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    The role of sentiment analysis in marketing

    Delivering successful campaigns hinges on understanding your target customers. When you know how they feel about your brand, products and industry, you can reasonably predict what it takes to build a campaign that resonates.

    Today’s customers are sharing feedback in new ways. Often, that feedback isn’t given directly to the company. Gathering as much insight as possible from the feedback you have is crucial. Without sentiment analysis, you only capture a small part of the big picture.

    Sentiment analysis marketing is an AI-powered technique that decodes the nuanced emotions and opinions your customers express online, producing insights about what truly drives your target audience.

    In this blog, you’ll learn how to amplify the impact of your marketing strategy using sentiment analysis.

    Table of contents:

    What is sentiment analysis marketing?

    Sentiment analysis in marketing is the process of analyzing and understanding the emotions, attitudes and opinions expressed by customers or potential customers toward a brand, product, service or marketing campaign. This analysis is conducted using natural language processing (NLP) techniques on digital text data from sources like the following:

    • Social media
    • Customer reviews
    • Articles
    • Surveys
    • Online forums
    • Customer service interactions

    Sentiment analysis classifies each piece of text as positive, neutral or negative.

    Positive sentiment reveals what customers like about you and often highlights areas of opportunity. Negative sentiment catches risks and identifies aspects of the customer experience that could use improvement. Neutral sentiment identifies a lack of strong positive or negative emotions in a piece of text.

    Role of sentiment analysis in marketing

    Sentiment analysis enables marketers to craft campaigns tailored to how their audience actually thinks and feels. It takes the guesswork out of catering to your ideal customer, making it easier to develop strategies that resonate and drive engagement.

    How sentiment analysis works

    Sentiment analysis tools digest large volumes of text and produce insights into your customers’ experiences, thoughts and feelings. Data is collected from online sources like social media, review sites and forums. That text then undergoes a preprocessing phase to remove noise, irrelevant information and formatting inconsistencies. This may involve tokenization, lowercasing, removing stop words and stemming or lemmatization.

    Once the data is clean and structured, machine learning algorithms or deep learning models extract words, phrases or n-grams that represent the content and context of the text, classifying the sentiment of each piece as positive, negative or neutral. They use a standardized scoring system to rate sentiment with minimal bias, making the resulting insights more accurate and trustworthy. From there, brands use the insights to optimize marketing initiatives.

    8 applications of sentiment analysis in marketing

    Sentiment analysis is like giving your customers a seat at the table, where you can get their honest, unfiltered feedback. Understanding how customers feel about a subject at any given moment helps you design stronger conversion paths, make better budgeting decisions and strengthen customer relationships.

    To get you started, here are some of the most impactful sentiment analysis applications:

    Social media listening

    Use sentiment analysis with social media listening to interpret what people are saying about your brand, product or niche on social networks.

    Your sentiment analysis tool will digest social posts and comments and score them based on the emotions, opinions and attitudes conveyed. This standardizes the process of determining how customers perceive your brand or other topics on social media.

    Marketers can implement these insights into their social media strategy by crafting campaigns with customer sentiment in mind. Incorporating the target customers’ opinions and emotions shows that you’re listening and care about your audience. This can lead to deeper connections and engagement through more personalized campaigns.

    Brand insights

    Sentiment analysis also reveals opportunities for improving products, services and the customer experience.

    Monitoring sentiment in real time to identify negative sentiment and protect the brand’s reputation in times of crisis.

    Sentiment analysis can also uncover compelling stories from customer feedback data. You can use these authentic customer stories to create powerful brand narratives that speak directly to your customers’ needs.

    Competitive analysis

    Analyzing a competitor’s customer sentiment provides valuable insights into their brand perception, market share and market behavior, giving you a competitive advantage.

    These insights are useful for benchmarking your performance, improving your audience engagement and identifying opportunities for differentiation.

    Opinion mining

    Opinion mining uses sentiment analysis to examine customer feelings, intentions and opinions on a sliding scale. Instead of scoring sentiment as positive, negative or neutral, opinion mining ranks a customer’s specific emotion. For example, a user’s social media comment could be ranked between “very happy” and “very unhappy”.

