Brand Voice Style Guide

Voice Overview

Core Attributes:

1. Problem-First Pragmatism: Lead with pain points your audience lives daily, then pivot immediately to solutions
2. Data-Backed Confidence: Use specific metrics and research to establish authority without bragging
3. No-BS Directness: Short, declarative sentences that cut through corporate speak
4. Empathetic Efficiency: Acknowledge customer struggles without dwelling—move quickly to actionable fixes

Voice Temperature: Warm-neutral. Friendly but focused. Professional without being stuffy. Zero tolerance for fluff.

Voice Personality

If this brand were a person: A technical consultant who’s seen your exact problem 500 times before. Doesn’t judge you for the mess—just rolls up their sleeves and shows you the fix. Brings receipts (data) to every conversation. Talks like a helpful colleague, not a salesperson.

What we sound like:

• The engineer who makes complex tools feel simple
• Your coworker who actually reads the analytics reports
• The implementation partner who’s already solved your problem

What we DON’T sound like:

• Aggressive sales pitch with exaggerated claims
• Academic whitepaper drowning in jargon
• Overly casual “startup bro” trying too hard to be relatable

Do’s and Don’ts

DO:

Lead with customer pain, backed by data:

• “After analyzing 10,000 customer support tickets, we found something surprising: 78% of issues stem from data sync problems.”
• NOT: “We have extensive experience with data synchronization challenges.”

Use second-person direct address:

• “You’re probably spending too much time on spreadsheets.”
• NOT: “Many businesses struggle with spreadsheet management.”

Keep sentences punchy and declarative:

• “Stop wasting time on manual data entry.”
• NOT: “Organizations should consider reducing time spent on manual data entry processes.”

Use contractions and conversational language:

• “We get it—we’ve been there.”
• NOT: “We understand the challenges because we have experienced them ourselves.”

Quantify impact with specifics:

• “We’ve helped 500+ companies save 40% on operational costs.”
• NOT: “We help companies significantly reduce costs.”

Name the problem directly:

• “No more copy-paste nightmares. No more formula errors.”
• NOT: “Eliminate common data management challenges.”

DON’T:

Use corporate buzzwords or vague language:

• AVOID: “leverage synergies”, “best-in-class”, “robust solution”, “paradigm shift”
• USE: “use”, “best”, “reliable tool”, “change”

Bury the lede with setup:

• AVOID: “In today’s fast-paced business environment, organizations face mounting pressure to…”
• USE: “Stop wasting time on manual data entry.”

Hedge or soften claims unnecessarily:

• AVOID: “This could potentially help reduce time spent on tasks.”
• USE: “Automates what takes your team hours into minutes.”

Vocabulary Guide

Words/Phrases We Embrace:

Problem words: wasting time, spending too much time, nightmares, errors, problems
Solution words: automates, fix, simpler, tool, platform, works
Evidence words: after analyzing, found, we’ve helped, [specific numbers]
Empathy phrases: “We get it”, “we’ve been there”
Transition phrases: “Here’s how it works”, “The fix is simpler than you think”, “That’s why we built…”
Direct address: you, your, you’re

Words/Phrases We Avoid:

Corporate jargon: synergies, leverage, ecosystem, paradigm, cutting-edge, revolutionary, innovative (overused), disruptive
Weak qualifiers: perhaps, possibly, might, could potentially, may help
Academic distance: organizations, entities, stakeholders, constituents
Feature-first language: “Our solution offers…”, “Featuring…”, “Powered by…”

Sentence Structure Patterns

Pattern 1: Problem Statement (Command)
Template: “[Action verb] [painful task]. Our [tool/platform] [specific benefit].”
Examples:

• “Stop wasting time on manual data entry. Our platform automates what takes your team hours into minutes.”

Pattern 2: Empathetic Recognition
Template: “You’re probably [doing painful thing]. We get it—we’ve been there.”
Examples:

• “You’re probably spending too much time on spreadsheets. We get it—we’ve been there.”

Pattern 3: Data Hook + Insight
Template: “After analyzing [number] [things], we found something surprising: [% or stat] [insight]. The fix is simpler than you think.”
Examples:

• “After analyzing 10,000 customer support tickets, we found something surprising: 78% of issues stem from data sync problems.”

Pattern 4: Negative Repetition (Emphasis)
Template: “No more [problem]. No more [related problem].”
Examples:

• “No more copy-paste nightmares. No more formula errors.”

Quick Writer Checklist

Before publishing, verify:

• Problem-first test: Does it open with a pain point or command?
• Data test: Specific numbers included (not just percentages—show scale)?
• “You” test: Direct address used at least once in opening?
• Simplicity test: No sentence over 20 words (aim for 6-12)?
• Fluff test: Zero corporate buzzwords or hedge words?
• Conversational test: Contractions used naturally?
• Clarity test: Could a busy executive skim and get the point in 10 seconds?
• Action test: Clear next step stated plainly?

Sample Rewrites

Example 1: From Generic to On-Brand

Before (off-brand):
“Our innovative platform leverages cutting-edge automation technology to help organizations optimize their data management workflows.”

After (on-brand):
“Stop wasting time on manual data entry. Our platform automates what takes your team hours into minutes.”

What changed: Removed buzzwords, led with problem, made it second-person, quantified benefit.

Example 2: From Hedged to Confident

Before (off-brand):
“Our solution could potentially help reduce the time your team might spend on spreadsheet tasks.”

After (on-brand):
“You’re probably spending too much time on spreadsheets. We get it—we’ve been there. That’s why we built a tool that does the heavy lifting for you.”

What changed: Removed hedging, added empathy, made it conversational with contractions.

Analysis Summary

Samples analyzed: 3 content pieces
Total word count: 75 words
Average sentence length: 6.8 words (Very concise, punchy style)
Contraction frequency: 2 instances
Direct address rate: 45.5%
Voice consistency score: 51%