In the hyper-competitive and hyper-connected world, customer experience has now become essential for many organizations. Every organization nowadays relies on their customer experience data to deliver the most relevant expectations.
So what value does this data analysis hold for businesses?
Every business strives to achieve such information so that they can continue performing their operations in the right direction. The data of customer experience is beneficial in many more ways than we could think of.
For instance, organizations can utilize this information for;
- Taking right decision to deliver more value to the business
- Creating an improved and more personalized customer experience
- Understanding the issues with the product quality and their root causes
- Improving channels of customer interactions and to provide timely resolutions
While it is becoming increasingly difficult to compete the price and product quality alone, organizations monitor the opinions of their customers in real time by making use of;
- Sentiment Scores
- SAS Text Analytics
To assist you further with these two approaches, let us have a look at each of them separately.
Sentiment Analysis vs. SAS Text Analytics
Both of these approaches are basically used to obtain meaning from the customer data and both of them are critical components of an established customer experience management program.
However, both of these approaches differ significantly on various grounds.
SAS Text Analytics is basically used for business intelligence, advanced analytics, predictive analysis and data management. While this can be achieved through a programming language, it can also be achieved through a graphical interface or Base SAS.
With the use of the text analytics process, a business can extract relevant information, analyze unstructured text, and transform it into meaningful and effective business intelligence. In simple words, text analytics provide the face value of written words.
On the other hand, a sentiment polarity score only determines if an opinion or expression is negative, positive, or neutral. A sentiment score provides insight of the ‘degree’ of emotions behind the customer experience.
The three major differences between both the programming tools are;
- Identification of different types of content from customer experience
- Provide different types of warning in terms of possible risk
- Work on different processing technology to generate results
While the traditional sentiment score approach has been used widely for a long time, the majority of organizations have now switched to SAS Text Analytics. Out of many, the potential benefit of adopting this advanced technology lies in making bold business decisions on the basis of the most specific insight in order to transform the existing business.
SAS Text Analytics and Customer Opinions
To achieve maximum accuracy in analyzing customer opinions, the features, brand, and sentiments must be assessed in the form of context rather than just simple phrases or words. SAS Text Analytics uses advanced programming to provide meaning to customer opinions at a deeper level than would have been achieved using sentiment score.
For instance, SAS contextual analysis is an application of text analytics that is web-based and provides a comprehensive solution for the problem of categorizing and distinguishing textual data. The application uses contextual analysis to perform its functions.
SAS Text Analytics allows many businesses to comprehend the language in context. The programming tool enables organizations to make the most of their customer’s experience by applying linguistic tools and statistical methods to automatically access, analyze and act upon the insight buried in text such as social media content, survey data, call center logs, service notes, and others.
The Use of SAS Text Analytics for Different Business Setups
SAS Text Analytics is used to analyze the textual information and as a key for improving business efficiency. Since all the businesses and organizations throughout the globe depend on their customer experience and transform their business using this valuable information, SAS Text Analytics can be used in almost all types of businesses.
Today, SAS Text Analytics is being used as the basic tool in various telecommunication companies, banks, government agencies, healthcare organizations, travel agencies and others. SAS Text Analytics is needed by all these businesses for the accumulation of large customer data and its utilization in shaping business decisions.
For instance, banks use SAS Text Analytics to improve the precision of the scoring model and to curb fraudulent activities. They use the textual analytics to know the borrower’s interest and develop the risk management process among other uses. The inclusion of SAS in the working of banks also helps in improving credit scoring accuracy by almost 25%
Similarly, the public sector uses the SAS Text Analytics to make development decisions. The construction or real estate industry would use this tool to develop pricing models that are based on the data of sold real estate sites. In the same way, the examination of textual information of clients in the telecom industry allows profound decisions and conclusions.
Monitoring of Customer Satisfaction to Improve Business Performance
In today’s world, the use of SAS Text Analytics is beneficial for customers as well as companies. In simple words, when a customer uses a brand and delivers its feedback in terms of quality and experience, businesses analyze the information through SAS Text Analytics to gain meaningful customer experience. The businesses will then be able to understand the customer needs, their expectations, the need for change, their problems, and provide real-time and effective resolutions, creating a personalized customer experience.
Moreover, companies can improve their performance and add value to their business by identifying the customer attitude and perceptions just by the language they use, while shaping their business decisions and dynamics around their customer’s needs, providing excellent services and ultimately increasing business revenue.
SAS Text Analytics has taken over business decisions with its precision and accuracy. Any business that aims to stay connected with their customers, gain a valuable advantage in the competitive industry, attain the most valuable information, and make appropriate business decisions, must adopt the technology of SAS Text Analytics.
Introduce your business to these analytics tools that are known for their high-performance and advanced level of accuracy. Make yourself aware of what’s happening and predict what’s going to happen with the help of the information processed by these tools. Moreover, invest your time and efforts in making only the most accurate and profitable business decisions at each step of your business success ladder.