Text analytics for SMEs

Mining social data with text analytics

The Internet is a busy place, and social media is an ever-growing piece. Hundreds of thousands of tweets, status updates, pictures, and reviews are posted every minute, and that number just keeps going up. For a small or medium sized business (SMB) owner, it is more important than ever to properly manage your online presence.

That being said, properly managing large amounts of social media data (reviews, mentions on twitter, and so on) as an SMB owner requires massive amounts of your most precious resource: time. You simply don't have the time each day to read through tweets, reviews, and every other online mention of your business.

But you still need to listen.

Text analytics is an amalgamation of processes beginning with input gathering and culminating in pattern identification and trend analysis – is the best way for an enterprising SMB owner like yourself to manage your online presence. Rather than manually reading every mention of your business or your competitors that you can find, you can have machines do the work for you.

More important is the sheer volume of input a good text analysis program can process. While responding to individual complaints can cultivate a positive reputation with your customers, different people can have wildly opposing views of the same product; if you base your decisions off of only a few data points, you could be alienating a significant portion of your customer base.

This is where the processing power of a text analysis engine proves invaluable. By gathering large quantities of data and identifying named entities, you can identify patterns and trends that will show shifts in customer attitude over time.

Fortunately, you don't have to worry about implementing text analytics yourself. There is a myriad of social listening, social marketing, or customer experience management tools out there that provide a complete system; which makes the pricing affordable to SMBs.

Of course, while a computer can gather the information and identify trends and patterns, a person is required to decide what to do next. There are two things to keep in mind when using a text analytics tool: first and foremost, base your decisions on those trends or on comparisons, never on point data. Second, use a wide view of your market and competitors – you have the ability to listen to more than you ever could before; use that ability.

  • Noah Blier is a marketing intern at Lexalytics, one of the leading providers of text analytics and sentiment analysis.