As I was checking The Weather Channel , the graph in the bottom right caught my attention. It summarizes the "weather related" Twitter discussions in the Indianapolis area.
Pretty neat. Huh?
This got me thinking about the application of text analytics in customer survey research. At Walker, we generally see the following use cases:
- Click - Click - Read: This phrase originates from one of Walker's clients who leverages text analytics to increase the awareness of customer comments within the organization. This particular organization uses the categorization model as a navigation tool for employees to filter down to the relevant customer comments.
- Adding context to quantitative data: Quantitative customer survey research provides directional improvement areas, but some designs lack the next level of detail, such as what specifically to fix. This is where the text analytics can come in handy. It can explain the unstructured customer comments. When used together, the quantitative input and the text analytics can be a very powerful tool for prompting action.
- Refine the customer survey: Text analytics help identify emerging concepts or areas that were overlooked during the survey design phase.
- Extend to other sources: The categorization models serve as a way to link customer survey research to other sources of unstructured data, such as social media, sales rep notes, chat sessions, etc.
How are you using text analytics within your company?