Introduction
Marvin is a customer insights platform built around a research repository, AI-moderated voice interviews, and an in-product voice intercept called Live Intercept. Sprig is an enterprise survey platform that uses AI agents to run structured studies in product, by email, and through panels. Choose Marvin to store, search, and question interviews and other qualitative evidence. Choose Sprig when a decision needs measured answers with a stated sample.
Last updated October 2026.
At a Glance
| Category | Sprig | Marvin |
|---|
| Core Category | Enterprise survey platform powered by AI agents | Customer insights platform with a research repository |
| Main Unit of Work | A structured study fielded to a defined population | A searchable body of interviews, calls, tickets, and research |
| Interviews | Not a Sprig product area | AI-moderated voice interviews in 40+ languages |
| In-Product Reach | Surveys on web, iOS, Android, React Native, and Flutter | Live Intercept voice interviews on websites and web products, in demo access |
| Quantitative Methods | MaxDiff, conjoint, rank order, and quotas on Enterprise | Charts for imported single-choice and Net Promoter Score questions |
| Repository | Not a Sprig product area | Knowledge Hub with Ask AI and Deep Research reports |
| MCP Server | Yes, with draft-only study creation | Yes, with 16 read and nine write tools |
| Security Badges | SOC 2 Type II, HIPAA, GDPR, CCPA | SOC 2 Type II, ISO 27001, ISO 42001, HIPAA, GDPR |
| Pricing Model | Does not publish pricing | Free plan, then pricing by demo or sales |
| G2 Rating | 4.3 out of 5 from 199 reviews | 4.8 out of 5 from 136 reviews |
Which Platform Should You Choose?
Marvin fits teams that need to make sense of qualitative evidence they already have or can collect by conversation. Sprig fits teams that need a number with a stated sample behind a decision.
Choose Sprig if Your Decisions Need Measured Answers
- You need to survey users inside a web or native mobile app at the moment they act, using events and attributes
- You need MaxDiff, conjoint, rank order, randomization, or response quotas
- You want in-product, email, and panel studies in one workspace
- You want agents that draft studies, probe open-text answers, and test differences between segments
- You want an MCP connection that can create studies only in draft, with a person approving launch
Choose Marvin if Your Evidence Is Mostly Qualitative
- You run customer interviews and want an AI interviewer that works across languages and time zones
- You need one repository for interviews, calls, support tickets, and past research
- You want teammates to query that repository in plain language, including from Slack
- You need PII redaction that blurs names and faces in recorded video
- You want to start on a free plan before a sales conversation
Teams that land on both lists can run both platforms, and the router near the end of this guide shows how to split the work.
Background and Positioning: How Sprig and Marvin Compare
This chapter defines each platform, where they overlap, and where Sprig is the weaker choice.
What Marvin Is
Marvin’s homepage calls it "the customer insights platform for modern teams." The company is based in Oakland, California. Its product menu groups the work into a Knowledge Hub, Ask AI, Reporting and Insights, Analysis Studio, an MCP server, AI Moderated Interviews, Live Interviews, and Live Intercept. G2 files Marvin under User Research Repositories, Insight Engines, and Transcription.
What Sprig Is
Sprig’s homepage reads "Enterprise surveys. Powered by agents." It names Design, Field, Analyze, and Synthesize agents and an MCP connector. Studies reach respondents through in-product surveys on web and mobile, email, and external research panels.
Evidence You Have Versus Evidence You Need
Marvin starts with evidence that already exists or arrives as conversation. A researcher uploads recordings, connects support tickets, or runs an AI interview, then asks the repository what customers have said. The unit of work is a transcript or a note with a source behind it.
Sprig starts with a question that doesn’t have an answer yet. A researcher defines a population, writes the instrument, fields it, and analyzes the distribution of responses. The unit of work is a response set large enough to support a claim.
Where the Platforms Overlap
Marvin imports survey data from Qualtrics, SurveyMonkey, and Microsoft Forms, charts single-choice and Net Promoter Score (NPS) questions, and lets Ask AI find trends across respondents. It also intercepts website and product visitors. Sprig asks AI follow-up questions inside surveys and synthesizes open text into themes. Both vendors publish a Model Context Protocol (MCP) server.
A question type isn’t a methodology, and a voice interview isn’t a survey with more words.
