Top 4 Benefits of Sentiment Analysis in Retail Industry in 2024
In 2022, the retail industry surpassed $5 trillion for the first time, indicating a continuing desire to buy and consume. However, staying updated with emerging retail industry trends, meeting an increasing number of customers’ needs, and standing out among competitors require great effort.
That’s why retail companies have started to automate their processes to benefit from AI-powered methods even more. Sentiment analysis, a natural language processing (NLP) method, has applications in many industries, and the retail sector is one of the greatest markets for sentiment analysis.
Here are the top four benefits of sentiment analysis in the retail industry:
1. Improve product and service quality
Customers usually prefer to express their opinions or sentiments regarding brands on social media. Here is an example of a customer sharing her feelings about a brand on Twitter:
Figure 1. A customer expresses what she would like to see in Walmart stores
A recent report shows that almost 30% of customers change their usual retail store to meet their needs. That’s why understanding how the customers feel about your products is crucial to align with customers’ needs and increase customer retention.
Through sentiment analysis, you can examine your customers’ reviews, feedback, or comments on social media to get insights into the products least preferred, what they need, or what would make them happier. This allows you to improve your existing products, develop new ones, and provide better service quality.
Figure 2. An example of consumer feedback and their sentiment scores
For instance, you can analyze the sentiment in customer reviews on products and rank them. You can determine a cut-off point, then work on improving the products below it.
For more, feel free to check our article on the use of sentiment analysis in marketing.
2. Provide personalized service
A survey conducted by Segment indicates that over 70% of customers feel frustrated when they do not receive a personalized experience. Personalized customer experience includes offering them promotions depending on their buying patterns, interacting with them with their names, or developing products that meet their expectations.
Sentiment analysis helps companies to understand their customers’ emotions and needs. You can analyze your customers’ feedback to offer them a personalized experience and increase their satisfaction. For example, you can explore the sentiment of your customers on social media and get insights into how to improve service quality.
3. Optimize marketing strategies
It is important to know what your customers think about your marketing strategies. Implementing sentiment analysis methods can be very helpful in measuring the ROI of your marketing strategies and either changing them or making necessary adjustments.
For example, the retail company Sears changed its logo in 2019 as a rebranding strategy to increase sales. However, they overlooked the importance of the emotional bond that customers may have with the old logo, which resulted in a bad rebranding strategy. By implementing sentiment analysis methods, you can get feedback from your customers before making your rebranding strategy public to understand how they feel about it. This helps you to prevent any unforeseen outcomes and minimize failure.
4. Increase brand loyalty
Figure 3. Factors that influence brand loyalty
“If you’re trying to build brand loyalty today, an emotional connection is no longer a nice-to-have, it’s a need-to-have.”René Vader, Global Sector Leader, Consumer & Retail, KPMG International.
Loyal customers are important for a brand in a way that 86% of them recommend the company to friends or family, 66% write positive reviews, and 46% remain loyal even after a bad experience. So, ensuring loyalty is essential for companies.
Small companies may personally interact with their customers and learn about their experiences. However, tracking every customer feedback is impossible if you are a tech giant, e-commerce retailer, or mid-level merchant. As sentiment analysis is conducted with machine learning algorithms, it helps you to detect negative feedback or reviews and take quick action against them. Thus, you can provide better service or products, which in turn promotes customer loyalty.
If you want to learn about the benefits of sentiment analysis, check our article.
- Top 5 Sentiment Analysis Challenges & Solutions
- Latest Top 4 Real-Life Examples of Sentiment Analysis
Get in touch if you have any questions regarding sentiment analysis:
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