Every day, every second, millions of consumers and machines interact with each other. In the digitalized world, this interaction grows exponentially every year, and it requires careful management by companies because the data is not only big but also high speed. When we add the aggressive targets of companies to this speed, the importance of rapid data management becomes even more critical.
We can relate streaming data analytics to the large and fast-flowing waters of Niagara Falls. Suppose each drop is a customer transaction. Making immediate business decisions based on real-time monitoring of tiny water droplets would be similar to streaming data analysis.
Companies in finance, telecommunications, retail, energy and e-commerce, in particular, need real-time analysis that can transform transactions into action instantly.
Streaming analytics impacts retail customer experience:
Streaming analytics adds value through customer engagement, operational efficiency, improving revenue, renewals and brand loyalty. These are some drops in the falls. Catching one small drop can create a meaningful effect on retail customer experience.
Understanding the needs of retail customers according to different segments and making the right offers at the right time, in the right place, and in a fast way makes a difference and is similar to providing the right product to a customer in the store, which requires real-time applications.
Retail customers can benefit from real-time, location-based information, as it provides detailed in-store information while they are shopping, according to their preferences and location. Real-time, location-based analyses and offers will increase the response rate and engagement.
The communication between machines is fast:
Thanks to smart grids, production plants can be calibrated to adjust their level of operation instantaneously, at an optimum level and according to the energy demand.
With the continuous and instantaneous monitoring of energy supply and demand, not only are the power plants operated with optimum efficiency, but energy is offered to the consumer at the best price.
Data of this speed and size can be instantaneously analyzed only with the help of fast data analytics tools and methods.
Streaming analytics has grown to become the most practical of all big data strategies:
The techniques of streaming analytics are known to increase revenue, customer retention, higher operation up-time for the managed devices, and lower customer support costs. It is possible to create value from the fast data in many sectors, including banking, telecommunications, retail, airline, insurance, health and energy. This will support KPIs by increasing customer satisfaction, productivity, security and, as a result, company revenues. It is necessary to evaluate and take the appropriate action as fast as it grows, while the data is flowing.
Companies that follow and implement these trends in the coming years will make a difference. Otherwise, they will simply be a business unit that does not know what to do with most of its data.
In our digitalized world, big data is being replaced by fast and big data. Every sector needs to consider streaming data analytics to maximize the value that their data can provide.
This blog post has been published in the CMA Blog and prepared on behalf of the CMA Insights Council.