Where Sprig Is the Weaker Choice
Sprig is the weaker choice for several jobs Marvin handles directly. It doesn’t run interviews, record or transcribe calls, or keep a cross-study repository. Its security page lists AWS hosting in the United States, no regional residency option, and no ISO certification of its own.
Sprig also doesn’t publish its MaxDiff estimation method, weighting approach, or sample size guidance. A team that needs any of those on day one should weigh them before the method comparison below.
Study Creation and Quantitative Methods: How Sprig and Marvin Compare
This chapter compares Sprig’s survey builder with Marvin’s interview discussion guides and its handling of imported survey data.
Study Creation at a Glance
| Category | Sprig | Marvin |
|---|
| Survey Builder | 15 documented question types | No native survey builder documented, surveys arrive by import |
| Interview Guides | Not applicable | AI-generated discussion guides, with uploads of existing guides |
| MaxDiff and Conjoint | Enterprise plan, Standard Format surveys | Not documented |
| Randomization | Answer options, rank order, MaxDiff, and conjoint | Not documented for surveys |
| Quotas | Response-based quotas on Enterprise | Response caps and closing dates for AI interviews |
| AI Drafting | Design Agent builds a study from a brief | AI drafts discussion guides |
Sprig’s Question Library
Sprig’s documentation lists 15 question types, including rating scale, open text, matrix, multiple choice, NPS, and video and voice. Rank order, recorded task, MaxDiff, and conjoint are limited to the Enterprise plan. MaxDiff and conjoint also require surveys in Standard Format.
MaxDiff, Conjoint, and Randomization
Sprig documents MaxDiff with sets of 4 to 24 items, and conjoint with at least three features of three levels each, up to four options per task and 15 tasks per respondent. MaxDiff item order is randomized per respondent, conjoint can randomize feature order, and multiple-choice options can be shuffled with pinned choices held in place.
Randomization matters because a fixed order can create position bias. None of the Marvin pages read for this guide document MaxDiff, conjoint, or answer randomization.
Quotas and Population Control
Sprig supports response-based quotas on the Enterprise plan, so a study stops filling segments that are already complete. Sprig’s quotas have limits of their own: criteria can use only single-select, rating scale, and NPS questions, and criteria can’t be edited after launch.
Marvin controls interview volume differently. An AI interview study can end at a response cap or a closing date, whichever comes first. That controls cost and timing, but it doesn’t balance segments.
Marvin’s Discussion Guides
Marvin’s AI generates discussion guides for interviews, and researchers can upload guides they already use. Within a guide, the researcher sets the depth of probing for each question and controls branching. For interview research, that’s the right instrument. A survey builder isn’t.
How Marvin Handles Imported Survey Data
Marvin’s help center describes a direct Qualtrics import on Pro and Enterprise plans. Marvin uses AI to classify each question as open-ended, NPS, single choice, card sort, or ranking, and researchers can correct the label. The first import brings in the 5,000 most recent responses, and some Qualtrics types, including constant sum, slider, and heat map questions, can’t be synced. Help articles also cover SurveyMonkey and Microsoft Forms imports.
Upcoming: Marvin’s Mixed Methods Study
At its summer 2026 showcase, Marvin announced a Mixed Methods Study that pairs structured survey questions with AI-moderated follow-ups. As of October 27, 2026, it’s listed as upcoming, not launched. Teams evaluating Marvin for survey work should ask for its current status.
Study Creation Verdict
Sprig wins study creation for quantitative research. Both platforms help a researcher draft an instrument with AI, but Sprig documents a native survey builder with MaxDiff, conjoint, randomization, and quotas that Marvin doesn’t document. Marvin is the better fit when the instrument is an interview discussion guide, or when the surveys already exist in another tool and the job is to analyze them alongside interviews.
AI Capabilities: How Sprig and Marvin Compare
Both vendors lead with AI, but they point it at different work. Marvin aims AI at conversations and the repository: running interviews, labeling notes, and answering questions across everything stored. Sprig aims AI at studies: drafting them, probing inside them, and analyzing the results.
