--- title: "Rippit vs. Qualtrics for Conversation Analysis and Agents (2026): Differences, Pricing, and When to Use Both" description: "Rippit vs. Qualtrics: surveys measure how customers feel, Rippit's AI reads every conversation to explain why. Differences, pricing and when to use both." canonical: https://www.rippit.com/comparisons/rippit-vs-qualtrics type: Comparison datePublished: 2026-09-28 dateModified: 2026-11-13 --- # Rippit vs. Qualtrics for Conversation Analysis and Agents (2026): Differences, Pricing, and When to Use Both **Short answer:** Qualtrics measures how customers *say* they feel, through surveys. Rippit explains *why*. Rippit is a Growth Data Platform: it reads every support ticket, call and chat in the sources you connect, turns what it finds into structured data[[2]](#src-2) and keeps it current next to your survey scores, product usage and account data, so product, CX and marketing can see which customers sit behind each score.[[1]](#src-1) Many teams use both: they keep Qualtrics for surveys and add Rippit to find what's driving the scores, including the customers who never respond.[[3]](#src-3) Rippit is self-serve and free to start, with $10 in credits.[[4]](#src-4) Qualtrics pricing is by quote.[[5]](#src-5) The two overlap in conversation analytics, which Qualtrics added with its 2021 Clarabridge acquisition; Clarabridge technology now powers XM Discover.[[9]](#src-9) By Lauren Alexander · Updated November 13, 2026 ## Rippit vs. Qualtrics at a glance | CRITERIA | Qualtrics | Rippit | | --- | --- | --- | | What is it? | Experience management platform | Growth Data Platform for the conversations and business data behind your scores, with agents your teams set up[[1]](#src-1) | | Starting point | Formal feedback collection and experience measurement, with broader analytics capabilities | The conversations you already have: tickets, calls and chats,[[6]](#src-6) plus the survey data tied to them[[7]](#src-7), next to product usage, account and revenue data | | Best fit | Survey-led CX programs and organizations looking for a broader experience management suite | Product, CX and marketing teams who need to know *what's driving a score*, which accounts it touches and where demand is growing | | Surveys | A central product capability | Imports Qualtrics CSAT and CES responses and links each one to the matching ticket.[[7]](#src-7) Predicts CSAT for conversations that never got a survey[[8]](#src-8) | | Conversation analysis | Available through XM Discover, built on Clarabridge technology, and contact center offerings[[9]](#src-9) | The foundation. AI analyzes every conversation you connect, with nothing sampled[[1]](#src-1) | | How teams use the data | Measure and manage customer experiences within an XM program | Describe the insight you want, and Rippit adds it as a field across every conversation in scope (root cause, churn risk, resolution).[[10]](#src-10) Reuse it in dashboards, QA and the agents each team sets up | | Customization | XM Discover category models use rules that match the words in each rule[[11]](#src-11) | AI tags every conversation in scope with the fields you define, such as intent, root cause, churn signal and resolution[[10]](#src-10) | | What gets scanned, analyzed and acted on | Analyzes feedback and interactions from the sources connected to XM Discover[[12]](#src-12) | 100% of conversations in scope, with nothing sampled[[4]](#src-4)[[1]](#src-1) | | How it handles large datasets | XM Discover Connectors pull data from multiple sources for analysis across all of them, and its NLU engine adds metadata to each document during processing[[12]](#src-12) | Stores every conversation you connect as structured, queryable data[[2]](#src-2) that agents and people can enrich and aggregate across the full dataset | | Traceability | Document explorer lets you browse the actual customer feedback behind a dashboard widget[[13]](#src-13) | Every result is a field on a specific conversation,[[2]](#src-2) and each analysis step is documented, so any answer can be audited | | Repeatability | Studio alerts notify you and