Machine Learning in 2020 has changed the landscape of digital transformation by utilizing parameters like behavioral targeting, micro-targeting, personalization, etc. The conglomeration of talented resources for Artificial Intelligence solutions and Machine Learning automation gives a new face to the digital marketing arena. Tech giants like Google, IBM, Amazon, and Netflix have employed Machine Learning for years to understand customer behaviors, improve search results and customer support, and achieve accuracy in inventory management and pricing. This advanced technology helps in drawing sales forecasts and predictions while fine-tuning the propensity models to achieve focused marketing strategies. Let’s see how artificial intelligence in ecommerce plays an instrumental role in marketing.
Helps in effective data visualization
Right data visualization is integral in setting up company’s goals and operational strategy. It helps you in making correct decisions at the appropriate time. Machine Learning conducts continual data assessment by which it facilitates active monitoring that enables to notify key personnel immediately in case any data anomaly is noticed. With the detection of irregularities, you can aim for more precise financial models and rules. Also, the decision-makers of your organization can speculate their queries/concerns to the systems and get easily comprehensible answers.
Facilitates easy product marketing
Machine Learning has proved incredibly helpful to organizations for promoting their products and consequently making an accurate sales forecast. ML consumes an unlimited amount of organizational data and creates a report based on which you can review the sales and marketing strategies of your company. As your model is trained, the ML gets you the highly relevant variables enabling you to get focused data feeds. Brands like Coca-Cola use Machine Learning to reinvent how consumers engage with their products on their smartphones.
Assists with right product recommendation
ML models analyze the purchase history of customers to draw a report of the type of products the customers are interested in. With the help of a special type of algorithm learning called unsupervised learning, you can identify hidden patterns in different items to group similar products in one cluster. This model helps to make better product recommendations to the customers and thus increase the chances of product purchase. The best example, in this case, is Amazon which tracks customers’ browsing and purchases history to create the tag “Recommendations for You”. Often Amazon also includes the “Frequently Bought Together” tag which further shoots the chance of more product purchases.
Enables better insights into customer behavior
The cloud-based platform mines existing data resources to predict trends that would prevail among customers in the future. These actionable business insights enable you to predict future needs and thereby enable you to focus your products/services in that direction. Also, with ML you can get a comprehensive study of the data related to past behaviors of customers which will help you in planning and predicting future trends.
Paves way for the conversion of guest customers to lifetime loyal ones
ML can help in achieving individual marketing and accurate predictions for incentives. Marketers can use the data showing the behavioral pattern of a particular set of users during the trial period to predict the probability of their conversion to the paid version. This helps to draw better methods of engaging customers so as to persuade them to convert early.
Frees skilled resources for other value-adding duties
Machine learning algorithms can solve data duplication and inaccuracy issues. Considering the vast amount of databases available, such situations are common. But with ML, you can leave the time-intensive data entry tasks to machines and consequently free your resources to concentrate on other tasks. This may sound like a threat to jobs at the data entry level but the reality is this will lead to tech integration and more effective use of human talent. Netflix, the online streaming giant, uses an algorithm called Dynamic Optimizer that compresses videos in a way to prevent buffering while maintaining its quality. This enables the resources to devote their time and effort to some other tasks while machines take care of video streaming work.
All these benefits make Machine Learning a top-rated digital innovation trend. With Machine Learning, we are entering into a world where people and machines work in harmony to promote their products or services with a personal touch. Besides, you can also discover new patterns and trends from the diverse database available. With this trend, you get to automate analysis to interpret business interactions so as to achieve personalized and unique products and services. Deployment of Machine Learning can prove to be a lucrative decision, taking you to unfathomable heights.
This article was created by S.Swati Nair, Sr. Instructional Designer at WBPRO.