Voice to Text for Data Analysts
You see patterns in the data that others miss, but explaining them takes forever. Writing up findings, annotating dashboards, and responding to stakeholder requests pulls you out of analysis mode. Blurt lets you speak your insights while they're fresh. Hold a button, explain what you found, release. Text appears in Tableau, Excel, Slack, email — wherever you need it. Your hands stay on your analysis tools. Your insights get documented before you forget the nuances.
The Typing Problem
Documenting insights before you forget the details
You just found a fascinating trend in the quarterly data. The correlation is clear in your head — you could explain it in 30 seconds to a colleague. But typing up the full analysis with context takes 15 minutes. By then, you've lost some of the nuance. The written version never quite captures what you saw so clearly moments ago.
Explaining technical findings to non-technical stakeholders
The VP wants to know why revenue dipped in Q3. You know the answer involves seasonality, a one-time customer churn event, and a change in how returns are recorded. Typing an email that explains all this without confusing them takes 20 minutes of careful word choice. You could explain it verbally in 2 minutes, but you need a written record.
Annotating dashboards with meaningful context
Your Tableau dashboard looks great, but the numbers need context. That spike in March? One-time promotional event. The dip in December? Expected seasonality. Each annotation requires you to stop analyzing, switch to text mode, type carefully, then try to remember where you were. Ten annotations later, an hour has vanished.
Writing methodology notes that nobody reads
You should document your data cleaning process. You should explain why you excluded certain outliers. You should note your assumptions. But after building the model and running the analysis, typing up methodology notes feels like punishment. So the documentation stays sparse, and three months later even you can't remember why you made certain choices.
Responding to ad-hoc data requests during deep analysis
You're deep in a complex analysis when a Slack message pops up: 'Quick question — what was our churn rate last month?' You know the answer. But typing a clear response with the right caveats pulls you completely out of your analytical flow. That 'quick' reply just cost you 10 minutes of regained focus on your actual project.
How It Works
Blurt works in every app data analysts use — Tableau, Excel, SQL clients, Slack, email, Notion. Anywhere you can put a cursor.
Hold your hotkey
Press your chosen shortcut while looking at your data. A small indicator shows Blurt is listening.
Explain your insight
Describe the trend, explain the methodology, or answer the stakeholder question. Talk naturally — Blurt handles punctuation.
Release and done
Text appears at your cursor. In your dashboard annotation, your email reply, your methodology doc. No copying, no extra steps.
Real Scenarios
Documenting analysis summaries while insights are fresh
You just finished a cohort analysis that reveals something important: customers acquired through referrals have 40% higher lifetime value. Instead of typing up your findings, hold the button and explain what you found: 'Referral customers show significantly higher LTV driven primarily by lower churn in months 3 through 6. Recommend increasing referral bonus budget by 25% based on projected ROI.' Your analysis summary is written in 15 seconds while the insight is crystal clear in your mind.
Writing stakeholder update emails
The marketing director wants a weekly metrics update. Instead of dreading the typing, hold the button and talk through the numbers: 'This week we saw a 12% increase in conversion rate, primarily driven by the new landing page test. Traffic was flat but quality improved based on time-on-site metrics. One concern is the slight uptick in bounce rate on mobile that we should monitor.' Email drafted in 30 seconds. Send and get back to analysis.
Creating methodology documentation
You need to document how you built this predictive model for the next analyst. Hold and explain your process: 'Started with the raw transaction data from the warehouse. Excluded refunds and test accounts. Applied log transformation to the revenue column due to heavy right skew. Used 80-20 train-test split with stratification on customer segment.' Methodology documented before you forget the details. Future you will be grateful.
Adding context to dashboard visualizations
Your executive dashboard needs annotations. Click the annotation field, hold your button: 'The March spike reflects the one-time enterprise deal with Acme Corp. Excluding this outlier, underlying growth was 8% month-over-month, in line with projections.' Context captured in seconds. Stakeholders understand the numbers. No more confused Slack messages asking about anomalies.
Responding to ad-hoc data requests
A product manager Slacks: 'Do you have the conversion funnel numbers for last quarter?' You pull them up and hold the button: 'Q4 funnel was landing page at 100%, signup at 23%, activation at 68% of signups, and conversion to paid at 12% of activated users. This is up 3 points from Q3, primarily from the onboarding flow improvements.' Request handled in 20 seconds without derailing your analysis work.
Writing data dictionary entries
The data dictionary needs definitions for the new columns you added. Instead of tediously typing each one, talk through them: 'Customer health score is a composite metric ranging from 0 to 100, calculated as a weighted average of login frequency, feature adoption, and support ticket volume. Updated weekly on Sunday nights. NULL values indicate customers with less than 30 days of activity.' Documentation that actually gets written.
Preparing findings for presentations
You need speaker notes for tomorrow's quarterly review. While looking at each slide, hold the button and explain what you'll say: 'This chart shows our year-over-year growth by segment. Key callout is that enterprise grew 45% while SMB was flat. This validates our strategy shift but we need to discuss whether to increase SMB investment or double down on enterprise.' Presentation prep done in minutes, not hours.
Why data analysts choose Blurt over built-in dictation
| Blurt | macOS Dictation | |
|---|---|---|
| Activation | Single hotkey, instant start | Click microphone icon or double-tap control |
| Speed | Text appears in under 500ms | 2-3 second delay before transcription |
| Technical terms | Handles SQL, metrics terminology well | Struggles with data jargon and acronyms |
| Reliability | Consistent accuracy across sessions | Often fails silently or mishears numbers |
| Number handling | Accurately transcribes percentages and figures | Frequently confuses similar-sounding numbers |
Frequently Asked Questions
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