other users when certain events happen in your data[[14]](#src-14) | Agents you set up run hourly, daily, weekly or monthly on new data and send findings, with the evidence, to Slack or email[[25]](#src-25) | | Setup | Omnichannel Listening setup is conducted by the Qualtrics Implementations team[[15]](#src-15) | Self-serve. Connect Zendesk, Intercom, Granola, Gong and more with pre-built integrations,[[6]](#src-6) without needing an engineer to start | | Survey + conversation data together | Survey data lives in Qualtrics. Joining it with ticket data depends on licensed products and integrations | Imports Qualtrics survey data alongside conversations.[[7]](#src-7) Keep Qualtrics for surveys and use Rippit to explain the scores | | Works with Claude | An official Public API MCP server, set up by a Brand Admin, so Claude can connect to the Qualtrics platform API[[16]](#src-16) | An MCP server, so Claude, ChatGPT or Cursor can query your Rippit data and open the conversations behind an answer[[17]](#src-17) | | Public pricing | Pricing by quote[[5]](#src-5) | $10 in free credits to start, no card needed; then pay as you go: $1/GB a month for storage with compute included, AI models at list price, people and agents free; Enterprise by quote[[4]](#src-4) | | Best starting question | "How are customers experiencing our company across key touchpoints?" | "Which detractor themes in this quarter's survey also show up in conversations from accounts whose usage is falling?" | Pricing checked September 28, 2026. **01 · THE DIFFERENCE** ## What's the difference between Rippit and Qualtrics? The three biggest differences are pricing model, time to value, and focus. **Pricing model.** Rippit publishes its pricing: free to start with $10 in credits, then pay as you go for storage and AI at list price.[[4]](#src-4) Qualtrics doesn’t publish prices; buyers request a demo or quote.[[5]](#src-5) **Time to value.** Rippit is self-serve: sign up on the website, connect Zendesk, Intercom, Granola, Gong and more with pre-built integrations, without needing an engineer to start.[[4]](#src-4)[[6]](#src-6)[[1]](#src-1) Qualtrics states that “the setup of an Omnichannel Listening program is conducted by the Qualtrics Implementations team.”[[15]](#src-15) **Focus.** Qualtrics is built around surveys and experience management. It added conversation analytics when it acquired Clarabridge in 2021, whose technology now powers XM Discover.[[9]](#src-9) It works well for running a formal CX measurement program across touchpoints. Rippit is a Growth Data Platform. It reads every support, sales and success conversation you connect[[6]](#src-6) and records what it finds as fields any team can query.[[10]](#src-10) It keeps those fields next to product usage, account and revenue data, so a theme can be ranked by the customers and revenue behind it.[[1]](#src-1) Product, CX and marketing teams then set up agents that flag a growing theme. | | QUALTRICS | RIPPIT | | --- | --- | --- | | Time-to-value | Setup conducted by the Qualtrics Implementations team[[15]](#src-15) | Self-serve, with pre-built integrations[[1]](#src-1) | | Price | Pricing by quote[[5]](#src-5) | Free to start; then pay as you go[[4]](#src-4) | | AI-native experience | Category models built on word-matching rules[[11]](#src-11) | AI tags every conversation with the fields you define[[10]](#src-10) | **02 · SCALE** ## How does Rippit analyze every conversation? 1,000 conversations or 1,000,000, not just the customers who answer a survey: Rippit reads every one you connect.[[1]](#src-1) Rippit runs an AI engine built to label conversations in bulk: AI enriches every conversation you connect[[1]](#src-1) and stores the results as structured, queryable data,[[2]](#src-2) so analysis and agents can work across all of it. Reading every conversation doesn't have to be expensive. In Rippit's own coverage benchmark, it read all 1,000 transcripts in full for about six cents, the same full read that cost about $61 per question with a map-reduce approach.