    Because opinion mining explores the underlying emotions driving customer behavior,
    you can use it to enhance the quality of market research, marketing campaigns, risk mitigation and customer service.

    Voice of customer (VoC)

    VoC represents feedback across the customer journey. Brands use VoC programs to design products and marketing strategies based on the wants and needs of their target customers. Around 83% of U.S. consumers classify good customer service as an important or critically important driver of brand loyalty. Leveraging sentiment analysis for VoC analysis enables you to optimize customer experiences and drive business growth.

    Sentiment analysis tools analyze customer sentiment from online reviews, surveys, CRM notes and other sources in real-time. This allows you to identify a problem or opportunity and then quickly adapt marketing strategies to meet the needs and preferences of your customers. Staying aligned with customer expectations fosters stronger relationships and drives customer loyalty.

    Market research

    There are several ways to apply sentiment analysis to market research. One example is market sentiment monitoring, which uses sentiment analysis to monitor overall sentiment and public opinion on industry trends, events and issues.

    Market researchers can use the sentiment insights gathered from news articles, social media conversions and online discussions to learn about the market dynamics, sentiment and potential shifts in consumer behavior. They can also use aspect-based sentiment analysis to research which aspect of a service, topic or product is preferred over others and why, all from open-ended feedback.

    Sentiment analysis can also predict shifts in customer preferences and market trends by identifying patterns and correlations in historical sentiment data.

    You can also use sentiment analysis to review open-ended target market surveys and analyze quantitative data on the emotions and opinions of survey respondents at scale.

    Influencer prospecting

    Sentiment analysis helps marketers find influencers whose sentiments align with the brand’s objectives. Identifying influencers who resonate strongly with your brand leads to more impactful and authentic collaborations.

    Start by finding influencers who often post using your target keywords, then use sentiment analysis to assess how their audience feels about the keywords. The ideal influencer’s audience will have positive feelings toward your niche topics.

    Campaign performance analysis

    Sentiment analysis helps marketers analyze and optimize campaign performances.

    Assess campaign performance in real time by tracking customer sentiment and analyzing the reasons why a campaign may succeed or fail. Try identifying which regions and demographics responded positively and negatively, then find out how you can optimize future campaigns to improve sentiment for each customer segment.

    Top sentiment analysis marketing tools

    Manually assessing customer sentiment would require hours—even days—of scraping together brand mentions, customer service interactions, online discussions and other relevant content, and then giving each piece of content a sentiment score, one at a time. On top of the time it would take, the inconsistencies and human bias would make the results unreliable.

    Luckily, there are plenty of advanced tools and technologies available for decoding a customer’s emotions and opinions. Here are some sentiment analysis marketing tools you can use to produce actionable insights, optimize marketing campaigns and elevate your customer experiences.

    Sprout Social

    Sprout Social is an all-in-one social media management platform equipped with sentiment analysis features that help marketers understand their customers’ wants and needs. Sprout uses AI-driven technology to enable high-volume data ingestion at scale. Our listening solution processes up to 50,000 posts per second and an average of 600 million messages every day, so you can zero in on the high-impact conversations driving the perception of your brand.

    Sprout’s sentiment analysis detects customer sentiment in complex sentences with emojis and grammatical inconsistencies, providing an accurate picture of how customers feel. Brands can track these insights over time, while also filtering individual posts by sentiment to triage high-priority customer service requests.

    You don’t need to be a Boolean search expert to use our powerful Listening tool. The Queries by AI Assist feature generates suggestions that refine your query based on your provided keywords.

    And because Sprout’s sentiment analysis tool is part of a full suite of social media marketing solutions, it’s that much easier to apply sentiment analysis across your entire marketing strategy. With Sprout, you can action insights directly into your social strategy within the platform, plus generate insights and reports that can be shared across departments to impact the larger business.

