06 February 2018

Listen to your customers with text analytics

Comments, articles and reviews are often considered part of the qualitative world. But with text analytics, you can analyse large amounts of text and listen to customers' positive and negative views of your company.

Administrating and analysing data, such as text, represents one of the biggest business opportunities for companies right now. It concerns both data administration, which you can process with a strong architecture and a transparent business logic, but also the data you can't control, and which your customers constantly generate online.

Much of this data exists as text, which can make it difficult to manage. But it represents a major opportunity to listen in on what customers are saying about your business. This is where text analytics comes in.

Text and data

In short, there are two ways to analyse. Qualitatively and quantitatively.

Business Intelligence (and all sub-genres) is mainly concerned with quantitative methods, when numbers, data, structure and statistics need processing.

Qualitative analysis can process interviews, texts and observations and examine attitudes, intentions and motivations using 'soft methods' in the target group.

The Internet is the world's longest text

Interviews or open comments in surveys are often seen as part of the qualitative world. Many have been discouraged from using quantitative techniques for this type of data. But with the sheer size of data that exists in text form, using qualitative methods for processing such data is practically impossible. Nevertheless, these large amounts of text generate new opportunities, which can be explored using quantitative methods.  

Text analytics: the happy medium

Text analytics allows you to analyse text using quantitative methods. It comprises a collection of linguistic and statistical methods and machine learning. Text analytics allows you to model, structure information and find patterns in the text.

Are customers feeling your brand?

One of these methods is the so-called sentiment analysis, which performs a sort of meaning or feeling analysis. Quite simply, this type of text analytics determines which feelings are linked to a specific word, sentence or text, so whether the overall message in e.g. an article is seen mainly as negative or positive. Such information is useful for several things, as we will see below.

Your brand's reputation

In recent years, several tools have come on the market that monitor social media sites, or references to a company's brand or products on third party sites. Here sentiment analysis can help understand how customers talk about your brand, but without having to sift through comments manually.

Data is collected by 'crawling' and 'scraping' those websites whose text you want to analyse, or where you want to check specific words/phrases that you are interested in. This could be comments on your Facebook page, or searches on news media or online fora that mention your company.

There are tools on the market that can do this. These are often called social listening software. However, there is also a wide range of freely available aids that can do the same job if you have the technical knowledge.

Talking to customers - where they are

Data can be used both for product development, to find out how users use your products, or for spotting new needs that your company could fill with its products and services.

Social listening tools can also form part of the customer service communication, or can be used to avoid bad press from spreading out of control and resulting in a potential shitstorm.

Personal product recommendations

One of the latest areas to use sentiment analysis with great success is product and service reviews. Based on the user's review, you can now analyse the comments and select those products you need to market to that exact customer or segment.

There is already a wide range of options available for users of text analytics, and we will see greater potential in years to come, in line with machine learning becoming even more widespread. The technology itself will become standard and thus less interesting, while the user experience and business potential will grow in focus.

Get started

Novicell is a digital consultancy with technical, analytical, strategic and operational skills. Do you need help utilising text data, or have an idea but don't know how to collect or process the data? Then Novicell has the skills you need.  

About the author

Jens Hagbard Grønkjær
Jens Hagbard GrønkjærBusiness Intelligence ManagerSend e-mail

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