Predictive Intelligence tools are helping companies improve their bottom line and reach their customers effectively. The term “Predictive Intelligence” might sound like an advanced tool that belongs in a Science fiction film. Nowadays, marketers are using this technology to deliver what their customers need.
Also referred to as Predictive Analytics, Predictive Intelligence is composed of Statistics, Data Mining, Algorithms, and Machine Learning. It gives companies a powerful new edge, compensating for the ever-expanding array of choices available on the internet anytime, anywhere. It is a method of creating a customer experience that is unique and personalized by monitoring customer behavior and build a profile according to their preferences. This customer profile data is later used to forecast customer expectations.
Are you still thinking whether Predictive Analytics is a powerful marketing tool since the arrival of online shopping or not? Read this blog further to know the 5 ways in which companies can use this technology to take customer service and sales to the next level.
Forecasting Customer Need
Organizations can use predictive analytics to decisively forecast clients’ needs, at times even before the individual has made up their mind. Predictive analytics can give early indications of any change in customer behavior. Furthermore, predictive capabilities enable brands to be proactive, empowering them to tailor their messages in expectation and successfully serving the customers. It’s a methodology that allows organizations to give predominant customer service. In a world where it would take much longer time to analyze the numbers and extract behavioral patterns of customers, AI can do it in the blink of an eye – something we expect in our hyper-personalized CX delivery models.
Machine Learning algorithms can:
- Clearly, detect which customer segments should be added and removed from the campaigns.
- Match the customers to the products they are more likely to use
- Avoid the promotion of certain stocks to buyers who always return items
Predictive analytics can also help organizations allocate their resources more efficiently and productively. The retailers can combine insight from their store footprints, logistics and customer behavior to perfectly plan staffing levels in advance. This will help the customers to have a smooth, better and overwhelming experience. Therefore, companies can become more efficient, streamline costs and reduce resource wastage. Also, customers can receive timely and personalized experiences.
Predictive analytics empowers organizations to upgrade the client experience as far as possible up to the delivery day. With a number of clients requesting “same day” and “next-day” delivery, predictive analytics helps retailers and their transportation accomplices safe and on-time delivery. The predictive analytics allow the drivers to have a better experience during their journey as the transportation departments can convey them earlier what adjustments need to be made on transport routes to manage volume, thereby impacting the overall customer experience.
Creating a personalized experience is all about delivering customers the right message at the right time, on the right channel.
Imagine a world wherein the retailer knows precisely what a customer needs even before landing on the company’s site or application. That is the experience that predictive analytics can exactly deliver.
Through data-driven innovation, we can make a customized collection, using thousands of products, each and every day — creating a client experience that is genuinely engaging and relevant.
In a personalized retail marketing environment, sellers weave varieties, selections, price points, shipping time, the shipping cost in a way to create a long-lasting customer experience.
Churn Reduction of Customer
“Predictive analysis” can be utilized to distinguish clients exhibiting a high churn risk and assist organizations with taking proactive attention to upgrade client experience and serve their requirements better. Retailers have quite a while ago, looked for methods for decreasing client churn, the level of once faithful buyers who have quit gaining an organization’s products or services during a particular time allotment.
Also called client attrition, client churn is a basic measurement, given that it’s far more affordable to hold existing clients than it is to secure new ones. For example- a denied loan request can alert a financial institution about the customers presenting a high churn risk.
We can say that predictive intelligence is an incredible asset for organizations to have in their armory and one that they should utilize deliberately and regularly to create an overwhelming customer experience. These organizations demonstrate that it’s conceivable to foresee the future and do it such that it keeps customers happy and returning for additional.
It is also true that this technology has evolved so much to the point that businesses can’t ignore some new innovations — like a system that offers recommendations on the basis of customer traffic patterns.