The only solution experts trust to deliver accurate and evidence-based insights in minutes.
I was blown away by the instant insights into what mattered from thousands of survey comments. We could easily see what themes impacted our NPS score and why. There’s no reason PMs should be spending so many weeks manually analyzing feedback.
Robbie Allan
Director of Product at Intercom
Thematic saves us time, which is critical when working against product timelines. This is due equally to the tool’s usability and the world-class support that Thematic offers to its users.
Artem Chekovechkov
Senior program manager, LinkedIn
Thematic transforms feedback from any data source into a readable summary with trusted themes, sentiment ratings and categories, instantly. It doesn’t matter how technical your product is. You’ll be up and running within hours!
Thematic AI is designed to be maximized by user knowledge, with an interactive theme editor. It’s easy for insights professionals to refine themes and validate the results.
Thematic delivers a deep, contextual understanding of your customer feedback with root cause analysis that makes everyone feel like a smart data scientist.
In her decade of research into natural language processing, co-founder Dr. Alyona Medelyan discovered that thematic analysis was the most effective approach to getting a practical understanding of unstructured customer feedback. Her widely cited research and discoveries in NLP and deep learning became the foundation for the AI-engine that powers Thematic. We’ve gone from strength to strength ever since.
Read our customer reviews
Other solutions lock you into a box and take months to set up, with no way to discover emergent themes. It’s hard work for you to get the insights they’ve promised in their marketing. There are none of those limits with Thematic. You get the deep, contextual insights, with the granularity you need, when you need them.
Key strength
How it arrives at themes
Speed
Consistency
Transparency
Ease of getting answers
(combines proprietary AI with LLMs)
Key strength
Discovers & quantifies what matters in minutes with readable summaries
How it arrives at themes
Discovers themes in data and adapts to new feedback
Speed
It takes 30 min to several hours to review themes
Consistency
Analyzes all feedback consistently
Transparency
White box, can trace themes to context
Ease of getting answers
Alerts you to new themes and delivers instant, readable and verifiable anwers
(like Medallia, Qualtrics Text IQ and XM Discover)
Key strength
Works well for industries with little changes in feedback, e.g. hotels
How it arrives at themes
Users create rules or professional services adjust pre-existing taxonomies
Speed
It takes weeks to months to create new rules or to re-configure a pre-canned taxonomy
Consistency
Analyzes all feedback consistently
Transparency
White box, can trace topic to rules
Ease of getting answers
Good at quantifying known and well-defined rules, struggles with complex language and unknowns
(and wrappers, like Viable, Interpret, Kraftful)
Key strength
Creates readable summaries of feedback, understands nuance
How it arrives at themes
Discovers theme in batches of data
Speed
Instant sample analysis
Consistency
Consistency is difficult to achieve because model guesses each time
Transparency
Black box, requires prompt engineering to trace
Ease of getting answers
Delivers instant readable answers that are difficult to verify
(like Chattermill, Medallia Athena)
Key strength
Scalable and accurate when using a limited set of categories it’s trained on
How it arrives at themes
Users or professional services curate examples (training data) for each category
Speed
It takes weeks to months to curate data
Consistency
Analyzes all feedback consistently
Transparency
Black box, difficult to adjust a model that’s inaccurate
Ease of getting answers
Good at quantifying known and well-defined rules, but will miss any emerging themes.
(like Medallia, Qualtrics Text IQ and XM Discover)
Key strength
Works well for industries with little changes in feedback, e.g. hotels
How it arrives at themes
Users create rules or professional services adjust pre-existing taxonomies
Speed
It takes weeks to months to create new rules or to re-configure a pre-canned taxonomy
Consistency
Analyzes all feedback consistently
Transparency
White box, can trace topic to rules
Ease of getting answers
Good at quantifying known and well-defined rules, struggles with complex language and unknowns
(and wrappers, like Viable, Interpret, Kraftful)
Key strength
Creates readable summaries of feedback, understands nuance
How it arrives at themes
Discovers theme in batches of data
Speed
Instant sample analysis
Consistency
Consistency is difficult to achieve because model guesses each time
Transparency
Black box, requires prompt engineering to trace
Ease of getting answers
Delivers instant readable answers that are difficult to verify
(like Chattermill, Medallia Athena)
Key strength
Scalable and accurate when using a limited set of categories it’s trained on
How it arrives at themes
Users or professional services curate examples (training data) for each category
Speed
It takes weeks to months to curate data
Consistency
Analyzes all feedback consistently
Transparency
Black box, difficult to adjust a model that’s inaccurate
Ease of getting answers
Good at quantifying known and well-defined rules, but will miss any emerging themes.
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