From good to great customer experience:

There are two ways for businesses to increase revenue, on one hand, there is the option of attracting more customers, on the other one they can maintain the ones they have by increasing their loyalty.

In highly competitive markets, looking for new customers is quite expensive and risky, because not all the investments in marketing have a positive ROI and cutting prices only get you so far. However, customers who had a good experience with a brand in the past spend 140%more compared to those who had the poorest past experiences, and 86% of all current customers are willing to pay more for a better customer support. 

Those figures give us strong arguments to re-affirm how important is to provide an excellent customer experience.

In this post, we want to show you how different sectors can extract insights and trends by using text analytics tools:


Text analytics tools have been widely used for a part of the hospitality sector, such as hotels or airline companies. But when it comes to restaurants or food and drink chains the applications of these tools are not that popular. 

One of our clients is one of the largest and trendiest hospitality companies on the Western Coast. They had the challenge of analyzing all the customer feedback at a store and a global level. Their former approach of manual coding was becoming almost impossible as they were growing, they were consuming a lot of time and human resources in just reading. And therefore, they were not reacting fast enough to the insights present on their customer feedback.

By using text categorization, they could detect automatically all the topics of everyone's response and combined with sentiment analysis customer feedback is classified into positive, negative and neutral.

Thanks to our embedded and interactive visualization, were custom filters can be applied, they can visualize the global chain results and the results at a store level. All with much faster turnaround cycles that allow taking immediate actions. 

If you want to know more about this example download our case.


Due to the growth of some marketplaces like Amazon, Asos, or Alibaba, retailers not only offer their products to more consumers but receive much more feedback. Before these marketplaces existed, companies were receiving customer’s opinions by surveys or individual emails to the customer support team. However now, around 92% of consumers check product reviews before purchasing any item.

Studies show that customers check an average of 10 sources before making a purchase, but how is it possible to manage information coming from so many different sites?

Another significant rate, is that 95% of unhappy customers will purchase again from a business if they can solve their issues quickly and efficiently, but again? How is it possible to detect these issues?

By using a variety of text analytics tools is possible to solve both issues:

  • Regarding the first one, thanks to our Customer Experience tool it is possible to analyze text coming from different sources just by adding all the reviews to an excel sheet.
  • Automatic topic and sentiment detection allow retailers to see what are the customer talking about: packaging, prince, quality, fabric and if the comments are positive, negative or neutral.



Software companies care a lot about their user’s customer experience, nowadays is one of the most competitive sectors and there is always at least a couple of products that cover the same need, so businesses need to know what their users think and extract actionable insights.

In one of our latest projects, a leading software company needed to analyze the answers from thousands of specialized surveys generated by top business clients. As many other companies, to analyze the feedback they were using manual coding with a specific coding plan.

The main issue was that this methodology was very resource and time-consuming, reading all the answers manually takes time away from discovering new insights.

With our platform and some assistance from our consultancy team, they transferred their own coding plan in to our automatic categorization platform and achieve 75% accuracy out of the box, and by adding complex rules they can even achieve rates as high as 90%.  

Bitext flexible visualization allows you to extract insights and discover new patterns and trends, so instead of spending your time categorizing you use to what really matters: analyzing.

If you want to kick start your project, we offer you not only a free month of our tool but also access to our consultancy team. All to achieve the highest accuracy on the market and to discover powerful insights that can enhance your customer’s experience.

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