Compare DevCycle and Optimizely Web Experimentation 
At a Glance
Market Segments
Small-Business (60.0% of reviews)
Mid-Market (47.8% of reviews)
Entry-Level Pricing
$0.00
Contact Vendor
DevCycle
Star Rating
(36)4.5 out of 5
Market Segments
Small-Business (60.0% of reviews)
Pros & Cons
Entry-Level Pricing
$0.00
Free Trial is available
Browse all 4 pricing plansOptimizely Web Experimentation
Star Rating
(410)4.2 out of 5
Market Segments
Mid-Market (47.8% of reviews)
Pros & Cons
Entry-Level Pricing
Contact Vendor
Learn more about Optimizely Web ExperimentationSummary
AI Generated Summary
AI-generated. Powered by real user reviews.
- G2 reviewers report that Optimizely Web Experimentation excels in providing a user-friendly experience, making it easy for non-technical users to set up experiments. Users appreciate the platform's ability to deliver real data, which helps them move away from assumptions and make informed decisions.
- Users say that DevCycle stands out for its robust feature flagging capabilities, allowing teams to work on upcoming features without exposing all code to users. This feature is particularly praised for its streamlined interface and the ability to schedule changes, making it a favorite among teams looking for flexibility.
- Reviewers mention that while Optimizely Web Experimentation has a solid overall rating, it faces challenges in feature management compared to DevCycle. Users have noted that DevCycle's dynamic configurations and scheduling options provide a more tailored experience for managing feature flags.
- According to verified reviews, DevCycle's ease of setup and administration is frequently highlighted, with users noting a smooth transition and responsive support. This contrasts with some feedback on Optimizely, where users have expressed a desire for more intuitive setup processes.
- G2 reviewers highlight that Optimizely Web Experimentation is particularly effective for A/B testing, with users enjoying the quick implementation of experiments directly in code. This flexibility allows developers to see the impact of their changes almost instantly, which is a significant advantage for rapid testing.
- Users report that while both platforms offer valuable insights, Optimizely Web Experimentation's reporting and analytics features are seen as less effective compared to DevCycle's data-driven insights. Reviewers appreciate how DevCycle simplifies the process of managing feature flags, making it easier to derive actionable insights from their testing efforts.
Pricing
Entry-Level Pricing
DevCycle
Free Forever
$0.00
For small projects, or people that just want to give DevCycle a try.
- Up to 1000 client-side MAUs
- Unlimited seats
- Unlimited flags
Optimizely Web Experimentation
Enterprise
Contact Vendor
Customized For Your Business.
Free Trial
DevCycle
Free Trial is available
Optimizely Web Experimentation
No trial information availableRatings
Meets Requirements
9.2
29
8.4
296
Ease of Use
8.7
29
8.1
309
Ease of Setup
9.0
24
8.0
155
Ease of Admin
9.3
10
8.2
124
Quality of Support
9.0
21
8.0
252
Has the product been a good partner in doing business?
9.7
10
7.9
119
Product Direction (% positive)
7.4
27
7.8
271
Features by Category
Visitor Behavior
Not enough data
7.8
24
|
Verified
Not enough data
8.5
26
|
Verified
Not enough data
7.6
22
|
Verified
Templates
Not enough data
7.8
24
|
Verified
Not enough data
8.3
23
|
Verified
Not enough data
8.4
24
|
Verified
Personalization
Not enough data
7.6
23
|
Verified
Not enough data
7.7
26
|
Verified
Not enough data
7.9
21
|
Verified
Not enough data
Feature Not Available
Not enough data
7.5
20
|
Verified
Not enough data
7.0
19
|
Verified
Not enough data
9.0
24
|
Verified
Not enough data
8.6
22
|
Verified
Multichannel
Not enough data
8.5
26
|
Verified
Not enough data
6.9
20
|
Verified
Not enough data
8.9
25
|
Verified
Administration
Not enough data
8.0
22
|
Verified
Not enough data
8.5
22
|
Verified
Not enough data
8.2
22
|
Verified
Not enough data
8.1
23
|
Verified
Agentic AI - E-Commerce Personalization
Not enough data
Not enough data
Not enough data
Not enough data
Segmentation
Not enough data
8.8
21
Not enough data
8.1
14
Targeting
Not enough data
7.6
21
Not enough data
7.8
20
Triggered Content
Not enough data
7.8
16
Not enough data
Feature Not Available
Not enough data
7.4
13
Personalized Content
Not enough data
8.0
15
Not enough data
8.1
16
Not enough data
8.7
18
Agentic AI - Personalization Engines
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Data Sourcing
Not enough data
9.3
5
Not enough data
8.0
5
Not enough data
Not enough data
Not enough data
7.2
6
Intelligence
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Management
9.0
23
8.3
24
8.4
22
8.3
25
8.3
23
8.0
23
Functionality
8.7
23
8.0
25
8.9
22
8.5
26
8.6
20
7.6
26
Computing
Feature Not Available
7.9
67
4.7
6
6.4
61
5.7
7
6.9
72
Experimental Design
8.6
7
8.4
70
Feature Not Available
8.7
69
8.5
8
8.7
69
Analytics
6.2
7
8.2
68
Feature Not Available
5.8
62
Agentic AI - A/B Testing
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Feature Not Available
Not enough data
Agentic AI - Personalization
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Not enough data
Categories
Categories
Shared Categories
DevCycle and Optimizely Web Experimentation are categorized as Feature Management and A/B Testing
Unique Categories
DevCycle has no unique categories
Optimizely Web Experimentation is categorized as Personalization Engines, E-Commerce Personalization, Customer Data Platform (CDP), Configuration Management, and Personalization
Reviews
Reviewers' Company Size
DevCycle
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Optimizely Web Experimentation
Small-Business(50 or fewer emp.)
Mid-Market(51-1000 emp.)
Enterprise(> 1000 emp.)
Small-Business
(50 or fewer emp.)
Mid-Market
(51-1000 emp.)
Enterprise
(> 1000 emp.)
Reviewers' Industry
Computer Software
33.3%
Information Technology and Services
23.3%
Banking
6.7%
Manufacturing
3.3%
Sports
3.3%
Other
30.0%
Computer Software
11.1%
Information Technology and Services
9.3%
Financial Services
9.1%
Marketing and Advertising
8.1%
Retail
8.1%
Other
54.4%
Discussions
What is DevCycle used for?
1 Comment
SY
DevCycle is a feature management platform that helps developers and product teams ship software confidently. It gives teams the ability and control to build,...Read more
DevCycle has no more discussions with answers
How does A/B Testing work?
1 Comment
TS
A/B testing is when you have a least two variations of something you want to test. Typically you have a control (which may be the current variant) and then...Read more
What are some ways that I can use A/B testing?
1 Comment
TS
Testing is ongoing and endless. We test new features such as additional form fields in a lead form. We test multiple CTAs to decide which produces the best...Read more
Optimizely Web Experimentation has no more discussions with answers
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