Text mining is one of the most powerful tools you can have for real world marketing. Also known as text analytics, this technology leverages artificial intelligence to power Natural Language Processing. You can discover deeper insights about your verbatim comments without resource-intensive manual processing. Projects that took your marketers days or weeks to work on end up getting processed in hours with text mining applications.


What is Text Mining?

Natural Language Processing takes your unstructured data and formats it into a structured form. This process is important because your analytics software needs help to understand conversational English. Text mining standardizes these comments so the system can use them properly for analytics.

These solutions work best for large unstructured data sets that you need to examine closely. You can learn about the sentiment behind a comment, discover overall themes, and get insights that would otherwise be kept behind unstructured doors.

Since most of this process is automated, your staff has more time to work with the data and find valuable insights that inform decision-making. It’s also a way to limit the subjectivity of some forms of analysis, which also reduces the opportunities for bias to be introduced. While eliminating biases completely is challenging, as biased learning data can introduce these issues to a machine learning model, it standardizes the process across all results.


What Kind of Problems Can Be Addressed With Text Mining?

The biggest problem that text mining fixes is the sheer amount of time it takes to code a set of unstructured data. It’s a tedious and time-consuming task when done manually, and can lead to employee burnout and disengagement. It also takes an unrealistic amount of time to work with very large data sets, which means that the insights in that information would not be available for marketers.

Text mining makes it easier to update the learning model of the machine learning technology and drives greater accuracy in the results. Your marketers’ productivity increases due to being able to focus on high-value tasks rather than manual processes. This also drives your overall costs down.

Text mining can be useful in virtually every industry, as most companies have an overwhelming amount of unstructured data that they’re not using to the fullest. You’re able to categorize this information, classify different entities, understand the topics present in the data, and more.


What are the Main Steps in the Text Mining Process?

While the exact steps vary based on the text mining application that you’re using, there are several broad steps that most follow. The first part of this process is to bring the data together, whether you’re collecting it through a survey or pulling it from social media or a software system. Make sure that you’re able to easily export and import this format into your text mining software.

If the format that you’re using for your data isn’t natively supported by the software, then you’ll need to convert it prior to use. In some cases, your text mining solution supports API access, which can make it easier to get this data into your system.

The next step involves the Natural Language Processing technology that your text mining solution uses. It looks at this data and analyzes it so that it can go through the text and identify important parts of it. This automated process doesn’t take long, as these applications are capable of awe-inspiring speeds when going through large sets of data.

The next step is more involved with looking at the text data. The system starts to look for the context and meaning of verbatim comments. It picks up on relationships between different parts of the comments.

In the last stage, the actual text mining occurs. This step discovers the context and sentiment in comments, trends and topics that occur frequently, and other deep relationships. It’s also capable of creating summaries of your documents and developing complex taxonomies automatically.


Text Mining Examples in Marketing

There are many use cases available for text mining in marketing. Here are some of the most common you should consider.

