Using Text Analytics in Marketing
Text analytics, also known as text mining, is the process of using machine learning technology to extract information from messy, unstructured text-based data and organising it so it can be analysed. Unstructured data is very common. It is information that is not easily stored in a database or spreadsheet. Emails are one such text example as the body of messages are not a standard format. Other examples include: tweets, reviews, invoices, support tickets and call centre data.
Machines organise the data by natural language processing (NLP). One such process is ‘Clustering’ which classifies similar data into a group allowing you to house together the specific information you want to look at such as property types placed into location and value. There are many software packages available. You can try Google’s NLP software for free.
How is this data useful to your company? It allows you to find patterns and trends in customer behavior and focus future advertising based on what you find. By extracting keywords, names, topics, or prices you can discover what is most important to a customer and target your messages to them. It can also improve your customer service by allowing you to discover what problems keep coming up they are discussing, what products they refer to most often. You can see negative versus positive comments. By identifying recurring words that appear in social media posts you can discover what customers think of your brand or what topics are being discussed in your field.
Now all you need to do is decide how to visualize your information and we’ve covered a few ideas in our blog post here.