Leveraging Market Research to Gauge Brand Sentiment.

Image of the post author Geetika Chhatwal

In 2018, Nike launched a bold advertising campaign featuring Colin Kaepernick, a former NFL player known for kneeling during the national anthem to protest racial injustice. This move was a significant risk, as it could have alienated a substantial portion of Nike’s customer base. However, Nike’s decision was followed by extensive market research, which indicated a positive shift in brand sentiment among their target demographic, primarily younger, socially conscious consumers.

Following the campaign’s launch, Nike’s online sales reportedly surged by 31% in the days immediately following. Moreover, a study by Edison Trends noted a 6.25% increase in Nike’s stock price after the ad’s release, hitting an all-time high for the company. 

This example illustrates how market research helped Nike understand and capitalize on brand sentiment, resulting in financial success and strengthened brand loyalty among its core customers.

Using Market Research to Understand Brand Sentiment

Understanding and influencing brand sentiment has become crucial for brands striving to maintain a positive public image and foster customer loyalty. Brand sentiment, the overall consumer perception of a brand, is a powerful indicator of a company’s health and future performance. It can significantly influence buying decisions, customer loyalty, and brand strength.

Market research plays a pivotal role in gauging brand sentiment. It offers insights into how consumers perceive a brand, what drives their perceptions, and how these perceptions translate into behavior. Companies can gather valuable data to understand public sentiment toward their brand through various methods such as surveys, social media analysis, and focus groups.

This blog explores the dynamic between market research and brand sentiment, illustrating how businesses can effectively use data-driven insights to shape their strategies and improve their market position. 

The Role of Market Research in Brand Sentiment Analysis

Understanding how the public perceives your brand is pivotal. Brand sentiment analysis, an aspect of market research, is crucial in this understanding. It involves collecting and analyzing data about a brand’s reputation and the emotions consumers associate with it. This analysis is not just about whether the sentiment is positive or negative but also about understanding the nuances and drivers of these perceptions.

How Market Research Contributes to Understanding Brand Sentiment

Identifying Strengths and Weaknesses: By analyzing the data gathered from various market research methods, a company can pinpoint what customers love about their brand and what areas need improvement. This insight is crucial for strategic planning and operational adjustments.

Measuring Emotional Engagement: Understanding the emotional aspect of brand sentiment—how customers feel about a brand—is as important as the rational perspective. Market research helps measure these emotional connections, key brand loyalty, and advocacy drivers.

Trend Analysis and Predictive Insights: Market research enables brands to track changes in brand sentiment over time. This long-term view can help predict future trends and consumer behaviors, allowing companies to adjust their strategies proactively.

Competitive Benchmarking: By comparing brand sentiment across competitors, companies can benchmark their performance and identify areas where they need to excel to gain a competitive edge.

Feedback Loop for Continuous Improvement: Market research provides a feedback mechanism for companies to continuously improve their products and services based on direct consumer insights.

Success Stories in Brand Sentiment Analysis

Several companies across different industries have effectively used market research to improve their brand sentiment. Here, we explore a few notable examples, detailing the strategies they employed and the results achieved.

Domino’s Pizza Turnaround Campaign

  • Background: In 2009, Domino’s Pizza faced a significant challenge with negative customer feedback about the taste of their pizza.
  • Strategy Employed: Domino’s launched an aggressive market research campaign to understand the specific complaints, including customer surveys and taste tests. They used this feedback to reformulate their pizza recipe.
  • Results Achieved: After the launch of their new recipe, Domino’s conducted an honest advertising campaign, admitting past mistakes and highlighting the changes made. This transparency and commitment to improvement resonated with customers, leading to a substantial increase in sales. In the first quarter following the campaign, Domino’s saw a 14.3% increase in same-store sales, a record in the company’s history.

Lego’s Reconnect with the Core Audience

  • Background: In the early 2000s, Lego faced near-bankruptcy due to losing focus on its core product and audience.
  • Strategy Employed: Lego engaged in extensive market research, including interviews with children and parents, to understand their preferences. This research led to a renewed focus on classic Lego sets and themes that appealed to their core audience.
  • Results Achieved: Lego restructured its product lines and marketing strategies because of these insights, contributing to a remarkable turnaround. By 2015, Lego had become the world’s largest toy company by revenue, with profits growing by more than 40%.