  • Learning about positive, negative, and neutral reactions from your audience: Sentiment analysis is an excellent tool for marketers, as it allows you to quickly see what the reception is to the topic that you’re studying. When you have a good understanding of your audience’s reactions, you can tailor your marketing campaigns based on that information.
  • Categorizing survey responses: Group survey responses into broad topics or get granular with it, depending on your needs. You can focus on the areas that are most important for a particular campaign or use more of a top-down approach to the studies. Recurring themes may require closer examination, so you can conduct more studies that focus specifically in those areas to get more information.
  • Translating and scoring survey results: Are you working with more than one language on your survey responses? You don’t need to translate that as a separate step before it goes into your text mining application. Simply choose a software that supports the languages you see the most and it can automate the process.
  • Testing your ads: Creating good ads is as much of an art as a science, and it requires a lot of testing. You can get an objective view of how well your ad copy and creatives are doing with the help of text mining. This allows you to effectively split-test ads, website designs, content, and other marketing assets. With more focus on highly personalized and relevant experiences, this is a good way to power those efforts and learn what your audience responds to. You’re able to compare your ad response rates over time, whether you want to look at them on a channel by channel basis, or directly comparing the campaign results to one another.
  • Gauging interest in a new concept: Even when you do your best at developing a concept that should appeal to your audience, sometimes the latest project just falls flat. You can start to troubleshoot why that happened by using text mining and open ended survey questions to see what your audience is thinking about the latest products, services, and company moves. By gauging the interest in a new concept before you move forward with the project, you can handle development much more cost-effectively. This helps you avoid particularly high-profile failures, as a small study may end up with respondents that are more on-board with the concept than a more representative sample of your audience.
  • Understanding the customer experience: Do you know why your customers feel the way that they do about your customer experience? It’s not enough to know if they are happy or not. You need to know the why behind it if you want to excel at marketing. Text mining gives you the why so that you can continually improve the experience and the marketing tools that support it.
  • Discovering your customer satisfaction ratings and the meaning behind them: Your audience gives you a lot of feedback on whether they’re happy or not, you just need a way to analyze it. Use text mining to look through customer service records to identify customers who may be open to purchasing again, those that are upset with the company and need attention, and others that may need a push to move away from being ambivalent in either direction.
  • Conducting market research: Closed questions only give you so much information when you’re conducting market research studies. Take verbatim comments from these studies and analyze them efficiently with text mining.
  • Tracking the success of new products and services: You want to know how well your new products and services are doing now, not weeks or months from now. Automating the analysis through a text mining tool means that you can get near a real-time understanding of how well a product launch is going.
  • Learning more about Net Promoter Score results: Many companies point to their NPS score as a way to show whether they’re doing a good job with the customer experience. However, it’s just as important to understand why your audience chose the responses that they did. This is another way that you’re diving deeper into the data and getting the why behind this information.
  • Finding out whether employees are engaged or disengaged: Are you running into problems with your marketing campaign because the team isn’t engaged enough to execute it? Your back end operations have a big impact on the customer experience, so checking in on your team is also important.
  • Finding new business opportunities: Open ended survey responses allow you to find replies that are outside of the norm. Sometimes your customers have adopted a product or service for a use case that never came up in research studies. Expanding horizontally or vertically may be possible based on this data, which can offer an excellent approach to building your business.
  • Setting up knowledge management for marketing assets: Trying to wrangle an out-of-control content database for marketing can be challenging. Text mining offers an automated method for developing complex taxonomies and sorting large sets of text data.
  • Using customer service data for marketing strategies: Your customer service data is a marketing goldmine, but it’s often overlooked due to the logistical challenges of processing the information. Text mining eliminates these concerns and allows you to find out more about your customers, what they like, dislike, and how to keep them loyal and happy.
  • Creating better context for advertising: Contextual advertising helps you improve conversion ratios and remain relevant to an audience that is increasingly becoming ad blind. Text mining helps you pick out common trends, contexts that a particular market segment is interested in, and other details to improve advertising campaigns.
  • Powering business intelligence software: Your business intelligence data is greatly improved when you have a way to bring unstructured data into it in a usable form. Use this information for data-driven decision making so you know how best to invest your marketing budget.
  • Providing hard data for reports and presentations: If you need a way to make your case to upper management, having powerful visualizations in helpful reports and presentations is one way to make it happen. Text mining creates structure out of unstructured data, so you’re able to use it in this fashion. Customizable dashboards are another way to easily access the data in a form that’s user-friendly for most marketers. When you can easily work with the data, that makes it more accessible to power all types of marketing efforts.
  • Improving the value of social media comments: People are more than happy to comment on social media, but harnessing that data is hard if you’re doing it manually and have a relatively active page. Text mining makes this process more efficient and allows you to leverage such a large and frequently updated data set. Consistently looking at your social media comments is also a good way to stay ahead of any public relations problems you may encounter. You can execute your crisis communications plan as soon as you start seeing negative comments pop up, rather than waiting for it to reach a head and potentially get out of control.
  • Eliminating personally identifiable information from survey comments: Everyone is more privacy conscious these days, so eliminating PII when you’re working with data saves you a lot of headaches. Text mining understands what named entities are and can scrub the data clean automatically. This filtering method can work for any data that may not be useful for your results. The cleaner the data is when it gets analyzed, the better the result that you’ll get from it.
  • Creating performance benchmarks for marketing campaigns: Get more benchmarking metrics for your marketing campaigns so you can study how customer sentiment changes over time, the ways they react to new campaigns, and isolating the characteristics that lead to a successful marketing effort.
  • Powering Voice of the Customer programs: Voice of the Customer programs are greatly improved when you have a cost-effective and productive way of working with audience feedback.

Whether you’re using text mining for a one-off study or an ongoing series, your marketing team will benefit from its implementation. It takes some time to fine-tune the results for your marketing team’s use cases, but once you get it dialed in, you’re going to wonder how you ever did without it.