Clarabridge was a solution that helped users understand how customers and employees feel about a company without having to ask. It was acquired by Qualtrics, and its capabilities are now part of the Qualtrics product suite's capabilities.
N/A
Gavagai
Score10 out of 10
Enterprise companies (1,001+ employees)
Gavagai Explorer is a text analysis tool for companies that want to keep track of what their customers think – regardless of which language they speak. Explorer analyzes texts in 47 languages. The texts get automatically analyzed and the results are presented in interactive and share-able Dashboards. Gavagai understands meaning The majority of the text data it analyzes comes from sources such as surveys, reviews, emails, chat conversations, and social…
$3,000
Time used to Set Up
Pricing
Clarabridge (discontinued)
Gavagai
Editions & Modules
No answers on this topic
Small - 3 project slots -1200 credits
€ 120 per month - More or extra credits can be purchased
Number of Texts Analyzing, number of seats, number of projects
Medium - 10 project slots - 1200 credits
€ 400 per month - More or extra credits can be purchased
Number of Texts Analyzing, number of seats, number of projects
Large - 50 project slots - 1200 credits
€ 2,000 per month - More or extra credits can be purchased
Number of Texts Analyzing, number of seats, number of projects
The Entire Web Application
$3000.00
Time used to Set Up
Enterprise
quote: https://www.gavagai.io/request-quote/
Number of Texts Analyzing, number of seats, number of projects
Offerings
Pricing Offerings
Clarabridge (discontinued)
Gavagai
Free Trial
No
Yes
Free/Freemium Version
No
No
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
Buy extra credits at any time
Bought credits never expire
The tool is awesome and the survey tool that was demoed for me is truly one that will be a game changer. I've actually been on site with clarabridge and they are awesome and they truly have a bright future in this industry. As HR analytics takes off and continues to grow, they will continue to become a key in how different talent, initiatives, etc., are assessed and can truly get an insight on the voice of employees on many possible initiatives.
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
Gavagai is well suited for a B2C business that receives a lot of customer feedback in a form of open-ended text. It makes life easier for the customer experience team to efficiently identify the strengths and areas of improvement for the business. It saves a lot of time and also the hassle of analysing text data manually. It is not just a word cloud tool that shows you the words with the most number of mentions. Gavagai directs you towards actionability.
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
With Engagor, it is possible to organize a large volume of mentions in different mailboxes, which is perfect for our large company. With special Smart Folders to drill down into our data, we can make it possible to organize our mentions even more in-depth, divide the workload, and optimize our workflow. This increased efficiency makes it possible to work together closely as a team, across different departments. To sum this up: the Engagor platform provides our company with the perfect foundation to optimize our entire organizational structure.
Another very interesting feature Engagor offers is their helpful and state-of-the-art tagging system. At NMBS we filter through large bulks of mentions and private messages on a daily basis which would be very difficult to organize without Engagor.
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
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 didn't evaluate many options while choosing Gavagai, I had explored a few local vendors whose capabilities were either incomplete or were not up to the mark. Their customer support was also quite poor. Also, the tool was debugged enough which led to frequent crashing. Alchmer although is not a direct competitor to Gavagai, since it's more of a customer feedback tool with additional capabilities of text analytics. I found Alchemer to be extremely expensive. Zonka on the other hand was quite welcoming to feedback from me and promised to develop additional capabilities for my specific requirements although the plan didn't go through due to internal reasons.
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
Well, due to the organization not truly pushing it for its value, we have struggled on this. We have seen great insight into certain projects when trying to improve certain processes or management structure and seeing the decline in those categories for term reasons/explanations but that does not truly say that the problem is fixed. You could draw a parallel but living in assumptions can cause more issues.
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
