Start with unstructured data (customer support emails, call transcripts, feedback threads). Use AI to extract themes and root causes. Then validate with surveys. Build causal models to prove what changes will actually work. Track actions to business outcomes. All in one platform.
Here's what survey teams waste time doing today
Endless debates about what to ask, who to ask, and why
📧 Email + Calendar
Google "good employee survey questions", copy random templates, hope they work
🔍 Google + Word Doc
Fight with SurveyMonkey/Google Forms UI, manually add every question
📝 SurveyMonkey / Google Forms
Export emails from HR system, paste into survey tool, pray the link works
📧 Email blast
Send reminder emails. Beg departments to participate. 23% response rate.
⏳ More emails
Clean data, fix formatting, merge columns, remove duplicates
📊 Excel
Manually create charts. "Looks like people want better coffee?" Total guesswork.
📽️ PowerPoint
"Can you run a t-test? What's significant here?" Data team is swamped.
🧑🔬 SPSS / R / Python
Insights die in a deck. No follow-up. Same problems next year.
🗑️ Forgotten slide deck
From survey idea to actionable insights
(If the data scientist has time. Otherwise, you just make charts in PowerPoint and guess.)
Everything in one platform-from questions to proven outcomes
State your business problem. AI suggests what to measure and who to ask. Link to KPIs you're trying to impact.
→ Clear problem statement with metrics
Surveys + voice recordings + email intelligence. Sync support cases automatically. Combine multiple sources. One-click distribution with real-time tracking.
→ Raw data from all stakeholders
Automatic statistical tests. Fishbone diagrams. 5 Whys drill-down. AI identifies patterns and themes with confidence scores.
→ Evidence-backed root causes ranked by impact
AI suggests targeted actions based on root causes. Prove impact on KPIs. Cross-validate across data sources.
→ Prioritized action plan with statistical proof
Assign owners, set deadlines, document solutions. Upload KPI data to prove actual business impact. Monitor control limits.
→ Sustained improvements with measured outcomes
Complete DMAIC cycle: From problem to proven improvement
One platform for Define, Measure, Analyze, Improve, Control. Lean Six Sigma methodology meets modern analytics.
DMAIC: A structured, data-driven framework designed to identify root causes, eliminate variation, and ensure sustained improvements. Define your problem, Measure what matters, Analyze for insights, Improve with evidence, and Control to maintain gains.
By the time you get insights, the problem has evolved. Insights die in a deck.
Fast insights mean fast action. Track outcomes until completion. Measure real impact.
✅ StatQuestions:
❌ Traditional:
Word docs, meetings, guesswork
✅ StatQuestions:
❌ Traditional:
Email exports, manual sends, broken links
✅ StatQuestions:
❌ Traditional:
Excel pivot tables, data scientist queue, PowerPoint guesswork
✅ StatQuestions:
❌ Traditional:
Slide deck nobody reads, no follow-up
How most teams analyze customer support emails today-and what's possible instead
Read Cases One by One
8-10 hoursSpend hours reading Zendesk/Salesforce threads manually. Take notes in spreadsheet.
Categorize Themes Manually
4-6 hoursCreate categories in your head. Copy-paste snippets. "I think this is about billing?"
Count Things in Excel
3-4 hoursMake pivot tables. Count keywords. No statistical rigor. Pure guesswork.
Try to Find Patterns
2-3 hoursScroll through notes. "Feels like people are confused about pricing." No proof.
Make PowerPoint
2-3 hours"Here are some themes we saw." No confidence scores. No root causes.
Total Time: 19-26 hours
And you still don't know which issues actually matter or what causes them.
Sync Salesforce Cases Automatically
2 minutesOne click. AI reads every thread, extracts timeline, tracks promises.
AI Extracts Themes & Root Causes
30 secondsAutomatic theme clustering. Root cause identification with confidence scores.
Statistical Analysis Built-In
0 secondsSentiment trends, confusion scores, escalation risk-no Excel needed.
Cross-Case Pattern Detection
InstantAI finds "12 cases mention the same bug" automatically. You'd never spot this manually.
Generate Insights & Actions
1 minuteAI suggests what to fix based on statistical impact. Link to causal analysis.
Total Time: 4 minutes
Plus, you get statistical confidence, root causes, and actionable insights-not guesswork.
Timeline Narratives
"Customer asked for ETA 3 times over 5 days, never got answer. Confusion score: 85/100."
Promise Tracking
AI detects when agent says "we'll fix this by Friday" and tracks if it happened.
Sentiment Shifts
See exactly when customer went from neutral → frustrated. What triggered it?
Escalation Prediction
0-100 score: "This case will escalate unless you respond in 2 hours."
Root Cause Analysis
AI identifies systemic issues: "Documentation gap caused 18 similar cases this month."
Cross-Case Patterns
"12 enterprise customers mention the same export bug. Priority: Critical."
Before you ask a single survey question, understand what your customers are already telling you. Sync support emails, analyze call transcripts, process feedback threads. AI finds patterns you'd never see manually-then you validate them with targeted surveys.
Sync Salesforce cases automatically. AI reads every thread and tells you: when confusion started, what promises were made, which questions went unanswered, and where sentiment shifted.
Upload customer calls or employee interviews. AI transcribes, extracts themes, tracks sentiment changes, and identifies root causes with statistical confidence.
Analyze Unstructured Data
Sync support emails and call transcripts. AI identifies themes: "Response time," "billing confusion," "feature requests."
Validate with Targeted Surveys
AI suggests survey questions to test hypotheses. "Is response time the #1 driver of churn?" Survey 100 customers to confirm statistically.
Build Causal Models
Combine unstructured and survey data. Create fishbone diagrams showing root causes → intermediate effects → KPI impact. Statistical proof at every node.
Track Actions to Outcomes
Implement fixes. Monitor KPIs in real-time. Prove "Reducing response time from 4hrs → 2hrs decreased churn by 8% (p<0.01)."
Scenario: Sarah's dashboard export fails. She emails support 8 times over 5 days.
AI Analysis: Confusion score: 75/100. Escalation risk: 85%. Root cause: Known bug not communicated. 4 unanswered questions.
Action: Pattern found in 12 other cases. Survey enterprise customers about communication gaps. Build causal model: "Proactive bug disclosure reduces escalations by 40%."
Scenario: Michael reports duplicate billing charge. Resolved in 48 hours.
AI Analysis: Confusion score: 15/100. Sentiment: Improving. Promise fulfilled on time.
Insight: Effective handling pattern detected. Use this as training benchmark for support team. No survey needed-case demonstrates best practice.
Surveys + voice + email intelligence + causal trees. Everything you need to go from fragmented feedback to proven outcomes.
Start Your First SurveyNo credit card required • Full lifecycle included