AI-Powered Action

Analyse SMS Sentiment With AI

Automatically detect customer emotions in SMS messages. Route angry customers to priority support, identify happy customers for review requests, and track sentiment trends across your Australian business.

85-92%
Accuracy Rate
<2s
Analysis Time
3
Sentiment Types

What Is SMS Sentiment Analysis?

SMS sentiment analysis uses advanced AI to automatically understand the emotion behind customer text messages. Instead of manually reading and categorising every SMS, our AI instantly detects whether a customer is happy, angry, or neutralβ€”helping Australian businesses respond faster and more appropriately.

😊

Positive Sentiment

Detects happy, satisfied, and grateful customers. Perfect for requesting reviews, upselling products, or gathering testimonials.

HappyExcitedGratefulSatisfied
😠

Negative Sentiment

Identifies angry, frustrated, or disappointed customers. Route to senior support, offer compensation, or escalate immediately.

AngryFrustratedDisappointedWorried
😐

Neutral Sentiment

Detects informational, factual messages with no strong emotion. Handle with standard workflows and response times.

InformationalEnquiryFactualProfessional

How Sentiment Analysis Works in Zapier

DataFlows SMS integrates with Zapier to provide instant, AI-powered sentiment analysis for every SMS message your Australian business receives.

1

Customer Sends SMS

A customer texts your Australian business number with feedback, a question, or a complaint.

From: +61412345678
To: +61400123456
Message: "This is ridiculous! My order still hasn't arrived after 2 weeks!"
2

DataFlows Receives SMS

DataFlows SMS platform receives the message and instantly triggers your Zapier workflow via webhook (no polling delay).

3

AI Analyses Sentiment

The "Analyse SMS Sentiment With AI" action processes the message and returns detailed results.

sentiment: "negative"
emotion: "angry"
confidence: 0.92
tone: "urgent"
reasoning: "Customer expresses frustration about delayed order"
4

Take Action Based on Sentiment

Use Zapier filters and paths to route the conversation appropriately.

  • Negative β†’ Create urgent support ticket
  • Positive β†’ Request review or testimonial
  • Neutral β†’ Standard response workflow

Real-World Use Cases for Australian Businesses

See how Australian businesses use SMS sentiment analysis to improve customer satisfaction, increase reviews, and identify issues before they escalate.

Priority Support Queue for Negative Sentiment

Customer Support

Automatically route angry or frustrated customers to senior support agents for immediate attention.

Workflow Steps:

  1. Customer sends SMS: 'This is ridiculous! My order still hasn't arrived!'
  2. AI analyses sentiment β†’ Result: Negative (Angry, Confidence: 0.92)
  3. Filter: Only continue if sentiment = 'negative' AND confidence > 0.7
  4. Create urgent Zendesk ticket with priority: High
  5. Send Slack notification to @senior-support team
  6. Auto-reply: 'We're sorry! A senior agent will contact you within 15 minutes.'

Happy Customer Review Requests

E-commerce & Retail

Request reviews from satisfied customers while they're in a positive mood.

Workflow Steps:

  1. Customer sends SMS: 'Just received my order! Love it, thank you!'
  2. AI analyses sentiment β†’ Result: Positive (Happy, Confidence: 0.88)
  3. Filter: Only continue if sentiment = 'positive'
  4. Wait 5 minutes (gives them time to enjoy the product)
  5. Send SMS: 'So glad you love it! Mind leaving us a quick review? [link]'
  6. Track review completion in Google Sheets

Sentiment Dashboard for Australian Businesses

Analytics & Reporting

Track customer sentiment trends over time to improve products and services.

Workflow Steps:

  1. Every incoming SMS is analysed for sentiment
  2. Data is logged to Google Sheets: Date, From, Message, Sentiment, Emotion, Confidence
  3. Google Data Studio dashboard visualises trends
  4. Weekly report emailed to management
  5. Identify patterns: 'Delivery complaints spike on Fridays'
  6. Take action to improve service

VIP Customer Alert System

Hospitality & Luxury Retail

Alert managers immediately when VIP customers express dissatisfaction.

Workflow Steps:

  1. VIP customer (from premium contact group) sends SMS
  2. AI analyses sentiment β†’ Result: Negative
  3. Immediately send SMS to store manager: '⚠️ VIP Jane Smith unhappy: [message]'
  4. Create task in Asana for manager follow-up
  5. Log interaction in HubSpot CRM
  6. Auto-reply offering personal manager callback

Product Feedback Categorisation

Product Development

Automatically categorise product feedback by sentiment to prioritise improvements.

