jKool is a good software for capturing user data
December 08, 2022

jKool is a good software for capturing user data

Duc Minh Nguyen | TrustRadius Reviewer
Score 7 out of 10
Vetted Review
Verified User

Overall Satisfaction with jKool

jKool is a software as a service, cloud-based platform for analyzing streaming Big Data which is good for addressing data collection. This service can be used to measure customer experience and user engagement which is what we need when developing new game or getting feedback for old games that we have created.
  • Log Analytics
  • User data monitoring
  • Detecting outlier
  • GUI has too many colors, hard to look at sometimes
  • Sometimes the data displayed can be overwhelming
  • Takes a bit of time to learn
  • Customer data retrieval
  • Open source eco-system
  • Ability to search in real time and in the past
  • Valuable customer data
  • A decent amount of research on learning how it works
  • Real time statistics
No other product that I used is similar to jKool, it's unique product that have good amount of features that I would be opened to invest more in the future if time permit. It still has a long way to go and the first thing it can do is clean up it user interface to make it better.

Do you think jKool delivers good value for the price?

Yes

Are you happy with jKool's feature set?

No

Did jKool live up to sales and marketing promises?

I wasn't involved with the selection/purchase process

Did implementation of jKool go as expected?

Yes

Would you buy jKool again?

No

JKool is a decent tool for retrieving information regarding user engagement and customer feedback for your software products. With these information it's very valuable stepping stone for us to make future updates or produce new products. However, there are some downsides with jKool, two of which are there are too much clutter in the GUI and it takes sometimes to turn how things work.

jKool Feature Ratings

Real-Time Data Analysis
7
Visualization Dashboards
5
Data Ingestion from Multiple Data Sources
7
Low Latency
6
Integrated Development Tools
7
Data wrangling and preparation
6
Linear Scale-Out
8
Machine Learning Automation
8
Data Enrichment
9