AI Capabilities at a Glance
| Category | Sprig | Marvin |
|---|
| Study Creation | Design Agent drafts a study from a brief or goal | AI-generated discussion guides |
| Live Probing | Field Agent asks follow-up questions on open text | AI interviewer probes by voice, with set depth |
| Synthesis | Synthesize Agent groups responses into themes with counts | Auto-labeling, affinity mapping, and Deep Research reports |
| Question Answering | Analyze Agent conversation over one study’s data | Ask AI across the whole repository, in quick and long modes |
| Statistics | Crosstabs, t-tests, ANOVA, correlation, and Van Westendorp | Not documented |
Marvin’s AI Moderated Interviewer
Marvin’s voice-to-voice AI interviewer has run since May 2025, according to Marvin’s September 2026 announcement. It runs simultaneous one-on-one interviews across time zones in more than 40 languages. Participants can share their screen, use push-to-talk, and explore Figma, Lovable, or custom prototypes during the session. Recordings and transcripts land in the repository.
Sprig doesn’t offer AI-moderated interviews.
Marvin’s Ask AI and Deep Research
Marvin’s Ask AI answers plain-language questions across the repository. Quick mode returns short, cited answers, and Agentic Ask AI 2.0 uses several specialized agents for search, analysis, citation, and synthesis on longer questions. Deep Research reports link each claim to its source, and those citations still need checking against the transcript. Organizational Memory, introduced October 8, 2026, lets admins load brand terms and product descriptions for Ask AI to use.
Sprig’s Four Agents
Sprig’s Design Agent ingests a research brief or survey document and produces an editable study, flagging broken logic and unclear questions. Researchers should still review drafted logic before launch. The Field Agent delivers questions one at a time in a chat-style format and asks contextual follow-ups, a feature researchers can switch off per study.
Sprig’s Field Agent page cites up to 2x improvement in completion rates from customer programs, a vendor figure with no published method.
The Synthesize Agent groups responses into named themes and shows how many responses support each one. The Analyze Agent runs crosstabs, t-tests, analysis of variance (ANOVA), correlation, and Van Westendorp using Pandas and SciPy. Sprig labels the Analyze Agent as in preview, so teams should confirm availability before relying on it.
What AI Doesn’t Replace
Neither platform’s AI removes the need for review. Check Ask AI citations against the source transcript, and check Synthesize Agent themes against the raw responses, before acting on either. Researchers remain responsible for the conclusions.
AI Capabilities Verdict
Marvin wins AI for interview work, and Sprig wins AI for survey work. Marvin offers an AI interviewer, repository-wide question answering, and cited research reports. Sprig offers agents that draft studies, probe respondents, and test whether segment differences are statistically significant. Neither covers the other’s job.
In-Product Reach and Distribution: How Sprig and Marvin Compare
This is the chapter where the two platforms now compete most directly. Both put an invitation in front of people while they use a website or product. What happens after the invitation differs.
In-Product Reach and Distribution at a Glance
| Category | Sprig | Marvin |
|---|
| In-Product Format | Structured survey with tap, rating, and text answers | Voice or video AI interview through Live Intercept |
| Availability | Generally available | Demo access since July 6, 2026, broader access later in 2026 |
| Platforms | Web, iOS, Android, React Native, and Flutter SDKs | Web snippet on public URLs and web products |
| Targeting | Behavioral events and user attributes | Page, click, custom event, session, location, device, UTM source, and user properties |
| Email Delivery | Native, from the customer’s own domain | Not documented as a channel |
| External Panels | Research panels with 300+ targeting attributes | No owned panel described on pages read |
How Live Intercept Works
Live Intercept places a widget on a website or inside a web product. When a visitor matches the trigger rules, the widget invites them to an AI-moderated interview. If they accept, they talk to the AI interviewer and can share their screen. Marvin’s help center says the session is entirely audio or video, participants can’t type responses, and they need to grant microphone access to take part.
Setup takes a code snippet on the connected domain. Marvin’s help center lists these trigger types:
- Page rules on the current or previously visited page
- Clicks on a button, heading, or list, or custom events sent in code
- Session length, active time, first visit, or pages viewed
- Country, based on IP address
- Browser, operating system, or device
- UTM source
Audiences can filter on user ID, email domain, custom properties, and earlier intercepts. Recordings and transcripts go to the repository with automatic PII redaction.
Sprig’s In-Product Surveys
Sprig’s SDKs for web, iOS, Android, React Native, and Flutter trigger a survey after a specific action, during onboarding, or at a moment of friction, using behavioral events and user attributes. Question wording can draw on live user attributes.
