The importance of adaptive models in business is most present when it comes to changes in real-time. In the business world, real-time means as fast as a customer demand can happen - which is really fast, as they're not communicating by hand-delivered mail anymore, and often not even directly, but instead by a Tweet or post on social media. In the event of a sudden change in customer sentiment, businesses don't have the time to meet a customer's new needs. Different from predictive models that need to be re-focused following a change of behavior in the customer base, adaptive models will react automatically.
Like a child that touches a hot surface for the first time and quickly pulls away, an adaptive model effectively learns the difference between a positive or negative response. To do this, adaptive systems look at data in a fluid form. The basic attributes of a customer are collected, such as age or gender, and many other attributes depending on the context. The customer response will then be related to the customer attributes. An example of how adaptive analytics work in real-time is when an 80-year-old woman calls her cable provider and the customer service representative recommends a particular package or channel for her to purchase. When the woman does not accept that particular offer and requests something completely different, the model will instantly readjust to avoid making the same error for not just this customer but for customers with similar attributes. If enough elderly ladies reject offer A and ask for B the business will automatically adapt to this change in demographics. In reality, of course, the models may look at hundreds or thousands of attributes not just, as in this example, gender and age.
Learning to adapt
As a special breed of predictive analytics, adaptive analytics is a very influential technology for businesses. Today, getting actively recalibrating intelligence out of your data, rather than depending on pre-scripted responses, is what gives businesses the competitive edge they need to survive. While big data and automation are just the beginning, we need to continue thinking ahead and learn from the past and present to continuously evolve models that provide the maximum benefit possible for the adaptive enterprise. This is the only way that businesses will be able to keep up with the changing demands of their customers and meet their needs moving forward. Survival of the fittest has always been a measurement for how organizations have been successful over long periods of time. Adaptive analytics help businesses today to stay fit and agile with an eye on adapting to future needs. Is your business fit enough to survive?
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