Accurate and timely brand sentiment analysis is critical to building a successful business. Sentiment analysis enables you to identify your brand’s strengths and weaknesses through the eyes of your customers.
In our digital world, where every comment, review or tweet can shape public perception, understanding customers’ sentiments is becoming a strategic must.
Hence, comprehending the emotional nuances helps businesses respond effectively and proactively build a brand in alignment with customers’ expectations.
Using this data to analyse your brand’s performance will help you get a more accurate and subjective view of the success of your brand strategies and direct you moving forward.
In the subsequent sections, we’ll delve into the intricacies of brand sentiment analysis, review its impact on consumer perception, find out how to execute such an analysis, what tools you need and how to use it to steer your marketing strategies in the right direction.
Brand Sentiment Analysis Meaning
In a word, it is the art of deciphering and evaluating the emotions, attitudes, vibes, and opinions conveyed by customers towards a brand.
Word choice, syntax, and tone of voice come into play when evaluating someone’s sentiments. Sentiment is categorised as either positive, negative or neutral.
Picture it as a linguistic detective that filters a vast amount of words and feedback to discover the real feeling behind them.
Brand sentiment analysis goes way beyond words, aiming to know not only what people are saying but to know their feelings when they say it. Whether it’s frustration, happiness, joy or sheer indifference, each sentiment is a piece of a maze that composes your brand perception.
Sentiment analysis is in the middle of a transformative voyage. It started as a rudimentary tool that focused on categorising sentiments as positive, negative and neutral. With the advent of advanced technologies like NLP (Natural Language Processing) algorithms and machine learning models, they are able to depict emotions and context.
Such an evolution propelled sentiment analysis from a reactive strategy to a proactive power that shapes real-time business endeavours.
What Are the Components of Brand Sentiment Analysis?
To gauge these sentiments accurately, sentiment analysis operates with several major components:
Text analysis
Text is the basis of consumer sentiment analysis. Text analysis implies processing customer reviews, social media comments and posts, blog comments and any content connected to your brand.
With the help of NLP algorithms, brands have the opportunity to comprehend the context, tone and general sentiment hidden behind words.
Social media monitoring
Social media is a prominent venue where real-life conversations about your brand develop. Among other things, brand sentiment analysis involves actively monitoring mentions, comments, and hashtags on social media channels where your brand is present.
Besides the buzz and volume of mentions, businesses need to understand the sentiment behind this chatter, from enthusiastic to disgruntled.
Customer feedback and reviews
Direct feedback from customers is a treasure trove for sentiment analysis. It may include customer care scripts, complaints, review platforms, surveys, comments on websites, etc.
Analysing the themes and language of these reviews delivers practical insights into what your clients like about your products and services and what areas need improvements.
Visual content analysis
Analysing images and videos is essential in a world where visuals have a huge role. Visual sentiment analysis counts on advanced technologies to decode the emotions expressed via images, emojis or video content.
This type of analysis adds another layer of depth and helps comprehend how your brand is perceived at a visual level.
Brand Sentiment Analysis Tools
In a fiercely competitive environment, understanding clearly the sentiments around your brand brings competitive advantages.
Nowadays, brand sentiment analysis doesn’t rely on intuition; it’s science-backed by data and powerful technologies.
Here is the trio of instruments that drives the engine of sentiment analysis:
Natural Language Processing (NLP)
NLP is an advanced technology that gathers and processes large amounts of data like customer reviews, comments, social media discussions, articles, etc. Their purpose is to decode the nuances of language considering the tone, context and subtleties of lingo as irony or sarcasm.
The idea is to comprehend precisely what clients say.
In practice, NLP is responsible for your brand sentiment analysis tool’s capability of discerning between a complaint and constructive critique.
Machine Learning (ML) algorithms
The core activity of machine learning is to analyse text, learn and adapt as it processes more data.
ML algorithms are trained on historical data, improving their ability and accuracy to predict and categorise sentiments. This adaptability is welcomed in a dynamic landscape where consumer opinions change fast.
