Brand Sentiment: What It Is and How To Measure It

Brand sentiment: what it is and how to measure it

Learn what brand sentiment means, how it is scored, and how to analyze it in your own survey data to guide smarter brand decisions.

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Summary:

Definition: Brand sentiment is the current emotional tone (positive, negative, or neutral) expressed by customers. Unlike perception or reputation, it reflects immediate feelings that shift quickly based on recent experiences.
Measurement: Sentiment is scored by classifying feedback from reviews, social posts, and surveys. Tracking the difference between positive and negative mentions against a baseline or competitors reveals meaningful trends.
Strategic Value: Combining public social listening with your own survey responses creates a representative, actionable signal. This helps teams identify root causes of shifts and implement targeted improvements.

Brand sentiment is the emotional tone behind what people say about your brand, whether that tone is positive, negative, or neutral. It is the feeling underneath the feedback, distinct from whether someone simply recognizes your name or ranks you against competitors.

Marketers track brand sentiment because raw awareness numbers do not tell you how people feel. A brand can be widely known and still carry a bruised reputation.

Sentiment fills that gap by capturing the emotional charge in reviews, social posts, support tickets, and survey responses, giving you an early signal before it shows up in sales or churn.

Most guidance on this topic treats sentiment tracking as a social listening exercise: scrape mentions, tag them positive or negative, and watch the trend line.

That approach works, but it only sees what people say in public. It misses the sentiment sitting inside your own survey data, in the open-ended comments customers leave when you ask them directly. This article covers both, with a closer look at how to put your own survey verbatims to work.

What is brand sentiment?

Brand sentiment is the aggregate emotional attitude, positive, negative, or neutral, that customers and prospects express toward a brand across their comments, reviews, and responses.

It answers a narrower question than most brand metrics: not "do people know us" or "what do people think we stand for," but "how do people feel when they talk about us right now."

That distinction matters because brand sentiment, brand perception, and brand reputation get used interchangeably in casual conversation, even though they measure different things.

Term	Definition
Brand perception	The broader set of beliefs, associations, and mental images people hold about your brand. It includes what they think you are good at, who they think you serve, and how they picture your product. Perception is largely stable and shifts slowly.
Brand reputation	How your brand is regarded over time, often shaped by track record, media coverage, and word of mouth. Reputation is cumulative and reflects history.
Brand sentiment	The emotional read at a given moment. It moves faster than perception or reputation because it reacts to recent experiences: a product launch, a price change, a customer service interaction, a news cycle.

Think of it this way:

Perception is what people believe about you
Reputation is what people have come to expect from you
Sentiment is how people feel about you right now

A brand can hold a strong long-term reputation while experiencing a temporary dip in sentiment after a rough product update, and tracking sentiment separately is how you catch that dip before it hardens into a perception problem.

How brand sentiment is scored

Sentiment scoring starts with classification. Each comment, review, or open-ended response gets tagged as positive, negative, or neutral, either by a human reader or, more commonly at scale, by a machine learning model trained on language patterns.

From there, teams roll the classifications into a single sentiment score so the metric is easy to track over time. A common formula is:

Sentiment score = (percentage of positive mentions) minus (percentage of negative mentions)

Brand sentiment score example

A brand with 60 percent positive mentions and 15 percent negative mentions would land at a sentiment score of positive 45.

Some teams simplify further and report net sentiment as a ratio of positive to negative mentions, while others weight recent mentions more heavily so the score reflects current mood rather than a flat historical average.

Brand sentiment score interpretation

The score itself is only useful in context.

A sentiment score of positive 20 might be strong for a category known for friction, like insurance or telecom, and mediocre for a category where customers rarely have anything negative to say.

Track your own score against your own baseline and against direct competitors in your category, and treat sudden swings, in either direction, as the real signal worth investigating.

Social listening

Most sentiment tools point a scraper at public channels: social media mentions, review sites, forums, and news coverage. This is social listening, and it has real strengths. It is passive, it captures unprompted opinion, and it can surface a crisis in near real time.

It also has real limits.

Sample bias. People who post publicly about a brand tend to be at the extremes, either delighted or furious. The quiet middle rarely shows up.
No context. A scraped comment tells you someone is unhappy. It rarely tells you why, or which product, team, or moment caused it.
No control over who is heard. You cannot ask a follow-up question, and you cannot guarantee the sample reflects your actual customer base rather than whoever happens to be loudest online.

