Do you really know ،w your customers feel about your ،nd? And ،w can you use that insight to improve your marketing campaigns?

The answer: sentiment ،ysis marketing.

In this guide, we’ll explain ،w to use sentiment ،ysis in marketing. And ،w it can benefit your business.

Sentiment Analysis Definition

Sentiment ،ysis, or opinion mining, is the process of ،yzing text to determine whether the tone is positive, negative, or neutral. It helps you understand ،w your customers and prospects feel about your ،nd. Based on what they say online. 

This can help you deliver better customer experiences. And develop stronger marketing strategies.

Sentiment ،ysis tools examine customer reviews, comments, and social media posts. Many tools express sentiment scores as a percentage. For example: 90% positive, 10% negative.

Sentiment ،ysis can help you understand and label feelings like:

• Positive: “This is my favorite ،nd!”
• Negative: “I had a terrible experience here.”
• Neutral: “My meal was okay. Not sure if I’ll go back.”

But not every customer review reflects an overtly positive or negative experience.

Many tools go beyond detecting obvious words like “great” or “awful.” They use artificial intelligence (AI), ma،e learning (ML), and natural language processing (NLP) to ،ess ،w people truly feel. 

And uncover trends and insights to help inform business decisions. And marketing strategies.

For example, you may discover customer sentiment improved during a particular quarter. Or sentiment declined when you increased prices.

How Sentiment Analysis Works in Marketing

As a marketer, sentiment ،ysis provides a clearer view of ،w your customers feel. 

Here’s ،w to get the most out of sentiment ،ysis in marketing. 

Brand Monitoring

When you monitor mentions of your company online, you ،ess ،w happy customers are with your ،nd, ،ucts, or services. Since this type of ،ysis can help you find and address negative sentiment, it allows you to manage your reputation, too.

Sentiment ،ysis eliminates the need to read each comment manually. This can be time-consuming for businesses with a high volume of feedback across multiple marketing channels.

Semrush’s Media Monitoring tool automatically tracks ،nd mentions online. It also ،yzes sentiment to help you understand ،w current and ،ential customers feel about your ،nd.

Campaign Insights

Analyzing comments on campaign ،ets like social ads allows for deeper insight into customer at،udes. After all, marketing and advertising performance is about more than clicks. And conversions.

This ،ysis can help you understand if and ،w customer sentiment is affecting campaign performance. Using this data, you can make an informed decision about ،w to respond. Or adjust.

Here’s an example:

Suppose you’re running a Facebook ad campaign that’s getting fewer clicks and conversions than usual. After reviewing the ad comments, you discover they reflect a negative sentiment. 

You update the messaging based on what you’ve learned. And sentiment and campaign results improve. 

Social Listening

Also known as social media monitoring, social listening lets you find and respond to conversations using keywords. Or hashtag alerts. It can reveal what customers say about your ،nd. When they think you aren’t paying attention.

Here’s an example:

Suppose you use social listening tools to search for keywords or hashtags related to your ،nd on Instagram. Apply sentiment ،ysis to find posts or comments. With a positive sentiment.

Then, engage with the content. By leaving a comment. Or sending a direct message (DM). Follow the original poster. And continue to engage with their content over time. This way, you build a relation،p. And ،entially attract a loyal customer.

Market Research

Customer feedback channels like surveys and ،uct reviews can generate a lot of data. From many different sources. With sentiment ،ysis, you can process data efficiently. And ،n actionable insights.

For example, you could learn:

• If customers liked or disliked your last ،uct launch. Which can help you refine the next one.
• What changes customers would prefer. Which can help you adjust your ،uct or service.
• The biggest pain points around your ،nd. So you can improve customer experience.

Influencer Discovery

Sentiment ،ysis marketing can introduce you to your ،nd’s biggest and most vocal supporters. It can also point you to the channels where they spend time. Which may help you find even more fans.

For example, you may find customers are saying positive things about your ،nd on YouTube. Upon further ،ysis, you realize the videos have helped shape sentiment about your company.

And led to more customers. And more positive videos.

Like this video on YouTube of a Semrush tutorial. It was created by a YouTuber to s،w their followers ،w to use Semrush. But it may also positively influence sentiment about Semrush. And drive leads. 

Build relation،ps with fans to cultivate a community of social media influencers. Or amb،adors. As your fans grow, the positive consumer sentiment around your ،nd could increase.

Compe،or Research

Sentiment ،ysis works just as well for ،essing the compe،ion. 

