Better understanding and superior insights in 45 languages

What is Gavagai Explorer?

Instant qual-to-quant conversion and analysis of unstructured text data - such as answers to open-ended survey questions, customer reviews, online mentions, customer support tickets, and other customer interactions - without prior computer skills.

Advanced analysis, with automated thematic clustering and by scoring themes against multi-dimensional sentiment, to get valuable and robust insights from text data, in more than 40 languages.

8 standard sentiments across all languages and the possibility to model any bespoke concept.

Single-handedly process small or large amounts of qualitative data - at a lower cost and with higher quality output.

The market’s most versatile solution - chosen by the global leaders in market research. Check it out right here:

Try it for free

Newest Features

  • Search function for topics. Working with your topics has become much easier - just start typing the word you’d like to add and scroll through the alternatives in the drop-down menu. These come from the complete matching list of all the terms used in your text file.
  • New suggestions without new exploration. Get newly generated suggestions directly in one click by pushing Get more button and continue working with your topic.
  • Upload your own model. Upload Excel or CSV file and use it as your own model on the Models page.
  • All results in one single Excel report. Gavagai Explorer Excel report consists of 3 sheets.
    Summary: structured results according to the project's topics and groups.
    Data: detailed sentiment analysis for every text from the original file.
    Metadata: general information about the project and analysis.
    And you can also configure the contents by adding a Target Concept, Keywords and custom concepts before generating your report.
  • Report history. All types of generated reports are saved on the Edit page under Reports.
  • Append history. The history of the project's previously uploaded files is always visible on the project Edit page.
  • Create projects from both csv and Excel files.
    It’s possible to create a new project directly from an Excel file (and CSV works as usual).


  • Theme Wheels. Visualize your pinned topics in a graphical display of the main topics and their associations. Theme wheels in Explorer is a way of visualizing the most important topics in the processed dataset. They represent pinned topics and their relative strength in the data set. They also show each topic's associations and their ratios to each topic.
  • Targeted sentiment analysis. The Explorer allows you to specify the target of your interest when performing sentiment analysis on texts in a project. When you do, it performs sentiment analysis only for those sentences that match the target; without a target it analyses the entire text. You define your target of interest as a custom concept using Explorer's Concept Modeler tool.
  • Various sorting of topics and groups. Sort groups and topics alphabetically, by number of mentions, and by their pinned status. Topics can be sorted either alphabetically or by the number of mentions, and you can also group all pinned topics together to avoid having to scroll the page up and down.
  • Concept modeling. Explorer provides powerful concept modeling for additional analytics capabilities. You can model any concept by finding and saving the necessary multiword expressions - Explorer makes this easy by providing automatically formed n-grams and suggestions for semantically similar words. Create custom concepts for use in the analysis of your data and your texts will be scored according to their presence, just like sentiment is analyzed. Just start with a few seed-words, and then build a complete concept by browsing through the list of suggestions and adding those that seem relevant to you. Your data is analyzed with respect to your concepts when downloaded as Excel report.
  • Keywords extraction. A part of the Excel report, extracted salient keywords add another analytics dimension to your data. There are four keyword columns for each text in the Excel report: salient keywords, salient keywords after qualification by Wikipedia, semantically expanded keywords, and semantically expanded keywords qualified by Wikipedia. The last of these represents related, relevant, and qualified keywords that are not part of the text.
  • Automatically created multiword expressions. Gavagai Explorer knows about multiword expressions like "San Francisco" so you don't have to create lists of them yourself. Explorer understands the language in which your texts were written and it automatically learns which words are actually part of bigger expressions. This prevents common expressions from being broken upp into their parts and it helps the user as you no longer have to painstakingly craft lists of important expressions.
  • Automatically created synonyms. Explorer automatically knows which words relate to one another. This makes it easy to get respondents' opinions tallied in one place - even if they all express things differently. Explorer understands the language of your texts. Therefore it can suggest synonyms: alternative ways of saying the same thing. By accepting the suggestions you get all respondents who mean the same thing, but express it differently, into the same bucket.
  • Merge, ignore and group topics. Structure your data the way you want it. Merge similar topics, ignore irrelevant topics or place related topics in groups. While structuring the project, Explorer automatically re-calculates the strengths of the topics and the groups, taking into account overlapping texts that belong to several topics. The result is an always up to date respondent count and relative strength to the total number of respondents.
  • Copy project model to new project. You can reuse a project model by applying it to new data. Pinned topics and groups, and ignored terms make up the model of a project and it can be applied to a new project. This is useful when analyzing a related set of data, like a set of hotel reviews for a different hotel, or the next month's batch of reviews for the same hotel.
  • Add more data to an existing project. The new data will fall into place - automatically, with zero effort. You can add data to an existing project to have the project's model applied automatically to the new data. This is useful when data is acquired in regular intervals. Then you can filter on the partitions and compare datasets over time. If you discover a new topic in the new data you can easily go back and see if that topic was present in the old data as well.
  • Pinned topics and groups. Pin your important findings and make sure they are never lost when filtering or adding new data. By pinning a topic or a group, you mark it as permanent and change its visual appearance. Pinned topics will always appear in your topics list even if they are not represented by any respondents. This is useful when filtering (and the result after applying the filter is smaller than before) or when copying a project model from one project to another.
  • Associations. When people talk about price what do they say? Explorer automatically calculates associated topics. Quickly find out what aspects are most important for any topic. Associations are calculated automatically and for every topic. They allow you to gain deep and quantified insight into aspects of your topics.
  • Sentiment analysis. For every topic and group we measure positivity, negativity and skepticism, but we can measure any attitude or concept. You can even model your own concepts - how about profanity in Portuguese? Or buying propensity in Spanish? Any attitude or concept can be measured ranging from "propensity to buy", "love", "fear" or "profanity". We can model and measure any concept with accuracy and coverage..
  • Find hidden topics. Do you know beforehand what to expect to find in your data? Do you want to test a hypothesis? Create a topic manually and see if there are any respondents to match. Manually create topics to help you structure your model or find weaker opinions in your data. If you also pin the manually created topic you can ensure that you will track it even if the topic is strong in one set of data and weak in another.
  • Quantify your qualitative data. Take free text data from open ended questions and turn it into quantified topics sorted in order of importance. Gavagai Explorer clusters your unstructured data into structured topics and quantifies them by measuring how many texts (respondents) "contain" each topic. You can quickly and easily find out what the strongest to the weakest topics are and track them over time as new data is acquired.
  • Analyze data in any language. All features work with data in any language. Synonyms, multiword expressions and all other features are supported for any language. We currently have more than 40 languages on-line in our "living lexicon" and more languages can be added in a matter of weeks.
  • Export to Excel, Pdf or csv. You can export to Excel, PDF or csv straight from any project. The Excel file contains every aspect of your project - quantified topics and groups with respondent counts and percentages, the terms and their synonyms, associations and their strengths, sentiment measurements, and example snippets of actual texts. The Pdf report is a sequential list of all topics, associations and snippets, formatted similarly to the appearance in the Explorer.

Three easy steps to get you started

Try an example

Try Gavagai Explorer yourself, by analyzing some example hotel reviews.

Sign Up

Sign up for a month long free trial, and try out all the features of Gavagai Explorer using your own data (up to 2000 texts included for free). No credit card information required.

Explore your own data

Upload your survey data, product reviews or other data concerning the same subject matter, and start exploring its contents. Gavagai Explorer allows you to peek inside the minds of all your respondents in a fraction of the time it takes to structure and code the data the traditional way.