[[24]](#src-24) Questions then run on those stored fields across the full dataset, instead of rereading transcripts each time, so asking the same question again returns the same answer.[[24]](#src-24) For open-ended questions no existing field answers, Rippit also runs ad hoc worksheet analysis[[2]](#src-2) on up to 10,000 conversations at a time, and what they find can feed new analysis and agents. **Every conversation you connect, not just survey responses.** **Counts are complete** "What share of refund conversations ended in a cancellation?" is computed across every refund conversation in scope, not just the customers who answered a survey.[[4]](#src-4) **New questions reach the past** Describe a new field in plain English, and Rippit applies it to past conversations in a single run.[[10]](#src-10) **Every number is checkable** Each result is a field on a specific conversation, so you can open the conversations behind any count.[[2]](#src-2) This matters because a result is only as reliable as the data behind it. Manual QA typically reaches 1–5% of interactions, and survey response rates often fall to low single digits.[[17]](#src-17) Before Rippit, Klaviyo reviewed fewer than 2% of its 600,000+ annual support incidents. With Rippit, it opened up 2.5 million conversations that had never been analyzed.[[18]](#src-18) **KLAVIYO** - BEFORE RIPPIT **<2%** of 600,000+ annual support incidents reviewed - WITH RIPPIT **2.5M** conversations opened up that had never been analyzed **03 · USE BOTH** ## Can you use Rippit and Qualtrics together? Yes. Rippit's Qualtrics integration imports CSAT and CES survey responses and links each one to the matching ticket and agent.[[7]](#src-7) You keep Qualtrics for surveys and use Rippit to explain the scores. Using both is common. In Rippit's review of 2,345 of its own sales conversations from 2025–2026, about 1 in 12 prospects brought up Qualtrics, and 60% of those were current Qualtrics users looking to add conversation analysis rather than replace their survey program.[[3]](#src-3) Using both fixes two common gaps: - **Survey and ticket data live in different tools.** Rippit puts the score and the conversation in one view.[[7]](#src-7) - **Most customers never respond to a survey.** At Checkr, surveys covered fewer than 10% of interactions. Rippit's predictive CSAT now covers all of them.[[8]](#src-8) Here's how that works on one question a product or CX insights lead might ask: *which detractor themes in this quarter's survey also show up in support and sales conversations from accounts whose usage is falling?* First, Qualtrics runs the survey, and its responses come into Rippit alongside the conversations.[[7]](#src-7) Next, Rippit matches themes to accounts. It has already stored a judgment on every conversation in scope as a field,[[10]](#src-10) so it can match each detractor's themes to that account's tickets, calls and chats, with usage from your connected product data. If a theme isn't a field yet, a deep dive reads the conversations behind it and answers now.[[2]](#src-2) To reuse the answer, add the theme as a field, and Rippit applies it to past conversations in one run.[[10]](#src-10) Then set up an agent that checks new conversations each week and sends product and CX the accounts where a detractor theme and falling usage show up together, with the quotes behind them.[[25]](#src-25) **FROM QUALTRICS** **CSAT and CES survey responses** CSAT CES **IN RIPPIT** **Links each response to the matching ticket and agent** **ONE VIEW** **The score and the conversation together** Score · + · Ticket · + · Agent · + · Conversation **04 · ANALYSIS** ## How is Rippit's analysis different from Qualtrics text analytics? XM Discover sorts feedback with category models, which are hierarchies of categories, each defined by rules that "find sentences where the words outlined in the rule occur."[[11]](#src-11) Teams build and edit these models in XM Discover's Designer tool.[[11]](#src-11) Rippit uses AI classification instead of word-matching rules. One pass tags each conversation with the fields you define, such as intent, root cause, sentiment, urgency, churn signal and resolution. When your business changes, a new category applies to past conversations in a single run.