Marketing In The Era Of Machine Learning
Dr. A.M. Sakkthivel, Professor, Skyline University College, discusses how companies can use machine learning to attract and retain new customers.
Marketing today is becoming extremely complex due to mounting competition and the dynamic behavior of consumers. Companies are always looking for ways to manage this and to reach out to target consumers for their survival, sustainability, and of course, growth. However, such methods are easily imitated by competitors, leading to the company’s failure to create excitement and value to target consumers.
Today’s consumers are enjoying the benefits offered by companies and they move around to wherever they can get better bargains and benefits. Such a move forces companies to constantly create and offer promotions to attract consumers to generate much-needed revenues to run their businesses. Such consumers are called “price warriors” and companies can’t profit and grow when they focus too much on them.
Instead, companies should create a loyal and contributing consumer base to achieve their expected profit and growth. Creating a loyal consumer base is a herculean task, as competing companies will constantly target and attract consumers through their continuous promotional offers. However, companies should hold on to their existing consumers and convert them into loyal customers by creating constant excitement, surprises, and benefits.
How does a company create continuous excitement and surprises to make sure that its existing consumers come back and spend more money? This is where the role of technology in marketing comes in. Companies can use technology for advertisements, communications, events, and services to attract consumers and retain their loyalty.
With people’s ever-shortening attention span, companies need to use technology that is highly interactive and multifaceted. This requires companies to design an integrated system of marketing that includes capturing consumer data, analytics, and the development of AI systems that includes machine learning designed to develop and act on its own with the right training and instructions.
Numerous companies are experimenting with machine learning and using it in different marketing aspects such as the monitoring and measuring of offline and online consumer buying behavior, deciding on profitable dynamic pricing, ensuring sales, targeting efforts towards relevant market, generating personalized promotional offers, measuring website experiences, identifying sentiments of target consumers, and predicting and generating counter-measures to customers’ churn rate, among others.
Machine learning could be of more use in products and service-oriented organizations that require frequent footfall from consumers to generate revenues for their survival, sustainability, and growth. It is, therefore, important to generate clean and enormous amounts of data because it will help the machine learning system train and understand patterns of purchase of products and services and for it to make predictions and alert the companies of what is coming.
It’s also important to set the priorities and functions while training the machine learning system to suit the requirements of a company, such as predicting consumer churn, predicting their next big spending, predicting most favorable products/services to make personalized promotions, and even personalized pricing to attract consumers.
Although the machine learning system is an autonomous one, it is important to have continuous human interactions and interventions to align machine learning with the ongoing strategic and operational aspects of a company. Such alignment will enable the system to inherently understand requirements and patterns of the company’s strategic and operational aspects to aptly generate suitable and useful responses. Hence, companies need to focus on using systems like machine learning for their marketing strategies and design them for greater use. Doing this will help companies successfully navigate the turbulent waters of the market with its ever-mounting competitions and the ever-changing consumer behavior.