Why teX.ai Can Help You Build A Truly Customer-centric Business?

‘Customer is king’ is an old adage that every business recognizes. Those who manage to truly satisfy their customers have an undeniable competitive advantage and genuine customer loyalty.

These days, social media has empowered customers further by providing them with platforms to express their views and influence the purchasing habits of their friends and social circles. It has enabled customers to reach out to businesses directly or indirectly. They are able to access the social media pages of businesses to express their views and complaints or post reviews and comments on different platforms.

Before jumping into the core, you should read: What Text Analytics Tells Us about a Customer’s e-commerce Shopping Experience

Knowing what the customer is saying is critical for businesses in more ways than one. It can help them understand their strengths as well as areas of improvement. It can help business leaders formulate strategies that are critical to building a truly customer-centric business.

Simple and logical as it seems, it is really not so. The number of views and reviews are infinite and increasing by the minute. Each review can have different shades, praising and criticizing different aspects of the same business, every bit of which needs to be heard and acted upon.

Manually sifting through each review to catch the sentiment of the customers is daunting as well as time-consuming. By the time a meaningful image can emerge, the business will lose the opportunity to address critical issues in a timely manner or press in on an advantage. Here the sentiment analysis solution plays the vital role to provide customer centric business plan by addressing the critical issues.

Automating Text Analytics of Customer Reviews

Automated text analytics software such as teX.ai can speed up the process of sentiment analysis. teX.ai can sift through large volumes of data and extract key phrases within weeks as against the months it will take to sort it manually. The product needs to be “trained”, but once that is done, they can act as ears that can ‘hear’ every word being said and extract every nuanced meaning for the business to act upon.

For instance, we have worked with a sports retailer to develop a proof of concept for sentiment analysis. For this, the team was given a table with 12,000 rows of reviews, each row representing just one customer. The teX.ai product was trained to identify key terms and even segregate positive and negative reviews within each review. That is, one review may highlight the strengths of the product while giving a negative view of the service or vice versa. The product can be trained to segregate each of these sentiments from each row – to provide a comprehensive overview.

It’s not wonder about Customer feedback or experience, right? Anyhow you might be interested to read on Voice Of Customer Analysis For The World`s Largest Sports Goods Retailer

The second area where the teX.ai product helps is in narrowing down the large volume, and bring the focus on five to ten key areas that the business should focus on.

From hundreds of reviews, the aspects that are most spoken of are extracted and grouped so that the businesses can channelize their energies to improve those specific areas or take corrective actions.

The third advantage of teX.ai is the dashboard that not only provides a comprehensive overview but also allows users to drill down to the review level depending on their business needs. The reports can be customized for different stakeholders within an organization. The reports generated from teX.ai can be different for the CEO and the marketing manager.

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Key Advantages of using teX.ai

teX.ai – An automated text extraction and sentiment analysis tool is highly customizable – and can be tailored to suit the needs of different enterprises and stakeholders.

It converts unstructured text into a structured format and enables:

  1. Identifying the local sentiment rather than the global one by minutely examining and analyzing the different views present in each review
  2. Identifying the key areas of focus
  3. Derive actionable insights

Along with machine learning models, NLP models are applied to capture nuanced meanings for an accurate understanding of the review. Language is used in different ways by different people.

Sarcasm, subtle hints and nuances can throw tools off track when they rely purely on machine learning.

By using linguistic models based on phonology, grammar and lexicon, the teX.ai product can extract the essence of every review to present a clear and accurate meaning.

Use Cases

The potential for use of this AI based text analytics tool is unlimited. It can help retailers, e-commerce companies and marketplaces improve their product mix, cross-sell and upsell.

It can help mobile app providers understand what customers are saying about their apps and where they can improve or strengthen based on the views presented.

Every business deals with customers and every customer has an experience they want to share. Especially for B2C businesses, teX.ai can be the window through which they can understand their customers better and cater to their demands in a meaningful and timely way.

If you want to listen to your customers and extract actionable points for improving your business strategies, Inquire Now!!!

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