FAQ: privacy, data accuracy, and analytics process

Your analytics questions answered

We’re not afraid to question the obvious. If you’ve wondered how sentiment analytics really works, or if you should trust the numbers, you’re in the right place. Here, we explain our methods and what sets us apart.

Why bother with sentiment?

We’ve all confused social media buzz for actual opinion. Our analytics go deeper, questioning the difference between noise and real shifts—so you get clarity, not just a pretty chart.

What happens to my data?

Privacy isn’t a checkbox. We treat every user’s data with care, anonymizing inputs and never selling your information to outside parties.

Are all sources trustworthy?

Not all sources are created equal. We check for bots, spam, and outlier events before using any public data in your reports.

Can I trust the findings?

Results aren’t set in stone. Social mood changes fast, and our team is always ready to rethink methods when new trends appear.

Frequently asked questions

How is my data kept private?

All personal data is anonymized and processed under strict privacy rules. We do not share user-specific information with third parties and follow Indian data protection standards.

How accurate are the reports?

No analytics can promise perfect accuracy. We compare new findings to historic trends, flag anything unusual, and always advise clients to consider multiple sources before acting.

Analytics terms

Glossary: social sentiment analytics

Social media analytics brings together language, numbers, and psychology. We’ve defined key terms to help you spot what sets our approach apart from basic metric-counting.

Impressions count

The total number of times a post is displayed to users, regardless of engagement. Useful for comparing visibility across campaigns or channels.

Metric

Sentiment score

A score representing the overall emotional tone of posts—positive, negative, or neutral—calculated using language models and reviewed for context.

Sentiment

Public data source

Any public channel or platform where data is collected for analysis. Our team reviews sources to avoid bias and filter out unreliable inputs.

Data source

Sentiment trend

A pattern or change in sentiment or engagement over time, often highlighted when there’s a significant shift from previous norms.

Trend

Anomaly detection

A method our analysts use to check if spikes or dips are genuine or caused by bots, spam, or outside manipulation.

Process

Sentiment dashboard

A summary of findings from analytics, often shown in a dashboard for easy review. Includes sentiment, trends, and source reliability.

Report

Engagement rate

Interactions such as likes, shares, and comments. Used to measure how users react to specific posts or trends over time.

Engagement

Hybrid analysis method

The unique blend of historic data, algorithm checks, and human review our team uses to generate reliable sentiment analytics.

Methodology