SurveyMonkey

Integrate Mavera with SurveyMonkey — bulk response analysis, survey design optimization via focus groups, and automated report generation

Overview

Pull data from SurveyMonkey (Survey Responses, Survey Structure, Collectors) → analyze with Mavera (Mave Agent, Focus Groups, Chat, Generate) → discover statistical patterns and sentiment trends in bulk responses, optimize survey question clarity with synthetic respondents, and auto-generate executive summaries.

SurveyMonkey API — Base URL: https://api.surveymonkey.com/v3/. Auth: OAuth 2.0 or Personal Access Token. Rate limits: Private apps: 120 req/min, 500 req/day. Public apps: higher limits on paid plans.

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Prerequisites

1. SurveyMonkey access token

   Create a Private App or use a Personal Access Token. Required scopes: surveys_read, responses_read, collectors_read.
2. Mavera API key

   Get your key from Mavera dashboard.
3. Environment variables

   export SURVEYMONKEY_TOKEN="your_access_token"
   export MAVERA_API_KEY="mvra_live_xxxxx"
   

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Jobs

#	Job	SurveyMonkey Data	Mavera Surface	Output
1	Bulk Response Analysis	Bulk response data	Mave Agent	Statistical patterns + recommendations
2	Survey Design Optimization	Survey structure	Focus Groups	Clarity and bias feedback
3	Response Data → Generate Reports	Response data	Generate (brand voice)	Executive summary report

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Executive Summary

1,247 respondents completed our Q1 satisfaction survey between January 15 – February 28, 2026. Overall satisfaction scores 7.2/10, up from 6.8 in Q4 2025. Onboarding remains the primary friction point, with 34% of respondents rating it below 5/10.

Methodology

Online survey distributed to active customers via email (72%) and in-app prompt (28%). 18 questions across satisfaction, feature usage, support experience, and open-ended feedback. Response rate: 23%.

Key Findings

1. Onboarding Satisfaction Gap (Critical) Respondents onboarded in the last 90 days score 4.1/10 vs 8.3/10 for those past 6 months. The gap suggests onboarding quality, not product quality, drives early dissatisfaction.

2. Feature Usage Concentration 3 of 12 features account for 78% of daily usage. Six features are used by fewer than 15% of respondents — candidates for deprecation or repositioning.

3. Support Channel Mismatch 67% of under-35 respondents prefer chat support; 58% of over-45 prefer email. Current allocation: 70% email, 30% chat.

4. Competitive Pressure Signal 14% of detractors mention “evaluating alternatives” in open-ended responses. Cross-reference with CRM for immediate outreach.

5. Documentation Demand “Better documentation” appears in 38% of open-ended improvement suggestions — the single most requested change.

Recommendations

1. Deploy a 14-day structured onboarding program with milestones
2. Reallocate support capacity: 50/50 chat/email split
3. Create a documentation sprint targeting the 3 most-used features
4. Flag “evaluating alternatives” respondents for CS outreach
5. Run follow-up survey with the 4.1/10 onboarding cohort

### Error Handling

<AccordionGroup>
  <Accordion title="Brand voice creation">If no `BRAND_VOICE_ID` is provided, the code creates a minimal voice from a sample paragraph. For better results, use an existing voice trained on your actual research reports.</Accordion>
  <Accordion title="Data block size">Large surveys produce JSON summaries exceeding 5,000 characters. The code truncates to fit Mavera's context. For 30+ question surveys, generate section-by-section reports.</Accordion>
  <Accordion title="Open-ended response volume">Reports with 500+ open-ended responses per question need pre-summarization. Send open-ended data to Mave Chat first for theme extraction, then include themes in the report prompt.</Accordion>
</AccordionGroup>

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## Rate Limits & Production Notes

| Endpoint | Limit | Strategy |
|----------|-------|----------|
| All endpoints (private apps) | 120 req/min | 500ms delay between calls |
| Daily cap (private apps) | 500 req/day | Cache aggressively |
| Survey details | 120 req/min | Cache locally — structure rarely changes |
| Bulk responses | 120 req/min | 100 per page; expect 10-20 calls |

<Warning>
The **500 req/day** limit for private apps is the real constraint. A single survey analysis (structure + responses + report) uses 10-25 calls. Plan your daily budget carefully. Cache survey structures and responses locally after the first pull.
</Warning>

**Production checklist:**

- Store `SURVEYMONKEY_TOKEN` and `MAVERA_API_KEY` in a secrets manager.
- Cache survey structure (`/details`) locally — it changes only when you edit the survey.
- For surveys with 2,000+ responses, pull responses once and store locally rather than re-fetching.
- Use `BRAND_VOICE_ID` env var to reuse an existing brand voice for consistent report styling.
- The 500/day limit resets at midnight UTC. Schedule batch jobs accordingly.
- Monitor Mavera credits at [Dashboard](https://app.mavera.io/settings/usage).

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<CardGroup cols={3}>
  <Card title="All Integrations" icon="plug" href="/integrations" />
  <Card title="SurveyMonkey API" icon="clipboard-list" href="https://developer.surveymonkey.com/api/v3/" />
  <Card title="Personas" icon="user" href="/features/personas" />
  <Card title="Focus Groups" icon="users" href="/features/focus-groups" />
  <Card title="Mave Agent" icon="brain" href="/features/mave-agent" />
  <Card title="Generate" icon="wand-magic-sparkles" href="/features/generate" />
</CardGroup>