Sprig captures a session replay clip with each response, showing up to five minutes before and after the answer, which links what a user did to what they said. The web and mobile pages describe both.
Live Intercept Versus an In-Product Survey
The two formats answer different questions, so the choice should follow the question. The table below compares them on the points that decide most studies.
| Decision Point | Marvin Live Intercept | Sprig In-Product Survey |
|---|
| What the participant does | Speaks with an AI interviewer and can share a screen | Taps, rates, or types a short answer |
| What finishing requires | Microphone access and time for a conversation | Short tap, rating, or text answers |
| What you get | A transcript and recording with themes | Structured responses plus a replay clip |
| Typical sample | Usually fewer, longer sessions | Many short, comparable answers |
| Native mobile apps | Not documented, device targeting only | iOS, Android, React Native, and Flutter |
| Best use | Understanding why visitors hesitate on a page | Measuring how many users hit the same friction |
Marvin’s own Live Intercept page frames the contrast directly: "A survey gives you answers to questions you already thought of." That’s a fair description of the trade-off. A survey measures the questions you knew to ask, and an interview finds the ones you didn’t.
Email, Panels, and Known Customers
Sprig’s email delivery sends surveys from the customer’s own domain, with embedded user IDs, attribute piping, and multiple runs from one study for tracking over time. Sprig’s research panels reach B2B and B2C participants across dozens of countries with more than 300 targeting attributes, and incentives are handled in the platform.
Marvin’s pages read for this guide don’t describe a participant panel or native email survey delivery. Teams recruiting for Marvin interviews should confirm how participants are sourced for their use case.
In-Product Reach and Distribution Verdict
Sprig wins distribution today. Both platforms reach people inside a website or web product, but Sprig’s in-product surveys are generally available on native mobile as well as web, and Sprig adds email and panel channels that Marvin doesn’t document.
Marvin’s Live Intercept is the better choice when the goal is a spoken conversation with visitors at a specific moment, and it may close part of this gap once it leaves demo access.
Repository, Qualitative Collection, and Integrations: How Sprig and Marvin Compare
This chapter covers the work Marvin was built for. A repository, interviews, and recorded video sit at the center of its product and outside Sprig’s.
Repository and Integrations at a Glance
| Category | Sprig | Marvin |
|---|
| Cross-Study Repository | Not a Sprig product area | Knowledge Hub across interviews, calls, tickets, and research |
| Video and Transcripts | Session replay clips around survey responses | Recordings, transcripts, clips, and trimming |
| PII Redaction | Not documented for recordings | Blurs names and faces, with speaker anonymization |
| Integrations | Slack, Notion, Dovetail, Amplitude, Mixpanel, and Segment | 30+ integrations by Marvin’s own count, plus an Import API |
| Chat Access | Not documented | Ask AI in Slack, with Microsoft Teams announced |
| MCP | Role-based, draft-only study creation | 16 read and nine write tools |
Marvin’s Knowledge Hub
Marvin’s Knowledge Hub holds interviews, CRM records, support tickets, existing research, product data, and customer calls in one place. Ask AI and Deep Research query across all of it, and topic subscriptions on Enterprise send weekly insight reports to Marvin or Slack. A new team member can find what the company already learned before commissioning another study.
Sprig stores responses by study and doesn’t position itself as a repository. That cross-study record is Marvin’s main strength.
Recordings, Clips, and PII Redaction
Marvin’s annotation tool lets researchers trim recordings into clips, and its PII redaction detects and blurs names and faces even with movement or partial visibility. Researchers can redact a time range or a drawn area of the frame, anonymize speaker identities, and preserve product names during redaction. Marvin’s pricing page lists PII redaction as an add-on on Pro and included on Enterprise.
Integrations and the Import API
Marvin says it brings in data from more than 30 integrations, and its 2025 review names SharePoint, OneDrive, Microsoft Forms, Maze, dscout, and Salesforce. The Import API, launched in August 2026, syncs audio, video, text, CSV, PDF, and Office files continuously.
Sprig integrates with Slack, Notion, Dovetail, Amplitude, Mixpanel, and Segment, and offers a public API and webhooks. Sprig documents no direct Marvin integration.
