Diaform

• AI-led customer interviews that adapt questions based on respondents’ answers.
• Voice and text conversations accessible through a browser-based shareable link.
• Intelligent follow-up questions to investigate motivations, problems, and customer experiences.
• Custom research projects with configurable questions, conversation goals, and AI agent settings.
• Knowledge-base uploads that provide product documents, policies, and other context to the AI agent.
• Automated response summaries, sentiment analysis, confidence indicators, and notable quotes.
• Analytics for reviewing response patterns, conversation completion, sentiment, and research findings.
• CSV exports and webhooks for transferring research data to compatible tools and workflows.
• Mid-conversation automations that can trigger actions based on detected topics or sentiment.
• Multilingual conversations supporting more than 30 languages, with English summaries for research teams.

What Is Diaform?

Diaform is an AI-powered customer feedback and research platform designed to make qualitative research easier to conduct at scale. It replaces static questionnaires with interactive conversations in which an AI agent listens to each response, asks relevant follow-up questions, and helps uncover the reasoning behind customer opinions.

Businesses can use Diaform to understand customer needs, investigate product problems, collect testimonials, explore cancellation reasons, test concepts, and research pricing decisions. Participants can respond through voice or text using a browser-based link, while teams review the resulting transcripts, summaries, and analytics in a centralized workspace.

AI-Powered Customer Conversations

Diaform’s central feature is its ability to conduct customer conversations using an AI feedback agent. Instead of presenting every participant with an identical fixed sequence of questions, the agent responds to individual answers and adjusts its next question according to the conversation.

For example, if a customer says that a product’s onboarding process was confusing, the AI can ask which step caused difficulty, what the customer expected to happen, and what they tried next. This approach helps researchers collect more contextual feedback than a simple rating or one-line comment might provide.

Adaptive Follow-Up Questions

Diaform is designed to probe beyond an initial response. Its AI agent can clarify vague statements, explore specific experiences, and investigate the reasons behind a customer’s decision or opinion.

Researchers can configure the depth of follow-up questioning to suit the study. This is useful when a team wants detailed qualitative answers without manually conducting every interview. The quality and relevance of follow-ups still depend on the study instructions, participant responses, and AI behavior.

Voice and Text Feedback

Diaform supports both voice and text-based conversations. Participants can access a study through a browser link and respond in the format that suits them. Voice interaction can encourage people to explain experiences in their own words, while text can be convenient for respondents who prefer typing.

The platform describes its voice experience as using natural-sounding speech, with pauses and conversational delivery. Respondents can participate without creating a separate Diaform account, reducing friction when collecting feedback from customers or prospects.

Research Projects and Study Configuration

Diaform organizes research through projects. A researcher can define the objective, prepare questions, add context about the product or service, and configure the AI agent before sharing the conversation link.

The project setup supports structured research while allowing the agent to respond naturally during the conversation. This can be useful for customer discovery, onboarding feedback, product concept evaluation, and other studies where the researcher needs consistent coverage of key questions without forcing every participant through identical follow-ups.

Product and Customer Discovery

Founders and product teams can use Diaform to investigate customer needs, validate assumptions, and understand how people experience a product. Instead of relying solely on multiple-choice answers, teams can ask open-ended questions and allow the AI to explore a respondent’s explanation.

Research can focus on current workflows, unmet needs, perceived product value, missing functionality, or obstacles that prevent adoption. The resulting transcripts and summaries provide material for product planning and further investigation.

User Research and UX Feedback

Diaform can support user research by collecting detailed accounts of how people interact with a product or service. Researchers can investigate onboarding friction, confusing features, unmet expectations, and the reasons behind user behavior.

Because participants can answer at their convenience through a shareable link, teams can collect feedback without scheduling every interview individually. Researchers should still interpret the results in context and consider whether the respondents represent the intended audience.

Customer Satisfaction and Post-Purchase Feedback

Businesses can use Diaform to collect feedback after a purchase or a key customer interaction. The AI can ask customers about their experience, explore what worked well, and request specific examples that may help a team understand their satisfaction.

This approach can also help businesses collect more detailed testimonials. Instead of asking customers only whether they liked a product, a conversation can explore what they valued, which problem the product addressed, and what stood out about their experience.

