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Frequently Asked Questions

How does the number of pages and queries affect usage?

The number of pages you can analyze and the number of queries you can make are interconnected. While you can analyze more than 200 pages, this will reduce the available number of queries.

On average, we estimate each page to be around 2,400 characters. If your dataset totals approximately 800,000 characters, you can still analyze it with QInsights, but you may reach your usage limit more quickly.

The amount of data processed per query depends on both the query and the data. If your query matches a large amount of relevant information, more data will be processed, impacting usage limits. Conversely, if less relevant information is found, it will have a smaller effect on your usage. Therefore, the 200 pages and 70-120 queries limit is an average based on typical usage.


What happens if I have used my usage limit?

If you reach your usage limit, you can easily top up your account as needed.


Can we use QInsights as a team?

While we don’t yet offer a dedicated team version, multiple users can share access under a single subscription. For teams, we recommend contacting us to discuss pricing, as usage limits are currently based on individual subscriptions and need to be adjusted for team access.


What is your cancellation policy?

Our cancellation policy allows you to cancel your subscription at any time. If you cancel before the end of your billing cycle, you'll retain access to QInsights until your current subscription period concludes, after which your subscription will not renew. For further assistance or specific questions about your subscription, please contact our support team: support@qinsights.ai


Are my data secure?

Your data is managed in compliance with European privacy laws, among the strictest globally. For more information on how we handle and store your data, please visit our Privacy Page.


Why should I use QInsights over chatGPT?

Purpose-built for Qualitative Research: ChatGPT is a general-purpose tool, while QInsights is specifically designed by qualitative researchers for qualitative research. It’s tailored to meet the unique needs of qualitative analysis.


Advanced File Management: ChatGPT lacks file management capabilities. With QInsights, you can organize your data into projects, storing all analyses in a dedicated project archive for easy access and review.


Detailed Filtering and Speaker Roles: QInsights enables you to create document and speaker variables, which serve as filters for comparing data within or across documents. ChatGPT lacks an understanding of speaker roles and segments, making it unreliable for role-based distinctions.


Diverse Analysis Options: QInsights offers multiple analysis types, including theme, grid, and sentiment analysis, in addition to chat. ChatGPT is limited to a chat interface and lacks built-in analysis features.


Optimized for Semi-structured Data: QInsights is designed for analyzing semi-structured data from Excel files, like survey responses and social media comments. Variables and values are extracted for detailed analysis, with sentiment analysis available for Excel data.


Context Management: QInsights employs a specialized qualitative data model and search engine to ensure relevant context is sent to the language model. ChatGPT, by contrast, fills its context with as much information as possible (current maximum is around 100,000 words or transcripts of 10 1-hour interviews) without assessing relevance. It is good at answering questions about single documents but prone to hallucinate when working across many.


Model Flexibility: QInsights uses the best available models—whether from Gemini, Claude, Mistral, or OpenAI—avoiding vendor lock-in. ChatGPT exclusively relies on OpenAI models.


Dedicated Support: QInsights offers responsive support, including guidance on analysis approaches. ChatGPT offers no direct support for analysis or usage questions.


Unlock Hidden Insights with AI-Powered Qualitative Analysis with QInsights

Unlock Hidden Insights with AI-Powered Qualitative Analysis

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