Experts predict that by 2030 predictive analytics (the ability to use information to predict future actions) in marketing will be much more refined. Today we consume many products and services daily. Some of these purchases are easy to predict – a student will need books or a new parent will need a pram, etc. However, most of the goods and services we purchase involve a decision process influenced by many factors including our income, values, mood and experiences on a particular day (all of which shape our purchasing preferences) as well as our awareness of the options available to us
Consumers are, thanks to the internet, more informed than ever before and through the sharing of information such their purchases, likes, dislikes and values online, huge amounts of data are being created. That’s why it’s called “Big Data”. The vast amount of data is so massive that usual data processing applications are incapable of managing it all, let alone analysing it.
As these massive amounts of data are becoming more open to tracking and analysis and the ability of information technology to deal with the data increases, opportunities are being created to understand the needs of consumers as individuals and provide them with purchasing options personal to them. Big Data contains not only information of individual preferences but also the potential to discover social trends of certain groups with similar preferences. These trends will make it easier for marketers to understand potential customers better and, based on the past actions of actual customers, predict which products and services are most suited to those potential customers.
Online advertisements are generally disliked and if online advertising wants to survive, it must become less irritaing and more artful in order to draw-in the customer by entertaining or informing consumers rather than annoying them. The power of seeing a product in a setting that conveys a feeling that the consumer wants was first used to help sell products in photographic print advertising and TV commercials. It is now the reason behind “product placement” on TV. Most recently, this type of visualisation has been used in vlogs and on the Instas of social influencers that link a personal story with the use of particular products and services. At the same time, online advertising has become more targeted. For example, if you have ever added a product to your shopping cart of an online retailer but not purchased the product, chances are that you will have started seeing ads for that product when you visit other websites that feature advertising. You may have also seen ads for products based on your recent purchase. This type of personalised advertising can be useful rather than invasive or annoying.
The leap towards big data will allow marketers to understand consumers on a more personal level and the evolution of online visual media will allow marketers to provide individual consumers with very specific products and services, matching their personal needs. Advertisers regularly use images and words to link desirable lifestyles and feelings with their product because advertisers know that people are more likely to buy something if they can easily see how using it in a way that makes them feel good. By 2019, leading information technology company Cisco predicts that 80% of the world’s internet traffic will be videos. This speaks to how attracted human beings are to things that stimulated their visual senses.
By anticipating individual consumer’s future needs, big data driven marketing creates four career opportunities in marketing: the Big Data Wrangler, the Purchase Prediction Analyst, the Multi-Marketer and the Marketing eMediamaker will all play a key role in the big data cycle. For more information on these careers please follow the hyperlinks.