[[10]](#src-10) That matters because keyword rules often misfire. A rule looking for "cancel" flags "How do I cancel a duplicate order?" as churn, while AI reads the actual intent.[[10]](#src-10) This speed pays off with unplanned questions. When Checkr's CEO asked a late-night question about background check issues in a specific state, the team delivered a detailed report by the next morning.[[8]](#src-8) **CUSTOMER MESSAGE** **"How do I cancel a duplicate order?"** **A RULE LOOKING FOR "CANCEL"** Flagged as churn **RIPPIT AI CLASSIFICATION** Reads the actual intent **05 · AI ASSISTANTS** ## Does Rippit work with Claude? Yes. Rippit supports MCP, so AI assistants like Claude, ChatGPT or Cursor can query your Rippit data and open the conversations behind an answer.[[17]](#src-17) You ask in Claude, and Rippit answers from every conversation you've connected.[[19]](#src-19) This matters at scale. A general-purpose assistant works within its context window[[20]](#src-20) and uses retrieval, code or summaries to get through large sets of conversations. Rippit has already read every conversation you connect and saved the results as fields, so Claude queries finished analysis and every number traces back to specific conversations. Qualtrics offers an official Public API MCP server, set up by a Brand Admin, so Claude can connect to it directly.[[16]](#src-16) Qualtrics' MCP exposes the Qualtrics platform API, while Rippit's exposes the analysis of every conversation you connect. **06 · PRICING** ## How much do Rippit and Qualtrics cost? Rippit publishes its pricing. AI models and data tools are billed at each provider's list price, with no markup.[[4]](#src-4) - **Free to start:** $10 in credits, no card needed, plus $90 more when you add a card[[4]](#src-4) - **Storage:** $1 per GB a month, with the compute to sync, run jobs and query included[[4]](#src-4) - **AI models and data tools:** each provider's list price, no markup[[4]](#src-4) - **People and agents:** free[[4]](#src-4) - **Enterprise:** a personalized quote, with SSO, SCIM, audit logs, data region choice and custom terms[[4]](#src-4) Qualtrics doesn't publish prices. Buyers request a demo or quote.[[5]](#src-5) To compare fairly, give both vendors the same data sources, volume and history requirements, and ask for the total cost, including implementation and services. **07 · SETUP** ## Which is faster to set up? Rippit is self-serve. You connect Zendesk, Intercom, Granola, Gong and more with pre-built integrations[[6]](#src-6) and can start without needing an engineer.[[1]](#src-1) Qualtrics setup of Omnichannel Listening goes through its Implementations team,[[15]](#src-15) and its text analytics comes with support from an implementation consultant or technical success manager.[[15]](#src-15) With either vendor, large historical imports and security reviews add time. **08 · CUSTOMERS** ## What do teams use Rippit for? - **Checkr** broke dissatisfaction down into specific "atomic problems." One billing cluster showed 47% predicted CSAT and a 58% unresolved rate, which the team took to its Chief Product Officer. Checkr says its time from insight to action went "from weeks to hours."[[8]](#src-8) - **Brex** replaced manual QA sampling with AI review of 100% of conversations and found churn risk in 3% of them. It feeds predicted CSAT and churn signals into customer success workflows.[[21]](#src-21) - **Klaviyo** analyzed a full month of product-launch conversations in two hours and reports a productivity gain of about 40% in under 12 months.[[18]](#src-18) ## When should you choose Qualtrics, Rippit, or both? **CHOOSE** ### Qualtrics You need to design and distribute surveys, or you want one XM suite spanning CX, employee experience and research. **CHOOSE** ### Rippit Your best customer signal is in support, sales and chatbot conversations, and you want it tied to the accounts and revenue behind it, so you can rank what's driving a score by who it affects and spot demand early. You also want product, CX and marketing to ask new questions and set up agents without writing keyword rules. **CHOOSE** ### Both You already run Qualtrics surveys and want to know why the scores move, and what customers who never respond are experiencing. ## Frequently asked questions ### Is Rippit a Qualtrics alternative? Not for surveys: keep Qualtrics to design, distribute and benchmark them. For understanding what's behind the scores, Rippit reads every conversation you connect, and many teams use it alongside Qualtrics.