Ask AI in Slack
Marvin’s Ask AI runs in Slack through the /heymarvin and /research commands, returning answers with quotes and citations. On Enterprise, teammates without Marvin accounts can use it, limited to public projects and verified email domains. Marvin has said Ask AI is coming to Microsoft Teams.
MCP Compared
Both vendors document an MCP server, so neither can claim exclusivity. Marvin’s help center lists 16 read tools and nine write tools, including creating projects, creating insights, and generating discussion guides, with each user authorized through OAuth. Marvin’s pricing page includes MCP on Pro and Enterprise, while its help center describes individual connections on Enterprise plans.
Sprig’s documentation states that every connection runs through OAuth, permissions are checked at every tool call, and study creation happens in draft only. A person approves each study in the Sprig app, admins can turn the server off for the whole organization, and Sprig doesn’t use response data to train models.
Repository and Qualitative Collection Verdict
Marvin wins this chapter outright. It offers a cross-study repository, interviews, recordings, redaction, and chat access that Sprig doesn’t offer. A team whose research is mainly interviews and accumulated qualitative evidence should choose Marvin for that work.
Analysis and Reporting: How Sprig and Marvin Compare
This chapter compares how each platform turns collected data into findings: question answering across a repository on one side, statistical testing within a study on the other.
Analysis and Reporting at a Glance
| Category | Sprig | Marvin |
|---|
| Open-Text Analysis | Themes with response counts | Auto-labeling, affinity mapping, and notes |
| Closed-Question Analysis | Native charts and crosstabs | Bar and pie charts for imported questions |
| Statistical Tests | t-tests, ANOVA, and correlation | Not documented |
| Behavior Context | Session replay clips around responses | Screen shares in interview recordings |
| Reports | Structured reports with summaries and recommendations | AI Writer and Deep Research reports with citations |
Marvin’s Analysis Workflow
Marvin’s Analysis Studio, which its menu describes as "mixed methods analysis," lets researchers label notes in bulk, build affinity maps, and view imported survey questions as bar or pie charts with filters. Ask AI identifies trends, patterns, and outliers across respondents, links insights to specific people, and can create charts and reports. The Qualtrics import article doesn’t describe statistical tests.
Sprig’s Analysis Workflow
Sprig’s Synthesize Agent clusters open-text responses into themes, and its reports include executive summaries, key takeaways, and recommendations that researchers can edit before sharing. The Analyze Agent tests whether a difference between segments is statistically significant and lets researchers adjust an analysis in natural language or send it to Claude or another model.
Searching Evidence Versus Testing Differences
Marvin answers questions like "What have enterprise customers said about onboarding over the past year?" by searching everything stored. Sprig answers questions like "Do satisfaction scores differ between plan tiers, and is the difference significant?" by testing one study’s data. Each question needs a different tool.
Analysis Verdict
Sprig wins analysis for survey data, with crosstabs and replay context today and significance tests through the Analyze Agent, which is in preview. Marvin is stronger at searching and summarizing qualitative evidence across many studies. Teams that need to defend a number to a leadership team should lean on Sprig, and teams that need to find what customers already said should lean on Marvin.
Enterprise Security, Governance, and Administration: How Sprig and Marvin Compare
This chapter compares what each vendor publishes about certifications, access control, and hosting. Most items sit at parity, with two real differences.
Security and Administration at a Glance
| Category | Sprig | Marvin |
|---|
| SOC 2 Type II | Badge on its security standards page | Listed on its security page, with annual audits stated on its pricing page |
| ISO 27001 | Relies on AWS’s certification | Stated on its security page |
| ISO 42001 | Not stated | Stated on its security page |
| HIPAA | Badge on its security standards page | Add-on on Pro, included on Enterprise |
| GDPR | Badge on its security standards page | Stated on its security page |
| Single Sign-On | SAML | Okta and SAML, plus Google and Microsoft sign-in |
| SCIM | Not mentioned | Not listed |
| Hosting | AWS facilities in the United States | US or EU data centers, per its pricing page |
Certifications and Attestations
Sprig holds SOC 2 Type II and displays HIPAA, GDPR, California Consumer Privacy Act (CCPA), and Data Privacy Framework badges. Marvin’s pricing FAQ states SOC 2 Type II, and its security page lists ISO 27001, ISO 42001 for AI management, HIPAA, and GDPR.