ML is responsible for accuracy improvement in brand sentiment analysis, empowering businesses to stay on top of shifting consumer sentiments.
Social Listening Platforms
The conversations related to your brand are spread across multiple social media channels, forums and online communities.
Social listening tools act as your brand’s ears that catch the shouts and whispers spread in the digital realm. They scrutinise brand mentions, conversations, and hashtags and deliver real-time insights on how your audience perceives your brand at a specific moment.
Social listening platforms alert you on what’s being said about your brand and where, helping you engage effectively with your audience and react promptly.
Keep an Eye on Your Brand’s Health with Symanto
Symanto is a next-generation text analysis software capable of converting unstructured data from customer conversations into actionable insights.
With Symanto’s platform, you can gather all the data you need from all relevant digital sources. Analyse it fast to get advanced brand insights that go beyond ratings and sentiment.
Your brand’s significant benefits are:
- Access millions of data points and obtain valuable consumer insights.
- Receive an advanced analysis personalised to your customers.
- Discover outstanding user insights via psychology AI.
- Leverage accurate brand sentiment at the topic and text level.
- Improve business decision-making by using data and critical metrics obtained via text.
- Tailor the dataset analysis model to your industry needs.
How Symanto works
- Collect data. Gather reviews from more than 75 data sources, upload your files, and collect data from your social media channels.
- Analyse and refine results. Analyse sentiment based on particular aspects, get accurate results using industry-specific models and adapt results to your business needs.
- Explore. Compare customer sentiment across brands with the help of our net sentiment heatmap and check the evolution of sentiment in time.
- Enhance. Use psychographic insights and 360° consumer segmentation to comprehend what influences buying processes and preferences. Evaluate your brand equity and get brand recommendations.
Symanto has developed the capabilities to execute an in-depth brand sentiment analysis and uncover critical details for the business. You will be able to discover the “why” behind the sentiment and get highly accurate, granular results.
In a nutshell, you get:
- Advanced insights. Powerful text analytics that translates opinion aspects into noteworthy topics.
- Granular level sentiment. Detailed analysis to identify the correct context.
- Business-critical metrics. AI prediction of metrics results and comparison with those of competitors.
Measuring More Than Just Sentiment
The Symanto Insights Platform does much more than measure whether someone feels positive, negative or neutral towards your brand.
Find out what proportion of your customers promote your brand through their posts, and discover whether customers are emotionally affiliated with your brand.
There’s a difference between customers who speak positively about your brand and those who want all of their family and friends to try it.
Promoters or detractors use words with a much more potent sentiment. Our platform also measures comments for “Emotional Connection”.
Promoters with an emotional connection to your brand or product are over twice as valuable as delighted customers. They build your brand through word of mouth and social proof.
Symanto can also detect your customer base’s personality traits and communication style preferences, enabling you to hone your messaging and attract more of the same kind of consumers.
Get Started with Symanto
The Symanto Insights Platform excels at analysing textual data accurately and at scale. Get in touch or book your free personalised demonstration to get started today.
How to Use Sentiment Analysis for Brand Building
1. Find out what your customers want
Discovering what your customers really want is the holy grail of building your brand. You’d never imagine it was so easy to find.
Your customers are telling you what they want, both directly and indirectly. Use sentiment analysis technology on reviews and customer comments to isolate the mentioned topics relating to your brand and how people feel towards that topic.
The Symanto Insights Platform isolates topics and subtopics so that you can discern where your main strengths and challenges lie.
Use a function like cloud to discover the main topics related to your brand that are being discussed and their associated sentiment. This will immediately give you an overview of your brand’s strengths and the issues that need addressing from the perspective of your customers.
2. Conduct competitor analysis
You can also use Symanto to conduct sentiment analysis on your competitors. It will help you discover why your customers choose you over other brands in your niche.
Use this information in your marketing strategies to capitalise on your key selling point.
It’s also advantageous to clearly understand the issues affecting your competitors across the board.
If an issue is unique to your brand, you must address it immediately to avoid losing customers to your competitors. If, however, the problem affects your competitors to a similar extent, you may be able to surmise that it’s an industry-wide phenomenon.
