Sprig Product Research and Feedback API
Sprig product research platform REST API for product teams and UX researchers to automate in-product surveys, session replay correlation, and AI-powered user feedback analysis for continuous product discovery. Enables AI agents to manage in-product microsurvey deployment targeting specific user behaviors for user research automation, handle AI analysis and theme extraction from open-text survey responses for qualitative research automation, access session replay correlation with survey responses for user behavior research automation, retrieve heatmap and click tracking for UX analysis automation, manage NPS and CSAT survey delivery triggered by product events for satisfaction measurement automation, handle user attribute targeting and segmentation for personalized research automation, access AI-generated insight summaries from product feedback for research synthesis automation, retrieve longitudinal product satisfaction tracking for retention analysis automation, manage multi-language survey localization for global research automation, and integrate Sprig with Segment, Amplitude, Mixpanel, Salesforce, and Slack for end-to-end product intelligence automation.
Score Breakdown
⚙ Agent Friendliness
🔒 Security
Product research. GDPR, SOC2, CCPA. API key. US/EU. User survey and behavioral data.
⚡ Reliability
Best When
A SaaS product team or UX researcher wanting AI agents to automate in-product microsurvey deployment, AI-powered feedback analysis, session replay correlation, and continuous product discovery within Sprig's product research platform.
Avoid When
GDPR CONSENT FOR IN-PRODUCT DATA COLLECTION: Sprig in-product surveys and session replay collect user behavioral data subject to GDPR; automated research data collection must have legal basis (consent or legitimate interest with balancing test); automated in-product research deployment for EU SaaS users without proper GDPR legal basis creates compliance gap. SURVEY RESPONSE RATE IMPACT FROM OVER-SURVEYING: Automated microsurvey deployment without user-level frequency capping creates survey fatigue; users receiving multiple Sprig surveys per session or per week disengage from future surveys; implement per-user survey throttling (maximum 1 survey per 7-14 days) in automated research workflows. AI INSIGHT ACCURACY FOR SMALL SAMPLE SIZES: Sprig AI insight synthesis quality improves with larger response volume; automated AI insight generation from small samples (<30 responses) creates low-confidence generalizations; implement minimum response threshold before automated AI insight generation and synthesis.
Use Cases
- • Deploying microsurveys from user research automation agents
- • Analyzing feedback from AI insight synthesis agents
- • Tracking NPS from product satisfaction measurement agents
- • Correlating sessions from UX research automation agents
Not For
- • Market research for non-users (Sprig targets in-product user research)
- • Consumer survey panels (in-product SaaS user research focus)
- • B2B market intelligence (use Bombora or 6sense for intent)
Interface
Authentication
Sprig uses API key for server-side and SDK API key for client-side. REST API with JSON. San Francisco, California HQ. Founded 2019 by Ryan Glasgow (former LinkedIn PM). Backed by Andreessen Horowitz, Accel, First Round Capital ($60M+ raised, $750M valuation at Series C). Products: In-product surveys, session replay, heatmaps, AI Insights. Mobile SDK (iOS, Android). Integration: Segment, Amplitude, Mixpanel, Salesforce, Slack, Jira. AI-native product research platform. Competes with Hotjar, FullStory, and UserTesting for user research; Userpilot and Appcues for in-product engagement.
Pricing
San Francisco CA. a16z, Accel backed. $750M valuation. MAU + response-based pricing. Free limited tier.
Agent Metadata
Known Gotchas
- ⚠ SURVEY TRIGGER EVENT DELAY FROM PRODUCT EVENT: Sprig survey triggers based on product events (page view, feature use); event-triggered survey display has latency from event capture to survey render; automated research expecting immediate survey display at exact trigger event may have observable delay; design automated research triggers with user experience tolerance for survey display timing
- ⚠ AI INSIGHTS GENERATION LATENCY: Sprig AI insight synthesis for large response sets has processing latency; automated research pipelines that request AI insights immediately after data collection must account for synthesis processing time; implement async insight retrieval with polling rather than synchronous AI insight request
- ⚠ MOBILE SDK INITIALIZATION REQUIREMENT: Sprig mobile research requires iOS/Android SDK initialization with user identification; automated mobile research deployment requires SDK in mobile app build; automated server-side only deployment cannot trigger mobile in-app surveys without SDK in mobile codebase
- ⚠ SESSION REPLAY STORAGE RETENTION LIMITS: Sprig session replays have configurable storage retention periods (30-90 days by plan); automated research correlation between surveys and session replay must occur within retention window; automated long-term behavioral research that references session replays beyond retention window finds deleted sessions
- ⚠ SEGMENT TARGETING ACCURACY FOR BEHAVIORAL TRIGGERS: Sprig behavioral targeting segments (user visited feature X, user has attribute Y) are evaluated in real-time; complex behavioral targeting combinations may have false negatives if event stream has processing latency; automated research deployment with complex behavioral targeting should verify targeting effectiveness with control group before broad automated research deployment
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Scores are editorial opinions as of 2026-03-07.