Sprig doesn’t hold an ISO certification itself and relies on AWS’s ISO 27001 for hosting. For a buyer whose security questionnaire requires a vendor-held ISO 27001 certificate, that’s a disqualifying gap for Sprig.
Single Sign-On and Access Control
Sprig supports single sign-on (SSO) through SAML, along with user roles and individual permissions, and keeps logs of user access for at least one year. Marvin’s pricing page lists Okta and SAML, Google and Microsoft sign-in, and free guest accounts through a magic link. Neither vendor’s pages mention System for Cross-domain Identity Management (SCIM) provisioning, so teams that automate user lifecycle changes should ask both.
Hosting and Data Residency
Sprig hosts its software in AWS facilities in the United States and lists no regional residency option. Marvin’s pricing page offers storage in US or EU data centers but doesn’t say which plans include it. Teams with residency requirements should confirm the plan in writing before signing.
Security and Administration Verdict
Marvin wins security. Both vendors publish SOC 2 Type II, HIPAA, GDPR, and SAML single sign-on, but Marvin also holds ISO 27001 and ISO 42001 certifications of its own and offers EU data storage, and Sprig offers neither. Sprig documents keeping access logs for at least one year, so teams should ask Marvin what its admin controls log.
Implementation, Packaging, and Total Cost of Ownership: How Sprig and Marvin Compare
Most teams comparing these platforms aren’t replacing one with the other. They’re deciding which to add, so this chapter covers packaging, setup, and what each platform leaves for a second tool.
Implementation and Cost at a Glance
| Category | Sprig | Marvin |
|---|
| Pricing Publication | Does not publish pricing | Does not publish prices for paid plans |
| Entry Path | Starts with a demo | Free plan with no credit card |
| Plans | Enterprise features on the Enterprise plan | Free, Starter, Pro, and Enterprise |
| AI Collection | Field Agent follow-ups within surveys | AI Research Suite add-on for interviews and Live Intercept |
| Setup for In-Product Work | SDK installed once | Code snippet on each connected domain |
Packaging and Pricing Models
Marvin lists four plans: Free, Starter, Pro, and Enterprise. Free is self-serve with no credit card. Starter and Pro go through a demo, Enterprise goes through sales, and an Enterprise trial is arranged with the sales team. AI-moderated interviews and Live Intercept sit in an AI Research Suite add-on for paid plans, and HIPAA and PII redaction are add-ons on Pro.
Sprig doesn’t publish pricing, and its homepage offers a demo rather than a free plan or self-serve signup. Its documentation limits rank order, recorded tasks, MaxDiff, conjoint, and quotas to the Enterprise plan.
Setup and Time to First Study
Marvin’s free plan lets a researcher upload files and try the repository without a sales call. That’s an advantage for a small team. Live Intercept needs a code snippet and connected domain, and custom events and properties need further code.
Sprig’s in-product studies need an SDK installed once. After that, research teams create studies and adjust targeting without engineering work, according to Sprig’s web page.
Running Both Platforms
Sprig’s raw response export can be uploaded to Marvin as a CSV or synced through Marvin’s Import API, so survey results sit beside interviews in the repository. Neither vendor documents a direct connector to the other, so teams should test the export path during evaluation.
Total Cost of Ownership Is Asymmetric
The gap that costs money differs by buyer. A team running mostly surveys that picks Marvin will add a second tool for building and fielding quantitative studies. A team running mostly interviews that picks Sprig will add a second tool for recording, transcription, and a repository. The cheaper platform is the one that covers more of the team’s weekly work.
Questions to Settle Before You Commit
A demo or trial can settle the points documentation leaves open.
In a Marvin evaluation, a team should check five things:
- Whether Live Intercept is available for the account and when it leaves demo access
- Whether native mobile apps are supported or planned
- Which plan includes MCP access for the team
- Which data residency regions are offered, and on which plan
- Whether the Mixed Methods Study has launched and what it measures
In a Sprig evaluation, a team should check five different things:
- Which question types the plan includes, since MaxDiff, conjoint, and quotas sit on Enterprise
- Business Associate Agreement terms, if health data is in scope
- How user provisioning works without documented SCIM
- Panel coverage and incentives for the target audience
- Whether the Analyze Agent is out of preview for the account
Implementation Verdict
Marvin wins implementation. A free plan with no credit card lets a team test the repository before any sales call, while Sprig starts with a demo.
