For businesses, it’s essential to understand how customers feel about their brand and what they think of your organization, product, or service. There is a lot of time and effort involved in figuring out how your organization ranks in terms of good or negative feedback if you must manually sort through a huge volume of data.
Using technologies that automatically “detect” positive, negative, and neutral sentiment, it’s now possible to analyze brand sentiment using improvements in AI technology. Customer feedback can be automatically analyzed by sentiment analysis tools utilizing machine learning to determine user sentiment rapidly and effectively but without lots of staff.
In this piece, we will discuss how sentiment analysis can help you analyze a large volume of customer feedback with ease. Let’s get right into it.
What are Brand Sentiments?
When people talk about your brand, they’re expressing their feelings about it. This is known as “brand sentiment.” Customers’ remarks about a brand’s “sentiment” might be either good or negative.
The context of the interaction is examined in order to acquire greater insights rather than only relying on quantitative statistics (the amount of “likes” or “comments”).
Why is Analyzing Brand Sentiments Important?
The internet is a goldmine of information about your brand: articles, blogs, forums, reviews, and more. At first look, an increase in online mentions could seem encouraging. The quality of the data, though, is critical – is the sentiment favorable or negative? In order to keep tabs on how your customers perceive and feel about your brand, it’s important to track the sentiment of your customer base.
Monitor Impact of Marketing Campaigns
Track your campaigns with the help of social media analytics. It’s possible to monitor the press coverage of a new campaign’s debut day at a predetermined time interval. You can also watch the analysis to see if it increases or decreases.
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Using sentiment analysis tools can help you keep customers and reduce harm to your reputation if it starts to go downhill. It enables you to immediately assess the success or failure of campaigns and advertisements.
Get Product Insights
Is this a brand-new element of design? Find out what people are saying about your new product shortly after it goes on sale. Or, if you’d like, peruse years of previously unseen reactions. You can search for certain keywords related to a new product or feature in order to find precisely the information you are interested in finding.
Instagram, for example, is continually adding new features, such as an in-app video cutting tool. Their business could suffer if they don’t find out how the general public feels immediately away. With brand sentiment research, you’ll be able to get the information you need right away. And you’ll be able to tell when it’s time to adjust.
Analyze Public Opinion
You’ll know wherever your brand stands daily with sentiment analysis. You can monitor your brand persona over time and see how it changes. When it comes to data analysis, machine learning is vastly superior to manual analysis since it does not change its criteria.
Over time, you won’t have to worry about whether you’re making the proper judgments because your results are always accurate.
Avoid Negative PR
On social media platforms, conversations can gain traction at a really fast pace. If the post is something negative about your brand, it can damage your reputation a lot. But if you monitor these posts in real-time, you can resolve them before they escalate.
Take the case of United Airlines. The flight was overbooked and 4 passengers were asked to leave to accommodate the crew. However, one of the passengers was a pulmonologist who refused to vacate his seat as he had an appointment with a patient the following day. The security resorted to forcibly dragging him out during which he got hurt and started bleeding. One of the passengers recorded the incident and shared it on Twitter that went viral. United Airlines did not respond quickly which hurt their brand reputation.
Identify Urgent Issues
When it comes to determining which brand references are most important, sentiment analysis can help. The right time will come for you to reach out to customers, whether it’s to express gratitude for their kind words or to assist them in resolving a problem.
Thanks for reaching out, Eniko. We’re so sorry for the experience you had with us on chat. Please shoot us a DM with your email on file and we’d be happy to look into this further for you. Look forward to hearing from you!
— ClassPass (@classpass) November 29, 2021
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To further enhance your business image, you can participate in the debate that has been started by a well-known social media influencer or a well-known blogger. However, you can prioritize product or customer complaints and reply within minutes if there is a problem.
How to Analyze Brand Sentiments?
Now that you know what brand sentiments are and why they are important, let’s discuss how to analyze brand sentiments.
BytesView
BytesView is an amazing sentiment analysis tool that can help you analyze and sentiments of users with ease. It offers various in-built integrations, such as Zendesk, Zapier, Excel, and Google Sheets. If you like, you can also select from a variety of bespoke integration options.
In addition, BytesView allows you to develop and train custom sentiment analysis models based on data particular to your organization. To construct your own sentiment analysis model, you can use the BytesView API. Building a custom sentiment analysis model provides the greatest benefit in terms of accuracy.
Closing Thoughts
It’s important to know exactly how the consumer feels about your brand at any given time using brand sentiment analysis. You can use a variety of effective machine learning techniques to gather the data you require.
Start leveraging BytesView’s sentiment analysis to get access to actionable insights about your brand.
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