    The role of sentiment analysis in marketingKey features:
    • Customer sentiment: Explore customer feelings and opinions on specific topics, trends, products, experiences and more
    • Social listening: Build sophisticated listening queries that capture audience insights on your brand, marketing campaigns, competitors and more
    • AI-powered filters and intelligent search queries: Use AI and automation to adjust listening query filters for more thorough, actionable results
    • Streamlined data analysis: Automatically sift through billions of data points to uncover trends, insights and key learnings
    • Crisis management: Monitor evolving conversations with custom crisis alerts and granular sentiment analysis
    • Competitive analysis: Identify industry gaps, track share of voice (SOV) and understand how customers perceive your competitors
    • Influencer prospecting: Identify influencers and thought leaders based on post sentiment and impact

    Reputation

    Reputation’s customer insights tools break down and analyze customer sentiment to reveal trending topics in real time. They use advanced text analytics to determine the subject matter and sentiment of a piece of content and display insights in a dashboard sorted by topic and theme.

    Use Reputation to understand customer sentiment, highlight your brand’s strengths and weaknesses, improve your customer experience and identify and mitigate risks critical to your brand.

    Reputation sentiment analysis dashboard showing reputation score

    Key features:

    • Competitive reporting: Understand customer sentiment toward competitors
    • Experience insights: Measure how customers feel about your customer experience
    • Reputation score: Get a real-time calculation that measures how customers perceive your brand
    • Sentiment maps: Analyze the emotions expressed in comments and reviews.
    • Automatic feedback categorization: Automatically group customer feedback into categories unique to your industry

    Monkeylearn

    Monkeylearn’s free sentiment analyzer allows marketers to quickly detect emotions in text data. Paste your text into the box to receive a sentiment rating. The tool will tell you whether the sentiment is positive, negative or neutral with a confidence percentage.

    A LinkedIn post reposted by Sprout SocialAn image of the same Sprout Social LinkedIn repost in Monkeylearn's free sentiment analysis tool

    Key features:

    • Sentiment analysis: Identify customer sentiment for a piece of text as positive, negative or neutral
    • Confidence rating: Receive a confidence rating for each sentiment

    Lexalytics

    Lexalytics uses text deconstruction and NLP to evaluate the sentiment of a piece of text. The tool uses categorization, named entity recognition, intention detection and other techniques. This produces structured conclusions that help marketers conduct historical and predictive analytics.

    This tool is ideal for transforming large amounts of social media content into structured insights that help marketers assess conversations about products, brands, people and services.

    Lexalytics's dashboard showing the feedback section with metrics such as tag, role and region along with their sentiment scores in color codes.

    Key features:

    • Sentiment analysis and rating: Gather and rate customer sentiment insights
    • Document categorization: Categorize customer reviews, support tickets and other documents using NLP and machine learning
    • Entity extraction: Automatically pull proper nouns from text and determine their sentiment from the document
    • Intention detection: Understand the intention of each piece of customer feedback
    • Native language support in 29 languages: Analyze customer feedback in 29 languages

    Talkwalker

    Talkwalker’s AI-powered sentiment analysis helps marketers understand what customers want and safeguard their brand’s reputation. This tool adds sentiment information to all monitoring results, from news articles and social media posts to survey responses. It flags high-risk posts in real time, helping you safeguard your brand’s reputation through rapid action.

    The tool also offers sentiment indicators for product features, helping you compare key product characteristics to find out which features your audience loves, which need improvement and ways you can stay ahead of the market.

    Talkwalker's sentiment analysis dashboard featuring customer feedback analytics and custom filters with sentiment scores

    Key features:

    • Sentiment analysis: Use AI-powered sentiment analysis to analyze customer feedback with an accuracy of 90%
    • Competitive intelligence: Understand how customers perceive your competitors
    • Content ideation: Brainstorm content ideas based on customer sentiment
    • Real-time trend identification: Identify current trends that resonate with your customers

    Optimize your marketing strategy with sentiment analysis

    Customer feedback is changing. Customers won’t tell you directly when they’ve had a bad experience. They’d rather take to social media or review sites to talk about it. This makes gathering feedback and analyzing their sentiment even more important. This is where sentiment analysis tools prove to be an invaluable resource. They help you automatically extract rich customer insights from a variety of sources to drive meaningful improvements to your products, marketing campaigns, brand reputation and more.

    To make the most of it, you need the right tool. We shared a few here, but check out our extended list of sentiment analysis tools to further research the best options on the market.

    The post The role of sentiment analysis in marketing appeared first on Sprout Social.

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