“Overall online retail eCommerce revenues are anticipated to rise to 4.88 trillion USD in the year 2021” as per Statista Report
Retail eCommerce is at its peak at this point of time with no signs of bringing down the curve of growth in the near future. In such a promising environment, every retailer wishes to have more and more of profits while cutting down on extra time and cost involved.
In context to such aspirations of retailers, Machine Learning (ML) is all set to serve its best to them on the way to growth. It is one of the biggest technological advancements in the form of Artificial intelligence.
Having to provide a brief definition of machine learning, I would say that it provides the digital systems with an ability to learn automatically and progressively enhance its performance from its own experience and that too without any need to programmed specifically.
How can it bring a turning point in your WordPress powered shop?
With an increasing competitive shift in the eCommerce industry, it has become crucial for almost every retailer to offer accurate, efficient, and more enhanced user-experience on their respective sales channels.
To set up a compelling store online, you can easily hire WordPress developer India or abroad, still, there will be a need to enhance its default functionality with various 3rd party integrations or apps. And, machine learning is one of those enhancements that can help you to conquer the challenges and meet the high expectations of your consumer base.
Let’s have a deeper look at the aspects where ML (machine learning) can help you;
➢ Churn Prediction
Customer churn or attrition refers to losing existing consumers due to different reasons. And, it becomes a crucial aspect to deal with while selling online. In any default eCommerce setup, it is difficult for any retailer to predict such customers.
But with the help of machine learning, you can easily opt for data-driven and predictive strategy to follow a proactive approach to this churn issue. It helps you to maintain, analyze, and compare existing customers’ shopping track for a particular time span.
Thus, you simply need to use behavioral analytics tools while segmenting those customers by different attributes (spending levels, behavior etc.). And, by opting for an effective predictive model, you can easily churn predictions while detecting the customers who are most likely to cancel your services or any kind of subscription from you.
➢ Data Quality
Maintaining a high quality in terms of data has always remained a top priority for almost every retailer. And, the rise of machine learning makes it possible to accurately gather and store the data and further the cost saving of the retailers.
In the ML (machine learning) models, whenever a new data is being submitted it automatically start learning, performing and delivering accurate results. It has dramatically impacted the traditional methodologies for data quality.
➢ Product Recommendation
Opting for smart product recommendations to your repeated customers (also applicable for first-time visitors) is one of the most effective ways to combat current eCommerce competition. And, it can definitely increase the average order value for your online shop as well.
Machine learning has made it possible to develop unique engine recommendations that can assist your consumers to experience such shopping journey where they will be shown most relevant products based on their specific taste and preferences.
Many retail giants like Amazon are already using this technique and are being able to make more of their efforts in terms of customer’s engagement and conversions.
Customer Service is yet another area where you can implement machine learning powered solutions in form of speech recognition advancement and natural language processing through deep learning.
Final Verdict
Machine learning is gaining huge importance by one of the world’s largest retailers and helping them to achieve high efficiencies and cost savings.
At last, I would like to state that Machine Learning is a boon to our eCommerce industry that has helped many retailers to cut down manual efforts with automation that has further, make the process more accurate and efficient.