Which Platform Is Right for Your Team?
Each audience below leans one way, and for several the honest answer is both. The chapter ends with a fit matrix.
Product Managers
Sprig fits product managers who want fast answers from users inside the product, at the moment of an action, tied to behavior through session replay and to experience measurement over time. Marvin fits product managers who want to ask the repository what customers have said before writing a spec, including from Slack.
User Research Teams
Marvin fits user research teams that run interviews, manage recordings, and need a repository the whole company can search. Sprig fits the quantitative layer of the same program, sizing an interview finding across a larger, defined user base. That pairing is the core of strategic and foundational research.
Market and Consumer Insights Teams
Sprig fits market and consumer insights teams that need quotas, randomization, MaxDiff, and conjoint, fielded to panels or customer lists. Marvin fits insights teams that already field surveys in Qualtrics or SurveyMonkey and want those results analyzed alongside interviews and calls.
Research Operations
Marvin fits research operations teams that want one governed home for research assets, with retention controls and redaction. Sprig fits operations teams that want one survey platform with role-based permissions and an MCP connection that creates drafts only.
Product Marketing
Marvin fits product marketers who mine sales calls and customer conversations for messaging language. Sprig fits product marketers who need to test which message or concept performs best with a defined audience, as in concept and prototype testing.
Which Platform Fits Different Organizations?
| Organization Type | Recommended Platform | Why |
|---|
| Product team with in-product and mobile questions | Sprig | Event-triggered surveys on web and native mobile |
| Research team with years of scattered interviews | Marvin | Knowledge Hub and repository-wide Ask AI |
| Insights team running quota-controlled studies | Sprig | Quotas, MaxDiff, and conjoint on Enterprise |
| Global team interviewing in many languages | Marvin | AI interviewer in 40+ languages |
| Team that needs vendor-held ISO 27001 | Marvin | Stated on its security page |
| Team that needs significance tests on survey data | Sprig | Analyze Agent, in preview |
| Small team that wants to try before buying | Marvin | Free plan with no credit card |
| Team that runs both interviews and large surveys | Both | Each covers the work the other doesn’t |
Routing Research Questions to the Right Platform
Find your question below. The router sends 10 common research questions to the platform whose strengths fit.
Research Question Router
| Research Question | Best Fit | Why |
|---|
| What have customers already said about billing? | Marvin | Repository search across studies and calls |
| Why do visitors hesitate on the pricing page? | Marvin | Live Intercept voice interview at that moment |
| How many users hit the same checkout friction? | Sprig | Event-triggered in-product survey |
| Which of 12 candidate features matters most? | Sprig | MaxDiff on Enterprise |
| Which plan bundle will customers choose? | Sprig | Conjoint on Enterprise |
| How do customers describe the problem in their own words? | Marvin | AI-moderated interviews |
| Do satisfaction scores differ between plan tiers? | Sprig | Analyze Agent significance tests |
| What did sales calls reveal about a competitor? | Marvin | Call recordings in the Knowledge Hub |
| How satisfied are mobile users after a new release? | Sprig | Native mobile SDK surveys |
| Is an interview finding true across the customer base? | Both | Interviews first, survey second |
Worked Pairing: Repository First, Survey Second
The numbers below are illustrative, not results from a real study. A product team asks Marvin’s repository what customers have said about permissions. Ask AI returns 14 interview and call excerpts in which administrators describe confusion about role names, each linked to its source, and a researcher checks each excerpt against its transcript.
That’s a strong hypothesis with a small, self-selected base. The team writes a three-question survey in Sprig and triggers it when administrators open the permissions screen in the web and iOS apps. It collects 600 responses in a week, and the Analyze Agent compares confusion rates across plan tiers.
The team uploads the response export to Marvin, so the measured result sits beside the interviews that prompted it. The repository found the problem, and the survey sized it.
Frequently Asked Questions
What Is the Difference Between Sprig and Marvin?
Marvin is a customer insights platform built around a research repository, AI-moderated voice interviews, and Live Intercept. Sprig is an enterprise survey platform that fields in-product, email, and panel studies and analyzes results with agents. Marvin helps teams understand evidence they have or can collect by conversation, and Sprig helps teams measure how widely a finding holds across a defined population.
Is Marvin a Survey Tool?
