This is the Big Data Age. Are You Getting the Most from It?
Today, there is an almost unimaginable amount of data available to companies. What do you do with it all?
Everyone has heard of big data, and there is no shortage of media buzz around the millions that the biggest companies are investing in big data analytics. More data is key to developing business strategies and marketing initiatives that are better aligned with customer expectations and trends, and this vital information is all wrapped up in that unfathomably vast sea of data.
Where does it all come from? Quite simply, everything we do online creates a parcel of data. Every purchase, product review, social media comment, retweet, even every web search we make. It is all grist to the mill in data analytics.
However, it is not the sort of data that can be simply plugged into a computer program and expected to deliver strategic insights. Sure, if you have 80 percent of five star reviews for one product and only 50 percent for another, that is ready made data that you can immediately use. But most is in the form of comments that are delivered in natural language.
Natural language processing
As the name suggests, natural language processing (NLP) is an area of data analytics that uses algorithms to process data that has been provided in natural language. A simple example might be comments submitted on a business’s contact form such as received my external widgets today, couldn’t be happier, they are really widgetty, thanks, guys! Compare this with an alternative, such as waited three weeks for my internal widgets to arrive, only to receive a box full of external widgets. This company is a joke.
NLP can immediately identify the sentiment behind these kinds of messages, providing you information on which product lines, sales channels or markets are attracting positive feedback and which are not.
Where to start?
In Alice in Wonderland, the Cheshire Cat remarked that if you don’t know where you want to end up, it doesn’t matter which way you go. This is a basic tenet of business strategy that we would all do well to remember.
The level of content understanding that you need – whether it is on the macro level, for example to identify that we have “one positive and one negative” feedback above, or whether we need to understand that the positive feedback related to the widgettiness of the external widgets, while the negative concerned both delayed processing times and the wrong sort of products delivered when ordering internal widgets.
There are advantages to both. Macro understanding will give a picture of market trends according to categories of market, product lines, demographics in terms of sales patterns and general feedback trends. It is handy for classifying and categorising your data, extracting keywords, understanding critical topics and removing duplicates.
The advantage to micro understanding is that it will automatically provide that “big picture” analysis, while at the same time delivering so much more, improving your understanding of customer experience and trends down to specific product lines, issues, locations and dates.
Ultimately, it is important to remember the advice of the Cheshire Cat. Sit down with your data analytics provider and decide where you would like to go. Then together, you can get there.
How to Make Your Big Data Useful