Use Case For Text Analytics

Text analytics is the process of extracting meaningful insights from human-written texts, using techniques such as natural language processing to identify patterns, trends, and sentiments. It's an important tool for extracting value from the vast amounts of unstructured data about brands.

This technique helps turn customer feedback, user reviews, verbatim comments on surveys and social media interactions into insights that can shape strategy, refine messaging and improve the customer experience.

In this article, we explore some of the use key use cases where text analytics can be employed to provide insight and discuss why brands should be utilising this capability.

Analysing online customer feedback

One of the most common applications of text analytics is analysing customer feedback. There are a lot of opportunities for customers to share their thoughts and experiences with brands. However, much of this feedback comes in the form of open-ended responses in online reviews.

Text analytics enables us to make sense of this information by identifying common themes, sentiments and the attributes customers associate with brands. This goes beyond simple keyword tracking and allows a deeper understanding of the issues driving customer satisfaction or dissatisfaction. Text analytics can quickly spot emerging trends, whether it’s a recurring complaint about a product feature or praise for a particular aspect of service. By acting on these insights, brands can refine their offerings, improve customer experience and build stronger relationships with their customers.

Customer experience

Text analytics plays a significant role in extracting meaning from the vast amount of unstructured data generated by customer experience channels. Whether the data comes from surveys, call centre transcripts, online chat or open-ended NPS questions, text analytics can aggregate and analyse this feedback quickly.

We use the analysis to help brands prioritise the issues most important to the customer, identify gaps in service delivery and adjust strategies accordingly. For example, if a retailer notices that third party delivery times are frequently mentioned in customer reviews, they can take immediate action to improve this aspect of the customer experience.

The value of text analytics within customer experience programmes lies in its ability to continuously inform business decisions, helping brands stay customer-centric and responsive.

Product development

Product development is another area where text analytics is a valuable tool.  Text analytics aggregates and analyses product specific comments to help product teams identify the most common pain points, bugs and potential areas for improvement.  For example, if a recurring issue with a product feature is flagged through customer reviews, text analytics can quantify the extent of the problem and provide evidence to support its prioritisation in the development roadmap. This capability not only speeds up the product improvement cycle but also ensures that innovations are aligned with customer needs, improving overall satisfaction and reducing the risk of launching products that fail to meet market expectations.

Text analytics can also be used to monitor rival brands and identify the strengths and weaknesses of products directly against competitors. It uncovers gaps in brand offerings, gain insights into emerging trends and highlights where brands can differentiate or improve their products to better meet market demand.

Reputation management

Reputation management has become increasingly complex as more consumers take to digital platforms to share their opinions. In this environment, the ability to monitor and manage a brand’s reputation is critical. Text analytics allows brands to track online discussions, reviews and media coverage, providing a clear view of how their brand is being perceived. This continuous monitoring helps brands identify potential issues before they escalate into full-blown crises. For example, if negative sentiment around a brand spikes following a controversial ad campaign, text analytics can pinpoint the specific issues that are fuelling dissatisfaction, enabling the brand to issue targeted responses.

In a competitive landscape, maintaining a positive brand image is crucial, and text analytics offers a proactive approach to ensuring that a brand’s reputation is managed effectively.

Conclusion

In conclusion, text analytics offers brands an important opportunity to make sense of the vast amounts of unstructured data they encounter daily. From improving the customer experience to enhancing and supporting product development and brand reputation, the value of these insights is immense. 

Get in touch if you're interested in finding out more about how text analytics can help your brand.