Every company relies on customer feedback to improve and iterate on its products. There are lots of ways to reach conclusions about what your customer base wants, and choosing the right data or feedback to focus on is critical, but one of the most valuable sources of information are comments, reviews, and other direct sources of opinion. Unfortunately, making sense of these inputs can be extremely challenging, as collecting, categorizing, and drawing conclusions from a large body of subjective or qualitative sources of information is no easy task. This is where the right consumer sentiment tools and strategies can make a huge difference.
This is especially true with eCommerce companies or large online retailers. Unlike brick and mortar stores, where sellers meet their customers and can read their emotions through facial expressions, online sellers can have a hard time reading the intent of customer feedback. As an eCommerce manager or marketer, you cannot quickly tell if buyers are happy or satisfied with your products. This is where customer sentiment analysis can help you evaluate your customers’ feelings about your services.
Sentiment analysis covers a wide variety of strategies and approaches to gathering data, but at its core, it’s about understanding the emotional intent of a text or collection of text-based data, like reviews, comments, or social media posts. Sentiment analysis relies heavily on machine learning and NLP to achieve accurate results. Done well, it allows sellers to determine if customers view your brand or products in a positive, negative, or neutral perspective. Bad sentiment analysis, on the other hand, can miss a lot, and lead to incorrect conclusions.
In many ways this is still a nascent technology, but you can use increasingly sophisticated tools to extract feelings and opinions from a text automatically. These tools can recognize positive, negative, or neutral words and spot emphasis when the buyer is extremely happy or unhappy about your brand or product. In the right hands, sentiment analysis can be a powerful tool, but it needs to be implemented carefully and intentionally.
Perhaps the best and most obvious use of consumer sentiment analysis is using it to understand, in a broad sense, how your customers are reacting to a certain market input. Consumer sentiment analysis can always be useful, even with existing products, but it is uniquely valuable when your brand is introducing a new product, feature, or service. It can also be used to help understand whether or not a product update is being well received, or if your marketing campaigns are having the desired effect.
Consumer sentiment analysis allows you to trawl a wide swath of data -- a collection of product reviews, social media posts that reference your brand, responses to online surveys or comments on a web form -- and draw actionable conclusions from that data. This sort of analysis can be used in place of or run alongside traditional methods of determining customer attitudes (like direct polling or focus groups), and can help brands uncover insights that might have been previously unavailable.
Another unique implementation of consumer sentiment analysis is that it can be used to benchmark your brand or your product against your competitors. Understanding the positive (or negative) associations that your product has when compared with your direct competition can provide powerful strategic insights that will let you target your future updates, product rollouts and marketing campaigns.
One of the unique values of sentiment analysis is that it can allow you to draw information and conclusions that consumers might not always be willing to share, or even fully aware of themselves. By analyzing the textual content of reviews or comments about your competitors, you have access to powerful information that might be otherwise expensive or difficult to obtain.
As mentioned above, one of the unique value propositions of sentiment analysis and tools like it are that it allows companies to glean actual consumer intent and opinion, even when they might explicitly say something else. Customers aren’t generally trying to be deceptive, but they may not know themselves exactly what their opinions are, and they may not be entirely honest or fully responsive on a survey or in a review or comment. There are pitfalls when using sentiment analysis this way (it is still possible to draw the wrong conclusions), but it provides a valuable data point and can help inform your future product or marketing efforts.
Customer sentiment analysis is an inside line to your consumers' thoughts about your brand. Their comments on social media, product reviews, and feedback directly to your customer support team are rich sources of information if you are able to mine them effectively.You can utilize sentiment analysis tools to establish what their emotions are and in return determine the areas that need improvement. This will significantly help you fine-tune your product development and marketing efforts. If you understand what your customers want, you can develop a product that meets their specific needs. This can make marketing and product development substantially easier for you. It improves your brand health in terms of awareness and reputation, hence little effort needed to attract new customers and retain the existing ones.
We are here to help you understand your customers through Yogi, an AI-based platform that reads your data to help you understand it more profoundly. The platform can be personalized to meet your company's specific needs, and with this, you can improve customer services and build brand reputation.
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