Old Spice’s Image Revamp

Photo Credit: The Drum
  • Background: Once seen as an outdated brand, Old Spice needed to revamp its image to appeal to a younger demographic.
  • Strategy Employed: The company conducted market research to understand the preferences of a younger audience and launched the “Smell Like a Man, Man” campaign, targeting a younger, more diverse consumer base.
  • Results Achieved: The campaign went viral, significantly boosting brand engagement. Old Spice reported a 107% increase in body wash sales following the campaign and successfully repositioned itself as a contemporary brand for a younger audience.

Tools and Techniques for Measuring Brand Sentiment

Brand sentiment analysis is a complex process requiring the right tools and techniques to gauge public perception accurately. Various methods, each with strengths and limitations, are used to understand how consumers feel about a brand. Below is an overview of these tools and techniques, along with their pros and cons.

Social Media Analytics Tools

  • Overview: Tools like Brandwatch, Hootsuite, and Sprout Social analyze social media conversations to gauge public sentiment about a brand. They track mentions, hashtags, and keywords related to the brand across social platforms.
  • Pros: Real-time tracking, large data sets, and the ability to capture organic consumer opinions.
  • Cons: Can be skewed by non-representative vocal minorities and may miss nuanced sentiments that algorithms can’t detect.

Sentiment Analysis Software

  • Overview: Software such as Lexalytics and Sentiment Analyzer uses natural language processing (NLP) to understand the sentiment in textual data from reviews, surveys, and social media.
  • Pros: Automated, efficient, and able to process large volumes of text.
  • Cons: May need help with context, irony, and sarcasm, leading to inaccurate sentiment analysis.

Online Reviews and Feedback Platforms

  • Overview: Platforms like Trustpilot and Yelp aggregate customer reviews, providing direct feedback on customer experiences and sentiments.
  • Pros: Direct from consumers, detailed, and specific to certain aspects of a product or service.
  • Cons: Can be biased (only extremely satisfied or dissatisfied customers may leave reviews) and susceptible to fake reviews.

Surveys and Questionnaires

  • Overview: Customizable surveys distributed via email, social media, or embedded on websites. Tools like SurveyMonkey and Google Forms are commonly used.
  • Pros: Direct feedback can be tailored to specific information needs and include qualitative and quantitative data.
  • Cons: Low response rates can skew data, and responses may only sometimes be honest or reflective of the broader customer base.

Focus Groups and Interviews

  • Overview: Structured discussions with selected groups of customers or one-on-one interviews to gather in-depth insights.
  • Pros: Can provide deep, nuanced understanding and qualitative insights.
  • Cons: Time-consuming, costly, and may not represent the general population.

Net Promoter Score (NPS)

  • Overview: Measures the likelihood of customers, categorized as promoters, passives, or detractors, recommending a brand to others.
  • Pros: Simple, widely used, and provides a clear metric for customer loyalty and satisfaction.
  • Cons: It doesn’t provide detailed insights into the reasons behind the score and can be influenced by external factors.

Interpreting Market Research Data

Accurately interpreting market research data is crucial for transforming raw information into actionable insights. This process involves analyzing the data, understanding its implications, and making informed decisions based on these insights. Here’s how businesses can effectively approach this task.

Data Segmentation and Grouping: Break down the data into manageable segments based on demographics, purchase history, or other relevant criteria. This helps in identifying patterns and trends specific to different customer groups.

Trend Analysis: Look for trends over time in the data. This could be changes in customer preferences, shifts in sentiment, or evolving market dynamics. Understanding these trends is critical for anticipating future market changes.

Cross-Referencing Data Sources: Compare insights from different data sources to validate findings. For example, if survey data indicates a decline in brand perception, check social media sentiment analysis to see if it reflects a similar trend.

Contextual Analysis: It’s crucial to analyze data within the context of the industry, the current market environment, and historical performance. External factors like economic conditions, competitive actions, and technological changes can significantly impact consumer behavior and sentiment.

Identifying Correlations and Causal Relationships: Determine if there are correlations between different data points. For instance, understand if positive sentiment correlates with increased sales. Be cautious to differentiate between correlation and causation.

Qualitative Insights: Consider qualitative data from open-ended survey responses, interviews, and social media shares and comments. This data can provide deeper insights into the ‘why’ behind the numbers.

Use of Analytical Tools: Leverage statistical tools and data visualization software to understand complex data sets better. Tools like SPSS or Tableau can be used for more sophisticated analysis and more precise visualization of trends.

Turning Data into Actionable Insights

Setting Clear Objectives: Know what you want to achieve with the data. Whether improving customer satisfaction, increasing brand loyalty, or enhancing product offerings, having clear objectives helps focus the analysis.

Identifying Key Performance Indicators (KPIs): Based on the objectives, identify relevant KPIs that need to be monitored. This could include metrics like Net Promoter Score, customer retention rates, or sentiment scores.