Churn Research and Cancellation Surveys

Diaform can be used to investigate why customers cancel a subscription or stop using a service. A static cancellation form might capture a broad reason, while an adaptive conversation can explore what led to that decision and what could have improved the experience.

Customer success teams can use these findings to identify recurring problems, evaluate retention opportunities, and prioritize improvements. The AI can also support research into whether a customer would consider returning under different circumstances.

Pricing Research and Willingness to Pay

Diaform provides workflows for researching pricing preferences and willingness to pay. Teams can explore how customers respond to proposed prices, package structures, and feature combinations, while follow-up questions investigate the reasoning behind each reaction.

Supported research approaches include Van Westendorp price sensitivity questions, Gabor-Granger price testing, and direct willingness-to-pay questions. These methods can help teams understand price perceptions and the alternatives customers consider.

Researchers can also compare reactions to different price anchors or package options. The results are qualitative and research-based evidence, not a guarantee of actual purchasing behavior. They should be considered alongside market conditions, conversion data, and other relevant evidence.

Concept and Message Testing

Diaform can help teams evaluate product concepts, marketing messages, and proposed features before committing to a launch. Participants can react to an idea, explain their initial impressions, and answer follow-up questions about perceived value or concerns.

These conversations can help researchers distinguish between general approval and genuine interest. They may also reveal objections, missing information, or alternative expectations that require further testing before a product or campaign moves forward.

Knowledge Base and Context-Aware Responses

Diaform allows users to add contextual knowledge to a research project. This can include product documentation, pricing information, policies, roadmaps, and other relevant reference material.

The AI can use the supplied context to make its questions more informed and respond to participant questions during a conversation. This is particularly useful when respondents need clarification about a product before they can give meaningful feedback.

Users should keep project knowledge accurate and up to date. AI-generated responses can still contain errors, so important product claims should be checked against the underlying documentation.

Automated Summaries and Structured Insights

After a conversation is completed, Diaform can generate structured outputs that help research teams review results more efficiently. These include per-question summaries, sentiment information, confidence indicators, notable quotes where available, and the original conversation history.

Summaries make it easier to review a collection of interviews without reading every transcript from beginning to end. The original responses remain important, however, because a short summary may omit qualifications or context that influence how a finding should be interpreted.

Sentiment and Conversation Analytics

Diaform provides analytics for examining feedback across conversations. Teams can review sentiment, response activity, completion patterns, and geographic information where available.

These features can help researchers identify recurring themes, compare participant responses, and investigate areas that may require attention. Sentiment labels and confidence indicators should be treated as analytical aids rather than definitive judgments about what a respondent intended.

Mid-Conversation Automations

Diaform supports configurable automations that can react to topics or sentiment detected during an ongoing conversation. Depending on the configured trigger and available integrations, a workflow can alert a team, capture follow-up information, offer a link, or help a respondent proceed to another step.

For example, a business may want to be notified when a participant expresses strong purchase interest or raises an urgent concern. Automations can help teams respond while the feedback is still being collected, rather than waiting until the entire study has finished.

Integrations and Data Export

Diaform supports CSV exports and webhooks for moving research information into other workflows. CSV files can be opened in spreadsheet software for further analysis, reporting, or organization of qualitative responses.

Webhooks allow configured events or data to be passed to compatible services. The platform’s documentation also describes integrations and automation setup, including Slack-related workflows. Specific capabilities and limits depend on the plan and integration configuration.

Shareable Links and Embedding

Diaform conversations can be distributed through a shareable link, allowing teams to invite customers, prospects, or research participants without arranging a live interview for every response.

Links can be shared through suitable communication channels, and the platform supports embedding conversations in websites. Custom subdomains are available across its listed plans, while custom-domain support is reserved for the Business plan according to the published comparison.

Multilingual Research

Diaform advertises support for more than 30 languages. This allows teams to conduct research with participants who prefer communicating in languages other than English, while research summaries can be returned in English for the team.

Multilingual conversations can help organizations collect feedback across different markets. Teams should verify language suitability for sensitive or specialized research and review translated summaries where accurate interpretation is especially important.

Team Collaboration and Workspace Management

Diaform offers plans with different numbers of workspace seats and live projects. This lets individuals and research teams organize studies, manage research activity, and collaborate within a shared workspace according to their subscription limits.

