Text Analytics : Five examples
Data is extremely important in today’s world and businesses receive large data quantities in the form of text through emails, chats, and social media conversations. This data is often unstructured and difficult to analyze. However, tools can be used to convert this into meaningful data that can be used for analysis. This process is known as text analytics.
Text analytics allows businesses to measure customer opinion and feedback and product reviews. Technologies and tools like text analytics have a lot of potentials but businesses can be unaware of the opportunities that text analytics can open for them.
These five examples of text analytics are bound to open your eyes to your own opportunities.
- Market Research
As a consumer, it is likely that you look up reviews of a restaurant before making a dinner reservation. You will visit the social media pages of the restaurant as well as websites that publish crowd-sourced reviews of restaurants.
The reason for this is because consumers are interested in knowing the opinions and experiences of other people. If reviews mention particular dishes or a service the reviewer liked, you are likely to remember it.
If reviews have such an impact on you as a consumer, think about what you can do with them as a business owner. Online reviews and feedback can give you an idea of exactly what your customers like or dislike about your business and your products and services.
If you are planning on expanding your business or introducing a new product, a lot of your market research can be based on these online reviews and customer feedback. This is one of the main uses of text analytics services.
- Product Changes
Putting yourself in the consumer’s shoes once again, imagine yourself buying a ready-to-assemble cabinet for your house. Once you get home, you realize that the instructions are not very clear. You may go online and share your negative reviews and complaints on the stores’ social media page.
The store will look at the review and consider points you have made. They may identify these shortcomings with their product and then take measures to improve it. This is another use of text analytics.
- Competition
When managing a business, it is not only the customer you need to worry about. You need to also keep an eye on your competition. Text analytics can help you understand your competition better and know how they are faring. This information can help you offer a better service or product to customers.
State regulations may require businesses to publish certain information about their products and services, especially if there are defects and recalls. In addition to this, there could be reports available publicly on customer opinions about certain industries and sectors. A survey on e-commerce websites, for instance, may give you a better idea of where your own e-commerce store stands in comparison to the competition and what services and products customers would like to see in your store.
Of course, these public records may not be structured and you may need AI service providers to organize this data for you.
- Research
If you introduce a new product to the market but find that it is not performing as well, you may want to do more research into it.
If you are a pharmaceutical manufacturer and find that a particular medication is not being purchased by many despite there being a need for it, you will want to carry out a study on this. If the product was launched across the country, the volume of data may make it difficult for you to find any side effects experienced by people who actually used it.
With text analytics, however, you can easily find the specific data you are looking for.
- Language Detection
A cosmetic product manufacturer with a global presence may receive customer complaints or inquiries from around the globe. These may not always be in English and instantly detecting the language used by the customer will make it easier for the system to direct the customer to the correct localized team.
A machine learning consultancy will recommend using a language classifier to identify the language used in an inquiry within seconds, thus ensuring efficient and quick customer service.