3. Capitalise on your strengths
Use sentiment analysis to discover your true competitive advantages. You might be surprised that the main message you push out in your marketing campaigns isn’t what customers identify with when using your products or services.
For example, if you market your brand as the most affordable option, you might have a revelation learning that customers connect more with your responsive and friendly service.
4. Develop your product/business accordingly
Now that you know what your customers want (and what they don’t), it’s time to make the necessary adjustments to your business strategy.
Issues with order fulfilment times? Investigate any funnels in your pipeline, or consider switching courier service.
Is there a negative sentiment around customer service? Invest in training and support for your customer care team.
Sentiment analysis will also help you quickly identify product flaws or opportunities for improvement. Are your customers disappointed by, for example, limited speed settings or lack of colour options? Let your customers direct your product development strategy for you.
5. Keep a close eye on the situation
Regarding brand building, sentiment analysis needs to be ongoing and constant. One PR disaster could set you back lightyears.
Sentiment analysis can be used for PR monitoring. Use sentiment analysis software to detect comments, tweets and reviews with strongly negative sentiment and act on these instances urgently to address them before they worsen.
6. Analyse campaign success
Once you have implemented changes and redirected your marketing messaging, you can use sentiment analysis to monitor the impact.
Did the messaging increase conversation and improve sentiment around your brand? How are customers responding to the improvements you’ve made?
This information will enable you to refine your ongoing strategy.
Preliminary Elements to Implement Brand Sentiment Analysis
To set a correct foundation for sentiment analysis, you need to :
Choose the right data sources
- Customer reviews and testimonials. Good reviews are the starting point for increasing the purchase volume. Simultaneously, client feedback, no matter how it is provided, and testimonials are a treasure for sentiment data.
By analysing the words and language used, you can extract the overall sentiment and various specific aspects, positive ones or those that need correction.
Customer reviews tell the truth about the customer experience.
- Social media channels. They are another valuable source of genuine, unfiltered opinions concerning your brand. Analysing this data to extract sentiment provides real-time insights into how your audience perceives your brand.
In our digital era, social media is more than a data source; it’s the temper of public opinion.
- Feedback forms and surveys. Using surveys and forms to find out your customers’ opinions adds a structured level to sentiment analysis and collects targeted sentiment data. Combined with the spontaneous data from social media and reviews, they create a comprehensive panorama of customer sentiments.
Surveys and feedback questionnaires are guided conversations with consumers that might reveal hidden sentiments.
Choosing the right tools
- Match the chosen tool with your business goals. Today, there is a plethora of sentiment analysis tools to choose from, each proposing its own set of features. The scope is to pick the tool with the most potent features in your area of interest. And ensure return on investment.
For instance, if your purpose is to discover insights early to spot new market opportunities and trends, you should look for such a tool. Symanto is an excellent example in this case.
- Budget considerations. When opting for a specific tool, you must balance functionality with benefits, practical aspects and budgetary considerations. At times, a more straightforward tool that accomplishes the current requirements is a better choice than a more complex tool that you cannot take advantage of all its functionalities.
How to Do a Brand Sentiment Analysis?
Usually, it comprises a series of strategic steps that, when executed correctly, guarantee the accuracy of the results obtained.
Data Gathering
Collect relevant data from relevant or all available sources.
The very first step of brand sentiment analysis is to gather data from a large variety of sources like CRM, customer service, social media, review sites, surveys and other internal feedback pipelines.
Each source will add a different perspective. And will contribute to obtaining a nuanced and complete overview.
The more diverse the data sources, the richer the insights.
Ensure data completeness and accuracy
The quality of sentiment analysis relies heavily on the quality, accuracy and completeness of available and collected data. It’s crucial to pay attention to details, verify sources, and the correctness of the data. Moreover, to depict the context of data, use NLP techniques to comprehend it accurately.
Accuracy is the guiding light of the analysis and ensures that the insights obtained reflect the reality of consumers.
