Experimentation
Editions & Modules
Free
$0
for a single individual, channel, and research project
Professional
$15
per month
Enterprise
Contact Sales
per year
No answers on this topic
Offerings
Pricing Offerings
Dovetail
Optimizely Feature Experimentation
Free Trial
Yes
No
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
Optional
Required
Additional Details
Discount available for annual billing on the Professional plan.
Well suited for: A product team with one FT person dedicated to research and operations to ensure the DT stays up to date, since its automated connectors are not that robust for lower plans. Eg., Salesforce doesn't work great without an enterprise plan, and you have to use outside automated workflows to feed in data from other sources of user feedback (e.g., Google Docs, Sheets). An enterprise team with more engineering time to dedicate to customizing their user research workflows.
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
I really like the User Interface, how easy it is to have all your research data in one project and how visual it is to understand where are things. It does have a good User Experience.
I like how nice and easy it is to create categories or use the ones auto generated as a starting point. It is very easy to create a color coded set of categories that help make sense of the data.
I like how easy it is to see the video snippet of a specific highlight.
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
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
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
Because we are really happy with the tool and it’s capabilities at the moment. The price increase is the main issue we can have but the features are getting better and better. It really saves a lot of time for our team and allow us to collaborate more efficiently with certain stakeholders that often did not réalise how much research we conduct. Now they can just have a look to it by themself!
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 relatively intuitive but it does take some practice to get used to the platform and understand the capabilities and limitations. There are also times that we have run into issues where the people we are sharing reports with either cannot view them or access is not provided. Additionally, the ability to export any of the video clips or snippets has created some frustration since we want to include the great findings that Dovetail helps put together, but need to bounce between screens or share after-the-fact rather than embedding it directly into a readout deck.
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
Regarding performance, I would say it’s satisfactory. Adding data and transcriptions is really fast and efficient, and can be done in the background, so I’m never hindered by these aspects. However, all the new AI-generated features are still somewhat slow to run. It’s nothing major, but it should improve in the future.
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
Support was good, especially when it comes to the capability of your support agents and engineers. But as i am located in Europe, the difference in the time zone made it hard to communicate with your offices and kept my work way back
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
The training went very well, and we co-built it to really address our needs. I also think it was beneficial to have feedback coming from someone other than myself (since I manage the tool), as it helped reinforce the points I wanted to highlight. The team’s feedback on the training was very positive.
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
We looked at a few other options, Marvin and Reforge Insight. They were both pretty cool platforms that operate largely or entirely on AI, but neither quite fit our needs. Reforge Insight was cool, but it did not have all the features we needed from Dovetail, and switching to Marvin felt like a massive undertaking. We have so much data in Dovetail that the "cost" of leaving feels monumental. Besides, Dovetail fits our needs right now.
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. More Info
Management is quite straightforward; it’s easy to change access if certain stakeholders need to use it. The repository features are accessible to all teams, making it a good entry point into the tool. The more people use it, the more powerful the tool becomes, so it seems truly scalable to me. The limits are more financial, in terms of accessing additional features.
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
Having a centralized research space is a game changer. Makes it so much easier to hand over research if working with new people and have system in place (using the templates). Saves so much time. We don't have hard numbers on the hours saved but we are much more efficient using Dovetail than without.
The tagging system in general is amazing and allows for consistency in topic marking. This was non-existent for our team before Dovetail and now we can do much more granule reports with exact # of times something was said with accuracy.
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