Marvin isn’t a survey tool. It’s a customer insights platform with a repository and an interview capability. It imports survey data from Qualtrics, SurveyMonkey, and Microsoft Forms and charts some question types, but Marvin’s public pages don’t document a native survey builder, MaxDiff, conjoint, or quotas. Its announced Mixed Methods Study, which adds structured questions, hadn’t launched as of October 27, 2026.
Is Sprig an Alternative to Marvin?
Sprig is an alternative to Marvin for measurement, not for the repository or interviews. Sprig doesn’t record calls, run interviews, or store research across studies. Teams that need those should keep Marvin or choose another repository and use Sprig for in-product surveys, quantitative methods, and statistical analysis.
How Does Marvin Live Intercept Compare With Sprig’s In-Product Surveys?
Marvin’s Live Intercept invites website and web-product visitors into a voice or video AI interview, and participants can’t type answers. It has been in demo access since July 6, 2026. Sprig’s in-product surveys collect structured tap, rating, and text responses on web and native mobile apps, with a replay clip for each response. Live Intercept explains behavior, and an in-product survey measures it.
Does Marvin Support MaxDiff or Conjoint Analysis?
As of October 27, 2026, none of the Marvin pages read for this guide document MaxDiff or conjoint. Marvin can import ranking questions from Qualtrics and chart them. Sprig documents both MaxDiff and conjoint as Enterprise plan question types, with randomization built in.
Does Sprig Run AI-Moderated Interviews?
Sprig doesn’t run AI-moderated or moderated interviews. Its Field Agent asks AI follow-up questions inside surveys, which adds depth to open-text responses, but it doesn’t replace a conversation. Teams that need interviews can use Marvin alongside Sprig.
Does Marvin Publish Pricing?
Marvin doesn’t publish prices for its paid plans. It offers a free plan with no credit card, while Starter and Pro go through a demo and Enterprise goes through sales. Its AI interviews and Live Intercept sit in a paid add-on. Sprig doesn’t publish pricing either, and its path starts with a demo.
How Are Sprig and Marvin Packaged?
Marvin packages its product in four plans with different seat types, including full seats, a Collaborator seat, and viewer seats, plus paid add-ons for AI interviews, Live Intercept, HIPAA, and PII redaction. Marvin doesn’t publish prices for paid plans. Sprig doesn’t publish pricing and limits MaxDiff, conjoint, rank order, and quotas to its Enterprise plan, so buyers should ask both vendors how cost scales with seats and volume.
How Do Sprig and Marvin Compare on AI?
Marvin applies AI to interviews and the repository: an AI interviewer, auto-labeling, Ask AI, and Deep Research reports with citations. Sprig applies AI to surveys through the Design Agent, Field Agent, Synthesize Agent, and Analyze Agent. Researchers remain responsible for checking conclusions on both platforms.
Do Sprig and Marvin Both Have MCP Servers?
Yes, both vendors document a Model Context Protocol (MCP) server. Marvin’s lists 16 read and nine write tools and appears on its Pro and Enterprise plans. Sprig’s checks role-based permissions at every call, creates studies in draft only, and can be switched off by an admin for the whole organization. Neither vendor can claim exclusivity.
Which Platform Is Better for Enterprise Security Requirements?
Sprig and Marvin both publish SOC 2 Type II, HIPAA, GDPR, and SAML single sign-on. Marvin also lists ISO 27001, ISO 42001, and US or EU data storage, while Sprig relies on AWS’s ISO 27001 and lists only United States hosting. Teams with a vendor-held ISO requirement or a residency requirement should treat that as a deciding point and request current reports from both.
Can Teams Use Sprig and Marvin Together?
Yes, Sprig and Marvin can be used together. Marvin holds interviews, calls, and past research, and Sprig measures how widely a finding holds through in-product, email, and panel surveys. Sprig’s response export can be uploaded to Marvin as a CSV, so results land beside the interviews that prompted them.
Which Platform Should My Team Choose?
Choose Marvin if your research centers on interviews, calls, and a growing body of qualitative evidence that teammates need to search. Choose Sprig if your research centers on questions that need a number with a stated sample, or on reaching users inside your web and mobile apps. If you run both large surveys and interviews, pair them as the worked example shows.
To see how a Sprig survey sizes the themes your repository surfaces, explore Sprig and book a demo.