Cleaning and Pre-Processing Data
Removing noise and irrelevant data
Noise may be encountered in a variety of forms like duplicates, redundancies, irrelevant comments, off-topic talk, spam, etc. Advanced technologies like NPL help clean the information and keep just the essence and relevant opinions.
Standardising data for analysis
To obtain accurate insights, data needs to be prepared for analysis. That usually implies standardising the data format, language and expressions.
Standardisation ensures that your sentiment analysis tool comprehends the languages of your consumers and brand and that the linguistic nuances are reconciled.
For example, it’s crucial to ensure that words like “fantastic” and “great” are associated with positive sentiments and that slang or regional variations are recognised.
Pre-processing data is a refining process that guarantees the raw data will be converted into valuable insights.
Core Analysis and Interpretation
Using advanced algorithms
Brand sentiment analysis algorithms are in charge of data processing. Most of them rely on technologies like Natural Language Processing and machine learning to decipher the emotions hidden behind words.
Such algorithms read, understand the context, depict the tone and spot the sentiments expressed by customers. As they are trained to comprehend the subtleties of human language. Ultimately, they will display the emotional course that configures the brand perception.
Discovering actionable insights
The real value of sentiment analysis lies in delivering actionable insights to drive businesses forward. Knowing how customers feel is not enough. A brand needs to understand why and how to react to this situation.
Extracting valuable insights means going deeper and dissecting customer feedback. If the sentiment is positive, what features are generating it? If negative, what elements caused the dissatisfaction?
Such insights are invaluable as they shape business and marketing strategies, product development and enhancement, and eventually prevent crisis.
Brand Sentiment Analysis Challenges
Awareness of the hurdles that can add complexity to your sentiment analysis activity is vital.
Some of the most significant are:
- Language ambiguity and context. Words can have different meanings based on their context. This is a challenge for sentiment analysis tools. Hence, they need to be trained to understand and contextualise the language in its broader conversation.
- Handling irony and sarcasm. Recognising the intricacies of tone in digital conversations is quite a challenge. Because a sentence in appearance positive might, in fact, be infused with sarcasm. Analysis algorithms need to be able to make the difference between figurative expressions and literal words.
- Multilingual aspects. Considering that in our interconnected world, conversations about brands may happen in several languages, sentiment analysis tools should be capable of depicting sentiment in all of them. That means supplementary layers of cultural nuances and idioms.
- Integration challenges. Consumer sentiment is expressed along a series of channels that need to be integrated. Usually, this is a logistical challenge as consistency in the analysis is paramount to getting an accurate brand sentiment and actionable insights. Insights with different origins should be coherent and convergent.
To overcome such challenges, you need a combination of advanced tools and human expertise for interpretation.
Brand Sentiment Analysis Examples
The success stories of businesses leveraging the output of brand sentiment analysis to their advantage are strong proof.
Improving customer satisfaction – Delta Air Lines
Active in a highly competitive industry, Delta Air Line was facing challenges related to customer expectations and poor online reviews. To improve things, they started by implementing sentiment analysis tools to monitor reviews, customer feedback and social media chatter.
As a consequence, they were able to determine their customer satisfaction levels, spot areas of improvement and identify emerging trends.
The result? Delta Air Lines refined its customer service based on real-time feedback received and used strategically positive sentiment to hone their targeted marketing campaigns. Plus, their customer loyalty and brand perception improved.
Brand Sentiment Analysis Delivers Surprising Insights via Symanto
A consumer medical devices provider wanted to analyse its customers’ journey in detail and identify new growth opportunities.
The company had more than 150+ retail stores in the franchise. An advanced sentiment analysis was performed at all levels – individual topics and various behavioural aspects of the customer journey.
Symanto’s team discovered a series of valuable insights like:
- Customer satisfaction was low because clients often did not consult a healthcare practitioner before buying in-store medical devices.
- A competitor had more satisfied clients because they involved healthcare practitioners early in the customer journey.
Conclusion
Brand sentiment analysis is a powerful tool that any company should take advantage of. In our highly competitive world, it can be an invaluable source of actionable insights and eventually provide a competitive edge. Choose your brand sentiment analysis tool now!
