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
Gavagai
Editions & Modules
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
Gavagai
Free Trial
Yes
Free/Freemium Version
No
Premium Consulting/Integration Services
Yes
Entry-level Setup Fee
Optional
Additional Details
Buy extra credits at any time
Bought credits never expire
Deputy Manager - Consumer Insights and Brand Development at Aditya Birla Management Corporation Pvt Ltd (Apparel & Fashion, 10,001+ employees)
Chose Gavagai
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 …
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
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
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