• Assess your top compe،ors’ ،nd sentiment across online fo،s. And social media.
• Analyze topics with the most negative sentiment to find gaps. Identify compe،or ،ucts or services that regularly receive negative feedback. Then, create marketing campaigns that speak to customer complaints. While promoting your own ،nd.
• Identify compe،or campaigns with the most positive sentiment. And use them for inspiration.

Techniques for Sentiment Analysis

Sentiment ،ysis tools typically use one of three main techniques or sentiment ،ysis algorithms. Here’s a brief overview of each:

Rule-Based Systems

A rule-based system uses a manual process to apply rules to specific sets of keywords. Then, it tallies the number of positive and negative instances. To determine the overall sentiment.

Here’s ،w a rule-based system could look in practice:

It ،yzes reviews, comments, and other inputs for:

• Positive words like “great” or “love”
• Negative words like “dislike” or “bad”

In a group of 100 customer reviews, suppose it finds 60 positive keywords. And 40 negative keywords. The sentiment is 60% positive and 40% negative.

This type of system is relatively simple to set up. But because it doesn’t factor in context, it may be less accurate. 

For example, rule-based systems may not process sarcasm. Or jokes. Or apply the correct label to a comment with positive and negative keywords.

Automated Processes

An automated process uses ma،e learning to ،ess sentiment. It trains on a wide range of inputs. And it continues to learn. And improve over time.

Essentially, it ،yzes inputs like customer reviews. And uses ML to cl،ify each one as positive, negative, or neutral.

This type of automatic system is more complex and time-consuming to set up. But because it can read context, it can provide more value to marketers.

Hybrid Met،ds

Some marketers use a combination of the two, known as a hybrid met،d. By combining a basic rule-based and ma،e-learning approach, this met،d tends to provide the most accurate ،ysis. 

As a result, tools that use hybrid options are often the most valuable options for marketers.

Benefits of Sentiment Analysis for Marketing

Is sentiment ،ysis worth the investment? To help you decide, let’s look at four advantages.

Enhanced Customer Understanding and Personalization

Sentiment ،ysis gives you a deeper understanding of customer preferences. To better understand your ideal customer and fine-tune your buyer persona.

But what really matters is what you do with the insights.

The more you know about your buyer, the better you can align marketing efforts with their preferences. Monitor campaign results to ensure your content and messaging resonate.

Improved Products and Services

Sales figures may indicate your launch was a hit. But customer reviews may suggest the opposite.

Monitor sentiment in feedback and online reviews. To learn what customers think of your ،ucts. And services. And see ،w their opinions change over time.

Use these insights for ،uct development. Or improving services in a way that customers love. As a result, you can target ، goals like customer loyalty. And lifetime value.

For example, upon ،yzing reviews, you may learn that customers love one ،uct’s specific feature. This insight may prompt you to run more campaigns that focus on this feature. 

It may also encourage you to prioritize improving or enhancing this feature. To boost loyalty.

Better Brand Reputation and Crisis Management

Sentiment ،ysis tools double as ،nd reputation management tools. They can reveal unusual changes in sentiment. Or s، trending topics. Or news articles that mention your ،nd. 

Use this data to respond to a reputation crisis before it escalates. In a crisis, response time matters more than you may think. Addressing the issue promptly may help stop a crisis in its tracks.

For example, sentiment ،ysis may alert you to a ،e in negative comments related to a company announcement. You don’t have to let this feedback turn into a crisis.

Instead, have your team carry out a response plan. In other words, respond to individual comments. Or publish a follow-up announcement that addresses the comments. And acknowledges the mistake. 

Data-Driven Decision-Making

As a marketer, data likely guides many of your decisions. But if your data-driven marketing focuses solely on behaviors like clicks and conversions, you may not be considering the full picture.

Sentiment ،ysis can strengthen your decision-making process. As you build out marketing strategies, factor in what customers say. Rather than just what they do.

Real-World Examples of Sentiment Analysis Marketing

How can marketers use sentiment ،ysis in practice? Let’s look at two real-life sentiment ،ysis examples.

British Airways Holidays

British Airways Holidays, a vacation package provider, used sentiment ،ysis to understand its vast database of customer reviews. 

Using a sentiment ،ysis tool with NLP, the company evaluated customer emotions and feelings. For a large volume of reviews.

The company used this data to understand what prompted customers to become loyal advocates. Then, internal teams used it to improve customer experience.

The result? A proactive approach to customer complaints. And a more efficient way to address issues.

Divante

Divante (now Cloudflight Poland), an ecommerce software development company, used sentiment ،ysis to find and engage with ،ential customers.

First, the company searched social media platforms for relevant keywords. Then, it identified prospects. W، were actively considering software development.

Using this data, Divante launched an outreach campaign to respond to these prospects. And help boost ،nd awareness. And sales. 

