Paste a support email or chat message and get an instant tone analysis — professionalism, friendliness, empathy scores plus actionable suggestions.
Minimum 5 words for analysis. Your text is analyzed locally — nothing is sent to any server.
Paste a message to analyze its tone...
Analysis based on linguistic patterns, sentiment markers, and readability metrics. Best for customer support emails and chat messages.
The tone checker uses linguistic signal analysis to evaluate your support messages across six dimensions that research has shown to be most predictive of customer satisfaction outcomes:
Each dimension is scored 0–100 based on pattern matching against sentiment lexicons, readability metrics, and linguistic markers. The analyzer also checks for common anti-patterns: blame language, passive-aggressive phrasing, unnecessary jargon, and missing next steps.
Tone consistency is one of the biggest advantages of AI-powered customer support. While human agents vary in tone based on workload, mood, and experience, an AI chatbot delivers the same calibrated tone in every interaction. Use this tool to audit your current tone, then set the bar for what your chatbot should match.
Tone directly impacts customer satisfaction, resolution rates, and brand perception. Research shows that customers who perceive a support interaction as empathetic are 3x more likely to remain loyal — even if the outcome isn't what they hoped for. A single dismissive or overly formal response can escalate a minor issue into a complaint. Consistent, appropriate tone across your team builds trust and reduces churn.
The analyzer evaluates your text across six dimensions: professionalism, friendliness, empathy, clarity, confidence, and urgency. It detects linguistic signals like formal markers ('please be advised,' 'per our policy'), empathy words ('I understand,' 'that must be frustrating'), hedging language ('maybe,' 'I think'), and sentiment patterns. Each dimension receives a score from 0–100, and the tool provides specific suggestions for improvement.
The ideal tone varies by context, but the best-performing support teams consistently score high on empathy (70+) and clarity (80+) while maintaining moderate professionalism (60–80). Overly formal language creates distance; overly casual language undermines trust. The sweet spot is 'professional warmth' — clear, competent communication with genuine empathy. For escalations and complaints, empathy should be the dominant tone signal.
Three strategies work best: (1) create a tone guide with before/after examples for common scenarios, (2) use this tool to audit a sample of responses weekly and coach on patterns — not individual messages, and (3) build approved response templates that encode your ideal tone. AI chatbots maintain perfect tone consistency by default, which is why many teams use them for first-response while reserving human agents for nuanced conversations.
In text-only channels like email and chat, tone carries outsized weight because there's no body language or vocal inflection to provide context. The same factual information — say, a refund denial — delivered in a cold tone vs. an empathetic tone produces measurably different satisfaction scores. Studies of support interactions consistently show that perceived empathy and clarity matter more than the specific words used, which is why tone-checking before sending is so valuable.
Join businesses that have automated support, captured more leads, and cut response times to zero — no code required.
Free forever on Starter. No credit card required.