Perform sentiment analysis at scale with AI
How to use AI to understand sentiment from any text data
What is sentiment analysis and why is it valuable?
Think of Sentiment Analysis as a vibe-o-meter for any type of text-based data, whether a few words or hundreds of pages.
- What it lets you do: Determine positive, negative, or neutral sentiment, gauge customer satisfaction, and monitor brand reputation.
- Use cases: Support tickets, sales call transcripts, customer reviews, brand mentions, user interviews, and more.
- Impact on your business: Better customer service, more targeted marketing, better product<>user feedback loops, and improved efficiency
The Old Way: Why sentiment analysis was often a pipe dream
Previously, sentiment analysis was often out of reach for resource and time-constrained companies. It was:
- Expensive: You either had to pay for manual human tagging or clunky, costly specialized software.
- Time-consuming: You had to endure lengthy setup and model training times - weeks or years, not minutes.
- Accuracy: You were at the mercy of the quality and quantity of available data.
- Technical skills required: You needed expertise in machine learning and engineering - expensive and out of reach for most companies!
The New Way: Now anyone can easily perform sentiment analysis at scale
Introducing AirOps’ Sentiment Analyze - now you can quickly, scalably, and affordably run sentiment analysis on any of your text data:
Accessible: Requires no technical ability - if you can use Google Sheets, you can use Sentiment Analyze!
Use it anywhere:
- In AirOps' Web App
- In our Browser Extensions: Chrome/Firefox Extensions, VSCode Extension
- In your Google Sheet: AirOps custom Gsheet formula
- In your Data warehouse: User-defined SQL function (e.g., Snowflake)
- Via API
Scalable: Analyze 1 to 1,000,000+ tasks without compromising performance or accuracy.
Start free today: Get started today and experience the magic with no upfront investment!