[[3]](#src-3) ### Can Rippit import Qualtrics data? Yes. Rippit imports Qualtrics CSAT and CES responses and links them to the matching tickets and agents.[[7]](#src-7) ### Does Rippit analyze 100% of conversations? Yes, every conversation in the scope you choose, with nothing sampled.[[1]](#src-1) ### Is Rippit cheaper than Qualtrics? Rippit is free to start, with $10 in credits and no card needed, then pay as you go: $1 per GB a month for storage, and AI models at list price.[[4]](#src-4) Qualtrics pricing is by quote,[[5]](#src-5) so compare equivalent scope. ### Do I need to build a taxonomy or keyword rules to use Rippit? No. AI classifies conversations across multiple dimensions, and new categories apply to past conversations in one run.[[10]](#src-10) ### Does Rippit work with Claude? Yes. Rippit supports MCP, so Claude, ChatGPT or Cursor can query your Rippit data and open the conversations behind an answer.[[17]](#src-17) ### What happened to Delighted? Delighted is no longer available, and Qualtrics points its customers to the Qualtrics platform.[[22]](#src-22) Former Delighted users who want insight from conversations rather than surveys can connect a helpdesk to Rippit and start free with $10 in credits.[[4]](#src-4) ### Is Rippit only for support? No. Rippit's customers use it for product feedback, churn analysis,[[18]](#src-18) coaching[[21]](#src-21) and chatbot monitoring.[[18]](#src-18) Product and marketing teams also use it to find demand: the requests and unmet needs customers keep raising, counted by the accounts behind them. ### Can I trace a number back to the conversations behind it? Yes. In Rippit, every result is a field on a specific conversation,[[2]](#src-2) so you can audit any answer by opening the conversations and fields behind it. ### Is Rippit the same company as MaestroQA? Yes. MaestroQA is now Rippit: same founders, with a rebuilt AI-first platform. The company moved from maestroqa.com to rippit.com, and existing customer data, rubrics and integrations carried over.[[23]](#src-23) Some Rippit help center articles still appear under the MaestroQA name and domain. ## Sources Rippit was formerly MaestroQA. Some sources below are hosted on the MaestroQA help center (help.maestroqa.com).[[23]](#src-23) 1. Rippit, homepage: [https://www.rippit.com/](https://www.rippit.com/) 2. Rippit, How It Works: [https://www.rippit.com/how-it-works](https://www.rippit.com/how-it-works) 3. Rippit first-party research: AI analysis of 2,345 Rippit sales conversations (2025–2026) run through Rippit's conversation analytics platform. Qualtrics was discussed in 188 conversations (8%); 113 of those prospects (60%) were current Qualtrics users. 4. Rippit, Pricing: [https://www.rippit.com/pricing](https://www.rippit.com/pricing) 5. Qualtrics, Pricing: [https://www.qualtrics.com/pricing/](https://www.qualtrics.com/pricing/) 6. Rippit, Integrations: [https://www.rippit.com/integrations](https://www.rippit.com/integrations) 7. Rippit Help Center, Qualtrics Integration: [https://help.maestroqa.com/en/articles/5724156-qualtrics-integration](https://help.maestroqa.com/en/articles/5724156-qualtrics-integration) 8. Rippit, Checkr customer story: [https://www.rippit.com/customer-story/checkr](https://www.rippit.com/customer-story/checkr) 9. Qualtrics, "Qualtrics Completes Acquisition of Clarabridge" (Oct. 2021): [https://www.qualtrics.com/articles/news/qualtrics-completes-acquisition-of-clarabridge/](https://www.qualtrics.com/articles/news/qualtrics-completes-acquisition-of-clarabridge/) 10. Rippit, Conversation Taxonomy playbook: [https://www.rippit.com/playbooks/conversation-taxonomy](https://www.rippit.com/playbooks/conversation-taxonomy) 11. Qualtrics Support, Category Models Basic Overview (Designer): [https://www.qualtrics.com/support/xm-discover/designer/categorize/category-models/category-models-basic-overview-designer/](https://www.qualtrics.com/support/xm-discover/designer/categorize/category-models/category-models-basic-overview-designer/) 12. Qualtrics Support, XM Discover Terms from A to Z: [https://www.qualtrics.com/support/xm-discover/getting-started-discover/xm-discover-terms-from-a-to-z/](https://www.qualtrics.com/support/xm-discover/getting-started-discover/xm-discover-terms-from-a-to-z/) 13. Qualtrics Support, Document Explorer (Studio): [https://www.qualtrics.com/support/xm-discover/studio/studio-dashboards/document-explorer/document-explorer-studio/](https://www.qualtrics.com/support/xm-discover/studio/studio-dashboards/document-explorer/document-explorer-studio/) 14. Qualtrics Support, Alerts Basic Overview (Studio): [https://www.qualtrics.com/support/xm-discover/studio/studio-alerts/alerts-basic-overview-studio/](https://www.qualtrics.com/support/xm-discover/studio/studio-alerts/alerts-basic-overview-studio/) 15. Qualtrics Support, Omnichannel Listening Management: [https://www.qualtrics.com/support/omnichannel-listening/omnichannel-listening-management/](https://www.qualtrics.com/support/omnichannel-listening/omnichannel-listening-management/) 16. Qualtrics Experience Community, "Has anyone successfully set up a Qualtrics MCP in Claude Code?": [https://community.qualtrics.com/artificial-intelligence-ai-149/has-anyone-successfully-set-up-a-qualtrics-mcp-in-claude-code-33207](https://community.qualtrics.com/artificial-intelligence-ai-149/has-anyone-successfully-set-up-a-qualtrics-mcp-in-claude-code-33207) 17. Rippit, The Complete Guide to Conversation Analytics: [https://www.rippit.com/playbooks/the-complete-guide-to-conversation-analytics](https://www.rippit.com/playbooks/the-complete-guide-to-conversation-analytics) 18. Rippit, Klaviyo customer story: [https://www.rippit.com/customer-story/klaviyo](https://www.rippit.com/customer-story/klaviyo) 19. Claude Help Center, Get started with custom connectors using remote MCP: [https://support.claude.com/en/articles/11175166-get-started-with-custom-connectors-using-remote-mcp](https://support.claude.com/en/articles/11175166-get-started-with-custom-connectors-using-remote-mcp) 20. Claude Docs, Context windows: [https://platform.claude.com/docs/en/build-with-claude/context-windows](https://platform.claude.com/docs/en/build-with-claude/context-windows) 21. Rippit, Brex customer story: [https://www.rippit.com/customer-story/brex](https://www.rippit.com/customer-story/brex) 22. Delighted, Sunset notice (now redirects to qualtrics.com/delighted): [https://delighted.com/sunset](https://delighted.com/sunset) 23. Rippit, "MaestroQA is now Rippit": [https://www.rippit.com/news/maestroqa-is-now-rippit](https://www.rippit.com/news/maestroqa-is-now-rippit) 24. Rippit, The Coverage Benchmark, Part 8: Rippit: [https://www.rippit.com/research/coverage-benchmark-rippit](https://www.rippit.com/research/coverage-benchmark-rippit) 25. Rippit docs, Pipelines: [https://docs.rippit.com/pipelines/overview](https://docs.rippit.com/pipelines/overview) Build your first agent on your customer and business data. ## Getting started from an AI agent There are two ways to connect. Either works. - MCP server: `https://mcp.rippit.com/mcp` (Streamable HTTP, OAuth). The person signs in or signs up in the browser that opens. No client ID, secret or API key is needed. - CLI: install with `curl -fsSL https://rippit.sh | sh` or `brew install adtribute/tap/rippit`, then get an account one of two ways: - `rippit login`: the person signs in or signs up in a browser. - `rippit start`: creates a temporary account with no email or browser, for a person with no Rippit account. `rippit claim --wait` lets them keep it; an unclaimed account is deleted after 14 days. Then bring in data: connect a provider such as Zendesk, Intercom, Gong or Salesforce, or upload a CSV. Full steps: https://www.rippit.com/setup.md