Workflow Steps:

  1. Customer sends product feedback via SMS
  2. AI analyses sentiment and categorises intent
  3. Positive feedback β†’ Add to testimonials database (Airtable)
  4. Negative feedback β†’ Create product improvement task (Trello)
  5. Neutral feedback β†’ Log for later review (Google Sheets)
  6. Product team receives weekly summary report

Why Australian Businesses Choose DataFlows SMS Sentiment Analysis

πŸ‡¦πŸ‡Ί Understands Australian English

Trained on Australian slang, idioms, and communication styles. Understands "mate", "no worries", and other Aussie expressions.

⚑ Instant Webhooks

Real-time analysis with no polling delays. SMS received β†’ Analysed β†’ Action taken in under 5 seconds.

πŸ“Š High Accuracy

85-92% accuracy rate with confidence scores. Filter by confidence to ensure reliable results.

πŸ”’ ACMA Compliant

Fully compliant with Australian SMS regulations and privacy laws (Privacy Act 1988).

πŸ’° Cost-Effective

No per-analysis charges. Included with your DataFlows SMS plan. Perfect for Australian small businesses.

πŸ”— 6,000+ App Integrations

Connect with Zendesk, Slack, HubSpot, Google Sheets, and thousands more via Zapier.

How to Set Up SMS Sentiment Analysis in Zapier

Step 1: Create Your Zap

  1. Log in to Zapier
  2. Click "Create Zap"
  3. Search for "DataFlows SMS" and select it as your trigger app

Step 2: Choose Your Trigger

  1. Select trigger event: "New SMS Received"
  2. Connect your DataFlows SMS account using your API token
  3. Get your API token from: https://sms.dataflows.com.au/developers/api
  4. Test the trigger with a sample SMS

Step 3: Add Sentiment Analysis Action

  1. Click "+" to add an action
  2. Search for "DataFlows SMS" and select it
  3. Choose action event: "Analyse SMS Sentiment With AI"
  4. Map the "Message" field to the incoming SMS content from Step 2
  5. Test the action to see sentiment results

Step 4: Route Based on Sentiment

  1. Add a Filter or Paths step
  2. Create different workflows for each sentiment:
    • Path 1 (Negative): sentiment = "negative" AND confidence > 0.7
    • Path 2 (Positive): sentiment = "positive"
    • Path 3 (Neutral): sentiment = "neutral"
  3. For each path, add appropriate actions (create ticket, send email, log to sheet, etc.)

Step 5: Test and Activate

  1. Send test SMS messages with different sentiments
  2. Verify each workflow path executes correctly
  3. Check confidence scores are within acceptable range
  4. Turn on your Zap to start automating!

Frequently Asked Questions

How accurate is the AI sentiment analysis for Australian English?

Our AI is trained on diverse English variants including Australian English. It achieves 85-92% accuracy in sentiment detection and understands Australian slang, idioms, and colloquialisms. The confidence score helps you filter out uncertain results.

What sentiments can the AI detect in SMS messages?

The AI classifies messages into three main sentiments: Positive (happy, satisfied, grateful), Negative (angry, frustrated, disappointed), and Neutral (informational, factual). It also provides emotion tags like 'angry', 'worried', 'excited', and tone indicators like 'urgent' or 'professional'.

Can I use sentiment analysis for SMS marketing campaigns in Australia?

Yes! Sentiment analysis is perfect for Australian SMS marketing. You can identify unhappy customers for retention campaigns, find promoters for referral programs, or segment audiences based on their emotional response to your messages.

What's the confidence score and how should I use it?

The confidence score (0.0 to 1.0) indicates how certain the AI is about the sentiment. We recommend only acting on results with confidence > 0.7. Low confidence (<0.6) should be routed to human review to avoid misclassification.

Does sentiment analysis work with SMS messages in different formats?

Yes! The AI works with standard SMS messages, long messages (concatenated), messages with emojis, abbreviations, and even messages with poor grammar or typos. It's designed to understand real-world customer communication.

How fast is the sentiment analysis?

Analysis is near-instant, typically completing within 1-2 seconds. Since DataFlows SMS uses instant webhook triggers (not polling), the entire workflow from receiving an SMS to analysing sentiment and taking action happens in under 5 seconds.

Can I analyse sentiment for bulk SMS responses in Australia?

Absolutely! Whether you receive 10 or 10,000 SMS responses to your Australian SMS campaign, each message is analysed individually in real-time. This is perfect for event feedback, product launches, or survey responses.

What happens if the AI can't determine sentiment?

If the AI confidence is very low or the message is ambiguous, you can set up a fallback workflow. Common approaches: route to human review, mark as 'neutral', or request clarification from the sender via automated SMS response.

Ready to Start Analysing SMS Sentiment?

Connect DataFlows SMS with Zapier and start understanding your customers' emotions automatically.