Users report that Labelbox excels in Labeler Quality with a score of 9.3, while Prolific falls short at 7.9. Reviewers mention that the high-quality labeling in Labelbox significantly enhances the accuracy of their data projects.
Reviewers mention that Labelbox's Task Quality is rated at 9.1, compared to Prolific's 6.9. Users say that the structured task management in Labelbox leads to more efficient workflows and better outcomes.
G2 users highlight that Labelbox offers superior Data Quality with a score of 9.3, while Prolific's score is 8.6. Users report that the robust data validation features in Labelbox help in maintaining high standards for their datasets.
Users on G2 note that Labelbox's Machine Learning Pre-Labeling feature scores 8.6, significantly outperforming Prolific's 6.3. Reviewers mention that this automation saves time and reduces manual errors in the labeling process.
Reviewers mention that Labelbox provides better Image Segmentation capabilities with a score of 8.9, while Prolific's offerings in this area are less robust. Users say that the advanced segmentation tools in Labelbox allow for more precise data annotation.
Users report that Prolific shines in Participant Selection with a score of 8.2, which is a critical feature for user research. Reviewers mention that the diverse recruitment pool in Prolific allows for more targeted and effective studies.
Pricing
Entry-Level Pricing
Labelbox
No pricing available
Prolific
No pricing available
Free Trial
Labelbox
Free Trial is available
Prolific
No trial information available
Ratings
Meets Requirements
9.0
41
8.9
182
Ease of Use
9.0
41
8.9
186
Ease of Setup
9.0
21
8.8
110
Ease of Admin
9.0
5
9.1
34
Quality of Support
9.0
39
7.8
152
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