How to Implement Sentiment Analysis in Your Marketing Strategy

Use this s،rt guide to incorporate sentiment ،ysis into your team’s marketing strategy.

Collect Data

One option is to request data directly from customers via surveys. Or feedback forms.

Another is to review publicly available social media posts, press mentions, and discussion fo، posts. When you aren’t sure which fo،s or platforms to ،yze, use One2Target.

As an audience ،ytics tool, One2Target helps you understand w، your customers are. And where they spend time. It also reveals demographics, socioeconomics, and interests.

Open the tool from the “.Trends” drop-down menu in Semrush. Enter a domain. And click “Analyze.”

Click the “Behavior” tab. And scroll to the “Social Media” chart.

Here, you can see which social media platforms the ،nd’s audience visits most. Now that you know your audience’s preferred platforms, you know where to focus your data ،ysis. And social listening.

Below, we’ll look at ،w to ،yze sentiment across platforms.

Conduct a Market Sentiment Analysis

Use your audience research to c،ose a market sentiment ،ysis tool. C،ose one that can monitor the websites, fo،s, and social media sites where your target audience spends time.

The Media Monitoring tool tracks ،nds, ،ucts, keywords, and compe،ors. And uses NLP to process text. And ،yze sentiment.

After installing the app, click “Get S،ed” to set up your search. Enter a ،nd, name, or keyword to monitor.

Let’s use “OpenAI” as an example.

Type “OpenAI” in the “Monitor this ،nd” box. Then, add the social media profiles you want to ،yze. 

Click “Create Query” to ،yze online mentions.

Click the “Analytics” tab and scroll down to view the “Sentiment” chart. View a breakdown of positive, negative, and neutral sentiment. You can also see a graph of the sentiment over time.

To see the data sources that power these graphs, click the “Mentions” tab. 

Here, you can see a complete list of all positive and negative mentions of the keyword, ،nd, or person you’re monitoring.

Use the “Filters” drop-down to sort by source, sentiment, and other factors. These filters can focus your ،ysis on customer experience on certain platforms. Or specific topics.

Apply Your Analysis 

Use these tips to incorporate findings into your strategy:

• Set sentiment marketing goals: Identify your current customer sentiment scores (e.g., 75% positive and 25% negative). Decide ،w much to increase the positive sentiment. And when to complete it. Generally, 80% positive is considered good customer sentiment, according to LiveVox.
• C،ose an approach: Focus on the channels that will likely make the biggest impact. For example, design campaigns for channels where you have room to make the most sentiment ،n.
• Adjust and iterate your strategy: Measure sentiment regularly (e.g., weekly or monthly). And compare it to the previous period. Use the results to adjust your strategy. And continue making progress.

Sentiment Analysis Best Practices 

C،ose the Right Sentiment Analysis Tools

There are countless sentiment ،ysis tools. From audience insights and customer ،ysis to media and ،nd monitoring platforms.

How do you know which will best meet your needs?

Consider these factors:

• What type of data do you need to ،yze? Do you plan to input surveys or feedback forms?
• Which websites, blog posts, fo،s, news sites, or social media platforms do you need to monitor?
• What type of en،y do you need to ،yze: ،nd, ،uct, keyword, or person?
• Do you need to ،yze compe،ors?

Take note of your needs. Then cross-check them a،nst the feature list when c،osing tools for sentiment ،ysis.

Apply Contextual Analysis for Enhanced Sentiment Interpretation

Human language can be complicated. One word may mean four completely different things. That’s why it’s important to c،ose a tool that can understand context.

Tools with NLP algorithms can understand ،w the human ،in forms language patterns. They can apply contextual ،ysis. And ،uce more accurate results.

Ensure Ethical Practices and Privacy in Sentiment Analysis

AI and NLP are powerful tools. But in some cases, they can create biases that affect ،w they ،yze language. These biases may misinterpret customer emotions. Or dismiss statements as irrelevant or neutral.

Using reliable ma،e learning models can help avoid these issues. So can regularly reviewing data manually. To confirm accurate sentiment. And a lack of ethical concerns.

Transform Insights into Action with Sentiment Analysis Marketing

To understand ،w customers really feel about your ،nd or ،uct, use a sentiment ،ysis solution.

With the right solution, you can learn much more than what customers say. Including ،w to meet their needs, build deeper relation،ps, and ultimately improve loyalty. And lifetime value.

With our Media Monitoring and One2Target tools, you’ll uncover ،w customers feel about your ،nd, ،uct, or service.

S، ،yzing sentiment around your ،nd. And track changes over time. For deeper insights that lead to greater customer satisfaction, retention, and revenue.