Developing Action Plans: Based on the insights, develop strategic action plans. If data shows declining satisfaction with a product feature, consider improvements or redesigns. If specific demographics show increased brand affinity, tailor marketing strategies to leverage this.

Testing and Experimentation: Before rolling out significant changes, conduct tests or pilot programs to assess the effectiveness of your strategies. This minimizes risk and allows for fine-tuning based on feedback.

Continuous Monitoring and Adjustment: Market sentiment and consumer behavior are dynamic. Monitor KPIs and adjust strategies to align with market trends and consumer preferences.

Communicating Insights Across the Organization: Ensure insights are effectively shared with relevant departments. Collaboration across marketing, sales, product development, and customer service teams is essential to implement strategies effectively.

The Future of Brand Sentiment Analysis: Emerging Trends and Technologies

As we move into 2024 and beyond, brand sentiment analysis is poised to become even more sophisticated and integral to brand strategy. Emerging trends and technologies are shaping the future of this field, offering new opportunities for deeper insights and more effective engagement with consumers. Here’s a look at some key predictions and trends.

Artificial Intelligence (AI) and Machine Learning: AI and machine learning are becoming increasingly central in analyzing large data sets for sentiment analysis. These technologies enable a more accurate and nuanced understanding of consumer sentiments, including detecting sarcasm, context, and complex emotions.

Natural Language Processing (NLP) Advancements: NLP technology will continue to evolve, becoming more adept at understanding and interpreting human language in text. This will enhance the ability to analyze social media posts, customer reviews, and open-ended survey responses.

Voice and Video Sentiment Analysis: With the rise of video content and voice search, sentiment analysis will expand beyond text. Analyzing voice inflections, facial expressions, and body language in videos will become more common, providing a richer data set for brand sentiment analysis.

Predictive Analytics: The use of predictive analytics in sentiment analysis will grow. Companies can predict future consumer sentiment trends by analyzing current and historical data, allowing for more proactive brand management.

Integration with IoT Devices: The Internet of Things (IoT) offers new avenues for collecting consumer data. Smart devices in homes and public spaces can provide real-time feedback and behavioral data, providing a more comprehensive view of brand sentiment.

Augmented Reality (AR) and Virtual Reality (VR): As these technologies become more mainstream, they will offer new platforms for brand engagement and new data sources for sentiment analysis.

Predictions for Brand Sentiment Analysis Evolution

Increased Personalization: Sentiment analysis will enable brands to offer more personalized experiences and communications, as they will understand individual consumer preferences and emotions in greater detail.

Real-Time Feedback and Action: The ability to analyze sentiment in real-time will empower brands to act quickly, addressing customer concerns and adapting marketing strategies instantaneously.

Greater Emphasis on Emotional Intelligence: Brands will focus more on emotional intelligence, using sentiment analysis to understand and respond to their customers’ emotional needs and states.

Integration Across Business Functions: Sentiment analysis will be integrated across various business functions, from product development to customer service, making it a core aspect of business strategy.

More Granular Consumer Segmentation: Advanced sentiment analysis will allow for more nuanced and granular consumer segmentation, leading to highly targeted marketing and product development strategies.

Final Thoughts: The Imperative of Market Research in Brand Sentiment Analysis

As brand equity can fluctuate dramatically with online sentiment, the role of market research has never been more critical. The omnichannel age demands a new approach to brand equity management firmly rooted in the science of data-driven analysis.

The traditional metrics of clicks and followers are no longer sufficient to gauge a brand’s health. Understanding user sentiment, especially as expressed in social media, is paramount. This is not just about tracking the positive or negative nature of the sentiment but also about grasping its nuances and context. 

Brands capturing and interpreting these sentiments in real-time will have a significant advantage. The rapidity with which good and bad news can spread online means that companies must immediately respond with quarterly reports or even weekly updates. The agility provided by real-time analysis can be the difference between safeguarding a brand’s reputation and watching decades of brand equity dissipate in moments.

State-of-the-art tools and techniques offer up to 90% accuracy in capturing vital indicators such as buzz volume and user sentiment. However, the accuracy hinges significantly on the methods used to decode the context of statements and feedback. This precision is about collecting data and correctly interpreting and converting it into actionable strategies.

Embracing new market research methodologies and data sources is necessary for brands aiming to protect and enhance their equity. By prioritizing real-time sentiment analysis and applying a data-driven approach to brand management, companies can navigate the complexities of modern consumer engagement and sustain brand relevance and appeal in an increasingly fluid marketplace.

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