In recent times, adaptive machine learning has grown in demand among the marketing fraternity. Also, the availability of vast amounts of data when churned through a machine learning algorithm creates meaningful and proactive marketing decisions and communications relevant to the customer’s wants. Our 4th part of Marketing Week Series speaks on the ability of Machine learning in solving problems of marketing.
What is Machine learning
Machine learning is a discipline combining science, statistics and computer coding that aims to make predictions based on patterns discovered in data. It is a great way to automate marketing activities to make them less time consuming and to provide better experiences for your customers.
With 89% of marketers saying that their customer experience is going to become their key differentiator this year, it plays a crucial role in the marketer’s best strategy to win. You want to take real advantage of data to convert visitors and increased sales. That’s where machine learning comes in.
How does Machine learning help marketers?
Machine learning-algorithms have also become indispensable in e-commerce. They enable retailers to gain more user knowledge in order to treat them individually. Therefore, retailers first track their visitors’ behavior, save it in a data warehouse, deploy a machine learning-algorithm to model this data and then, accurate next best action predictions can be made.
The key thing to remember is that as you supply machine learning software with more data, it keeps on learning and adapting. Other areas in which a machine learning application can help marketers include:
Customer segmentation – Machine learning customer segmentation models are very effective at extracting small, homogeneous groups of customers with similar behaviors and preferences.
Customer churn prediction – By discovering patterns in the data generated by many customers who churned in the past, churn prediction machine learning forecasting can accurately predict which current customers are at a high risk of churning. This allows proactive churn prevention, an important way to increase revenues.
Customer lifetime value forecasting – CRM machine learning systems are an excellent way to predict the customer lifetime value (LTV) of existing customers, both new and veteran.
True Personalization with Operational Intelligence: You see your users sharply in all their diversity and treat them according to their individual characteristics & preferences. Operational Intelligence also uses the historical database as a knowledge pool about your visitors The crucial difference: It does not analyze and model this data offline and in advance – instead, it analyzes the raw data in real-time for each individual visitor in the moment of his/her visit (real-time clustering).
Machine learning in India’s e-commerce industry
Indian e-commerce firms are evaluating various technology options including AI and machine learning.
Pramod Jajoo, CTO at BigBasket said, “One needs to derive intelligence and actionable insights from data and to do that, technologies like AI and machine learning are very important tools to make solutions more compelling. It is important to apply these technologies with the proper business context so that one can use these more efficiently. “
Similarly, Rajesh Dalal, VP – Technology at MakeMyTrip quoted, “These technologies are helping the ecommerce industry understand their customers better. In an industry where customer is top priority, connected data helps us understand their travel behaviour in a much better way and helps us in offering them customized packages.”
For an e-commerce firm, there are various stages to the use of intelligence. You have inbuilt intelligence, stylist designers, analyzing various trends, what people are going to buy and based on it you decide. Beside, product’s conversion rate and demand is taken into consideration. So, it is a strategy of machine learning combined with human intelligence which makes you procure those particular products.
What might future solutions look like
The marketer has a proliferation of channels at disposal to adapt and use them effectively. To make the customer experience consistent and coherent, you’ll need to make thousands of decisions and machine learning will do this for you. For this year, think about machine learning on two fronts: how it can impact your customer experience and how it can help you better do your job.
(References: optimove, odoscope, yieldify)
More on Machine Learning and how technology is changing the future of marketing at eCommerceTrendz Bengaluru 2017, which takes place on 18th May in Bengaluru. Click here for more information and to register: /register/