Higher-tier plans provide additional project capacity, more AI messages, and more seats. The Business plan also includes custom-domain support and organization API keys, while Pro and Business plans include additional branding and voice options.

Who Can Benefit From Diaform?

Diaform is designed for teams that need detailed feedback from customers, users, employees, or prospects. Potential users include product managers, UX researchers, startup founders, marketing teams, customer success professionals, SaaS companies, and people or HR teams.

It can be useful when an organization needs to run ongoing qualitative research without arranging every conversation manually. Teams that need simple contact forms or fixed surveys may not need the full adaptive-interview workflow, while teams seeking deeper explanations can use its follow-up and analysis capabilities.

Pricing and Plans

Diaform offers a 14-day free trial without requiring a credit card. The trial includes 250 AI messages, one project, and one workspace seat.

The Starter plan costs $49 per month when billed monthly and includes 1,000 AI messages per month, two projects, and one seat. Standard costs $89 per month and includes 3,000 messages, four projects, and two seats.

The Pro plan costs $199 per month and includes 7,000 messages, 20 projects, and five seats. Business costs $499 per month and includes 20,000 messages, 50 projects, and 15 seats. Annual billing offers discounted rates, and custom enterprise arrangements may be available by contacting the company.

Plan limits also differ in areas such as the number of base questions per conversation, knowledge capacity, webhooks, branding controls, and custom-domain support. Users should check the current pricing page before selecting a plan.

Privacy and Responsible Research

Diaform processes participant responses and project context to conduct AI interviews, generate follow-up questions, and summarize findings. Its terms explain that AI outputs can be probabilistic and should be reviewed before being relied upon.

Researchers should inform participants about the purpose of a study and handle personal information according to applicable privacy requirements. Before collecting sensitive feedback, teams should review the current privacy policy, terms, data-retention settings, and relevant contractual commitments.

How to Get Started With Diaform

To begin, create an account and start a research project. Define the goal of the study, prepare the questions, add relevant product or service context, and configure the AI agent for the intended audience.

Preview the conversation before sharing it with participants. Distribute the link through an appropriate channel, monitor incoming responses, and use the analytics and summaries to identify patterns. Export the data or configure supported integrations when the findings need to be included in other workflows.

Frequently Asked Questions About Diaform

What is Diaform used for?

Diaform is used to conduct AI-led customer feedback and research conversations. Common applications include customer discovery, product research, churn analysis, onboarding feedback, pricing studies, concept testing, and testimonials.

Is Diaform free?

Diaform offers a 14-day free trial with no credit card required. The trial includes 250 AI messages, one project, and one workspace seat. Paid subscriptions are available after the trial.

How much does Diaform cost?

The monthly plans are Starter at $49, Standard at $89, Pro at $199, and Business at $499. Annual billing offers discounted rates. Check the official pricing page for current prices and plan limits.

Can Diaform conduct interviews using voice?

Yes. Diaform supports voice and text conversations through a browser-based link, allowing participants to choose how they respond.

Does Diaform ask follow-up questions automatically?

Yes. Its AI agent adapts follow-up questions to participants’ answers, helping explore vague responses and investigate the reasons behind customer opinions.

Can I upload product documentation?

Yes. Diaform supports project knowledge that can include product documents, pricing details, roadmaps, and other context to inform the AI’s questions and responses.

What insights does Diaform provide?

Its analysis features include summaries, sentiment information, confidence indicators, notable quotes where available, and original conversation histories. Analytics help teams examine response patterns and completion activity.

Can Diaform integrate with other tools?

Diaform supports CSV exports and webhooks, with documentation for integrations such as Slack-related workflows. Available integrations and limits depend on configuration and subscription level.

Does Diaform support multiple languages?

Diaform advertises support for more than 30 languages, with English summaries available for research teams.

Can I embed a Diaform conversation on my website?

Yes. Diaform supports embedding conversations and sharing them through links. Custom subdomains are available across plans, while custom-domain support is included in the Business plan.

Who should use Diaform?

Diaform may suit product teams, researchers, founders, marketers, customer success teams, SaaS companies, and HR professionals who need detailed qualitative feedback without manually conducting every interview.

Should AI-generated research summaries be trusted without review?

No. Summaries and sentiment labels are useful aids, but researchers should check original transcripts and supporting evidence before making important product, business, or organizational decisions.

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