Who has not already wondered about that shopping suggestions on Amazon? Or wasn’t glad about potential new acquaintances Facebook, Instagram & Co have picked out? The secret is Big Data – even if there is no data about a very person available yet, its behavior can be predicted based on the behavior of the crowd.
The transparent citizen has been reality for a long time. We cannot hide, we leave traces and our behavior is predictable. Even if we haven’t left any traces within the web due to several years of sabbatical on a desert island or consequent denial of social media and smartphones, thanks to our friends and fellows our doing can be figured out and predicted!
At the i-KNOW 2017, Luca Maria Aiello of Nokia Bell Labs gives insights into the world of „Predictive Analytics“, the basis for market optimization, shopping cart analysis and efficient customer retention.
„We are not that special“
Even though individualism is a huge priority in 2017, “Predictive Analytics” teaches us better: We are not that special! Based on captured data of the crowd behavior many of our steps are predictable in advance. When will you reply your next email, what and how much will you buy next, what song will you listen to next via a streaming service? Scary, but individual behavior can be predicted with 90% probability.
„We are similar to our friends“
The power of interpersonal relationships reveals a lot about our behavior in social media networks. In our analogue world it is very likely that two strangers will like each other in case they have a common friend. This very easy principle was transferred to the social world. the friendship recommendations we receive are not chosen arbitrarily, they result from collected data. The same principle is applied to the prediction of buying behavior: If I have a friend who got himself a new product, there is a high probability that I will follow suit.
„Anything is measurable“
Anything? „Yes, anything“, Aiello says. Even though beauty is in the eye of the beholder, people like to compare. Based on these comparisons, patterns regarding personal taste can be recognized. These patterns can then be scaled and – voilà – beauty was made measurable. Machine vision has progressed so far by now that it almost matches the human eye and the human sense of beauty.
While Business Intelligence enables companies to systematically evaluate collected data in order to take better operative and strategic measures in the future, “Predictive Analytics” is going one step further: It also forecasts how the collected numbers will develop and thus becomes an indispensable element for all e-commerce service providers. Those who have a notion about how to improve the acquisition of new customers, how to make long-term customer retention work and which products are displayed to which customer at what time, will sooner or later take the lead!