In this day and age, it’s hard not to be be overwhelmed by information. We get it via newspapers, television shows, advertisements, newsletters and social network. We’re often engaged in generating information ourselves, each time we use the internet to blog, post pictures, comment on an article or debate on public forums. In fact, every time we use social networks, we are sending out a lot of data, a lot of which may seem useless to most, but which is very valuable to many businesses, who are looking to gain a deeper understanding of their customers.
It seems simple enough and of course, social networks are used by various companies to gather different kinds of data. A bar will want to know what its regular customers like to drink, while a fashion retailer would want to track which runway trends have generated the most enthusiasm among shoppers. On their part, customers are more than happy to share reviews, preferences and opinions about the products and services they use. This gap between what the customers want and what companies are willing to supply can be bridged using data that is floating around on the internet, thanks to social media. For instance, a restaurant can now use Foursquare and Facebook check-ins to see when a particular customer likes to visit and what she usually likes to order. So the next time the customer comes in, they can offer a discount on her favorite or most frequently ordered dish. By engaging on a personal level like this, the restaurant makes one of its regular customers special, thus ensuring repeat business and possibly, good word-of-mouth and social media publicity.
Obviously, the amount of data that is available online is immense and wading through layers of irrelevant data to get to the relevant nuggets is a massive task. While information is definitely more easily available, the question remains of how to see patterns of behaviour or get specific, personalized data. Customers and their preferences can be studied anywhere – blog posts, comments, forums, Facebook and Twitter updates, Foursquare check-ins, Instagram images, but the diverse nature of these platforms ensures that the forms and channels through which information comes are equally diverse. Often the patterns are small enough to be missed, and it is difficult to get hold of each individual customer’s information.
By adopting a solution like QlikTag, companies will find it easier to get straight to the relevant data, as well as gain a deeper understanding of each customer that they have. For example, if an apparel brand uses QlikTag, it could print QR codes on labels attached to clothes. Once a customer scans the code, the product information would be sent to a database, where a profile for that particular customer and his unique buying history may be stored. So if the customer has bought a brown leather jacket, this information is stored and the next time there’s a sale on leather jackets, or a new line of leather apparel is launched, the customer would be notified.
