Propensity modelling is customer insight technique which utilizes past observation analysis to predict future behavior. A single view of the consumer is created by data analytics so as to identify who the target is for the current or new products and/or services depending on the value they expect to contribute. Propensity simply predicts the likelihood that a customer will behave or act in a certain way in future.
Regardless on the status of your business (big or small), sometimes it may lose track of exactly who the loyal customers are and the products and/or services they are exploring the most. Understanding consumer behavior is critical, this is because it helps in optimizing the current business items in ensuring that there is success for new items in the market. Propensity modelling usually takes place at the divisional management stage, even though a number of operational levels are involved; mostly when they hold information concerning customer behavior.
For expert analysis, propensity modelling offers extensive market research on which products or items will work greatly to your advantage. Most companies usually provide insightful propensity which gives them in-depth look at your current customers as well as soon-to-be customers. This is tactfully done by understanding the characteristics and behavior of the customers. It is a detailed and effective process focusing mainly on customer relation.
Consumer behavior is often not easy to discern through basic analysis of the company’s data but initializing propensity will bring an efficient approach together with sharp eyes to help distill value from sample complex data relationships.
According to many companies dealing with propensity modelling, most of them collect data from both the client and the consumer to know what and how the previous action was. Let’s say you have a business and you want to know who your customers are and what they buy the most, this model will work for you.
The following process is generally what propensity encompasses:
– Data collection showing what your customer base is
– Linking the collected data using analytics and indicators
– Coming up with a single view of your customers together with their behaviors
– Identifying from your customers which of them is relevant to the product as the target market when it (the product) is introduced in the market
Propensity modelling provides a single view by computing consumer’s behavioral predisposition to purchase certain products or/and services. It forms an ‘Inside-Out Analysis’ which explains why understanding the internal aspects affecting a client’s business is important. Other elements connected to this include; market sizing, trend analysis and competitor analysis – all falling under ‘Outside-In Analysis’; a type of analysis relating to proper understanding of all market and industry aspects that impact the customer, and at the same time external to the client’s business.
In actual sense, propensity modelling will help your business to target the right customers, optimize resources and most importantly increase the probability of positive response from marketing campaigns by doing away with the infamous ‘broad brush’ approach. So far it is a technique that has proven to be not only efficient but also an effective method of prediction when it comes to future consumer behavior.
