Imagine how the world would change when any ad you receive is only about a product that interests you.. How beautiful would it be to receive information only on relevant products? How efficient would it be when you get all the necessary grocery items in the first aisle? How much can mankind gain by being able to predict their illnesses by looking at current medical history and symptoms??
All of this can be done using the power of predictive analytics.. Many companies are already using this and improving and improving their targeting. They can get more than 100% responsiveness of your marketing campaigns by predicting customer needs and communicating only with relevant products.
Then, What is predictive analytics and how can it help?
According to Gartner:
Predictive modeling is a commonly used statistical technique to predict future behavior. Predictive modeling solutions are a form of data mining technology that works by analyzing current and historical data and generating a model to help predict future outcomes..
In a nutshell, predictive analytics uses past trends and applies them to the future. For instance, if a customer buys a smartphone from an e-commerce website, you may be interested in your accessories right away. Could be a potential customer for the phone battery in a few years. Nowadays, the chances of you buying an accessory from a competitor's smartphone are relatively bleak.
While the example may seem simple, imagine doing this for thousands of categories you might be selling. Within those thousands of categories, there may be multiple options (hundreds of covers, cases, optical pencil…). What's more, even if you have a thousand visitors every day (a small amount from many electronic retailers), predicting the next purchase without a data-driven decision for these customers could become impossible.
This is exactly where predictive analytics will come to your aid. (remember that Amazon helps you with, you may also like ...).
I understand how predictive analytics can help, What do i do next?
If you are a business owner and want to take advantage of business analytics, you must set up an analytics team. I'll cover the details of setting this up sometime later. This post is for people who want to learn the art of predictive analytics.
Below is a typical life cycle of predictive modeling:
Steps to build a predictive model
The first step in any predictive model is to collect data from various sources. These may be data you have about your client (as pages visited in the past, products purchased in the past) or data that the client has provided (for instance, address, Name, age, etc.).
This data should be cleaned and organized in a structure so that it can be easily analyzed. This structure must be synchronized with various commercial hypotheses. For instance, if the commercial hypothesis is that an age group / particular gender may be more likely to buy a certain set of products, age and gender must be attributed at the client level.
Once these data sets are ready, we use various predictive modeling and business understanding techniques to gain various business insights (gold nuggets). This knowledge can be used in website design / marketing to increase efficiency.
In one of the future posts, we will go over these steps using a dataset and case study to highlight these aspects.
Meanwhile, if you have an example where predictive modeling has helped or a business problem where predictive modeling can help, let me know.
