Structured data means the data which is used for transactional processing like air ticket booking and it is stored in relational tables in conventional databases.
The other type of data is unstructured data which is mainly used for analytical purposes. This type of data contains image, video, text, speech etc. With the growth of social media, smartphones, smart devices, blogs, forums, internet of things this type of data is growing at a very fast rate and relational databases can’t be used to store and mine such high velocity data. So to draw meaningful insights from such type of data big data techniques are used. So Big Data consists of 3 V’s namely volume, variety and velocity. Variety of data can be explained by the following picture.
With the growth of technology more people are going for personalization by connecting their devices to the internet. Embedded sensors in these devices are used to collect data and these can easily be controlled remotely with the uses of cloud services. A simple example could be your mobile phone synchronized to your watch, your washing machine, your coffee maker and other devices. So this gives rise to user specific data and big data analytics enables marketers to draw conclusions based on such type of data. Browsing and purchasing history, facebook likes, movies watched, places visited gives insights of what a customer wants and how much he/she can pay. This data can be used by CRM systems for market segmentation and also the preferred mode of communication.
To store real time information, big data makes use of distributed file systems which provides scalability of storage and processing.
The use of big data allows companies to develop a new kind of relationship which is unconventional and user specific. Big data gives opportunity to use micro-economics at its minutest level. Using this, a new type of STP and marketing mix approach can be followed by organizations, which is based on users’ behavior. Companies can easily get to know the target segment of their product and also how to communicate to that particular segment. Online activities of users also give information about the optimal positioning strategies that can be followed by organizations. Marketing teams analyze user’s behavior to draw correlation between the requirement and their offering. By this they get to know about the optimal marketing mix which should be followed for maximum utilization of marketing budget. An example of efficient utilization of big data in making marketing strategy could be Walmart. Walmart uses almost ten different website to feed data into analytical system.
Also as big data is cheap; it brings competitiveness in the industry by enabling small firms to take its advantages. A simple example could be companies using google analytics to measure and manipulate data flow. Data analytics enables firms to segment markets in more sophisticated ways so that firms can deliver value to each segment based on their requirement.