Open-ended survey questions

Survey open-ended responses solve a different problem.

When you ask your own customers a direct question, such as "what's the one thing we could do better," you get sentiment tied to a known respondent, a known context, and a known moment in their relationship with your brand.

You control the sample, the timing, and the question, which means the sentiment you extract is more representative and easier to act on.

Social listening vs. surveys: which is better?

This is not a case for choosing one over the other.

Social listening tells you what the broader market is saying, unprompted.
Survey open-ends tell you what your actual customers and prospects mean, in their own words, when you ask them directly.

The two are complementary. A first-party sentiment signal from your surveys gives you a controlled baseline you can trust, while social listening adds the wider, unsolicited view.

Pairing them closes the gap that either one leaves on its own, and it is why a brand perception survey is a natural home for open-ended sentiment questions alongside your rating scales.

How to analyze sentiment in your own survey data

Turning open-ended survey responses into a usable sentiment signal does not require a research team. Here is a straightforward process.

Add at least one open-ended question to every brand survey. A single prompt, such as "what comes to mind when you think of our brand," generates far richer sentiment data than a rating scale alone. Ratings tell you the score. Open text tells you the reason behind it.
Run the responses through sentiment analysis. The AI-powered text analysis available in SurveyMonkey reads open-ended responses and automatically classifies each one as positive, neutral, or negative, then surfaces the specific words and phrases driving each classification so you are not left guessing at the raw comment volume. That level of detail is what a general brand tracking survey needs to move past a single blended score.
Segment sentiment by respondent group. Break results down by customer tenure, region, product line, or persona. A brand that looks fine on average can be hiding a sharply negative segment that a blended score would never reveal.
Compare sentiment against your quantitative brand metrics. Look at sentiment alongside awareness, consideration, and intent-to-purchase questions from the same survey wave. A drop in sentiment that lines up with a drop in purchase intent is a stronger signal than either metric alone.
Track sentiment on a consistent cadence. A single survey wave gives you a snapshot. Repeating the same core questions weekly, monthly, or quarterly turns sentiment into a trend line you can act on before a small dip becomes a lasting perception problem.

Turning sentiment shifts into action + example

A sentiment score only earns its keep when it changes what your team does next. Treat a sustained negative shift as a trigger for a specific set of actions, not just a number to report.

Read the open-text comments driving the shift before you react. The score tells you sentiment moved. The verbatims tell you whether the cause is a product issue, a pricing change, a support experience, or a competitor campaign.
Validate the shift against a second data source. Confirm what your survey sentiment is showing against your social listening feed, support ticket themes, or churn data before committing budget to a fix.
Loop the finding back to the team that owns the cause. Sentiment tied to a support interaction goes to the customer experience team. Sentiment tied to a campaign goes to marketing. A sentiment score with no owner rarely leads to change.
Re-measure after you act. Run the same survey question again after a fix ships or a campaign launches, so you can attribute the sentiment recovery, or lack of one, to a specific decision.

Brand sentiment example

Elephant Insurance offers a useful example of closing the feedback loop.

The auto insurance provider struggled with brand tracking data that skewed toward an older population, which limited how confidently it could act on the numbers.

After implementing SurveyMonkey Audience to leverage its advanced demographic filtering, the team moved to weekly survey cycles.

That shift to weekly survey cycles provided real-time visibility into consumer sentiment, allowing the team to validate a regional billboard campaign through measurable increases in aided awareness and a significant spike in intent to quote.

The lesson is not just that sentiment data existed, it is that a faster measurement cadence let the team connect sentiment directly to a specific marketing decision.

If you want a structured way to start building that same feedback loop, the Brand Health Program from SurveyMonkey is built to track sentiment, awareness, and perception together on a recurring cadence rather than as one-off snapshots.

Frequently asked questions

What is brand sentiment?
How do you measure brand sentiment?
What is a good brand sentiment score?
What is the difference between brand sentiment and brand perception?

Start tracking sentiment where your customers already talk to you

Sentiment is most useful when you can trace a shift back to a cause and a fix. Pairing social listening with sentiment analysis of your own survey open-ends gives you both the wide view and the controlled, first-party signal you can act on with confidence.

Explore the Brand Health Program to track sentiment on a recurring cadence, or start with the brand perception survey template to add open-ended sentiment questions to your next brand wave.