“A baby learns to crawl, walk and then run. We are at the crawling stage when it comes to applying machine learning.”

Before going into the nitty-gritty of machine learning, it’s essential to understand the connotations and significance of machine learning.

Machine learning in simple terms is language of machine. It is a branch and subset of artificial intelligence used for improving the performance through experience. Going deeper machine learning allows E-com to create a personalized customer experience. 

In current milieu, customers expect personalization and interaction while shopping for their beloved and preferred brand. Machine learning helps in reduction of customer service affairs, thus reducing cart abandonment rate and increasing sales. Also, customer service bots provide unbiased solution around the clock. 

Machine learning improves search result of a website every time the customer shops, based on customers’ preferences and purchase history. Use of Machine learning avoids the use of traditional search methods, instead it helps in search rankings based on relevance/ preference of user. 

This has further added in predicting and displaying the most apposite search result.

Furthermore, visual discovery has replaced keywords search. For e.g.: pointing your camera at a desired object will find it online through use of algorithm thus further helps in avoiding a vague search. 

Machine learning helps in increasing conversion rates by analysis of data from various channels. This analysis stimulates the algorithm to identify purchase patterns and helps in anticipating what a customer actually desires. 

Earlier the personal shoppers were limited to only high-end consumers, but nowadays each one can take the advantage of this premium service. 

Withal Machine learning also helps in annihilating fraud. It helps in learning what is apt and normal and what is not and get notified when something is wrong. For e.g.: Shopping with stolen cards or retracting the payments after item delivery is the most common fraud which the retailers face. 

Machine learning is an application of wider tech area of Artificial intelligence, involving algorithm creation that can access and learn from data, without human interference/ programing.

Discipline of Machine learning began after the invention of how neurons in brain works, which was further executed by E-Com through application of Machine learning. 

Machine learning makes use of data to make predictions and perform actions. More the exposure to data more is the accurate output.

Machine Learning algorithm builds a model based on simple data known as “training data”.

Machine Learning algorithm are used in vast applications like Medicine, computer vision and e-mail filtering.

It is also referred as predictive analytics.   

To get started with Machine learning- 

• Full understanding of its capabilities and getting familiar with its solution 
• If Machine learning is not your cup of tea than reach out to someone whose expertise.
• Problem identification should be the first concern.
•  Team creation should be the next implementation.
• Adoption of machine learning solution should start on a smaller scale, once you are faultless in your programing you can move to big data.

Mentioned hereafter are useful Machine learning tools for E-com

• Choice.AI- creating personalized E-com site
• Granify- monitors online shoppers’ behavior 
• Personali- performs precision targeting with intelligent incentives 
• Wacul-AI- provides user friendly solutions to boost entire website.

“COMPUTERS ARE ABLE TO SEE, HEAR AND LEARN- WELCOME TO THE FUTURE“

Machine learning in E-com targeting

online shopping portals are hit with huge amount of customer data; thus, customer segmentation becomes a top priority.

This helps in understanding needs and fabricating personalized shopping experience. 

Machine learning in price optimization

the algorithms of Machine learning help not only collecting price trends from your competitors, demands of items, but further combines this information with customers behavior to determine the best price of the product. Price optimization helps in client satisfaction.

Machine learning in increased conversions

Machine learning algorithm delivers smart search results, via natural language processing and understands what is typed in search bar. It helps in understanding what the researcher genuinely looks for. Returning to the website again, presence the similar items to those who have shown interest in product before.

Machine learning in relevant marketing campaigns

In era of big data, Machine learning can help them make sense of customer data to better tailored marketing campaigns. Algorithm of Machine learning helps in retargeting campaigns. 

Machine learning churned prediction and eradication

Churning refers to the rate at which customers relinquish a brand, potentially to patronize another. Thus, retention marketing came into existence. Here Machine learning helps in churned prediction about customers priority, patterns, behaviors. These insights are delivered by Machine learning. This further helps in tailoring market campaigns by e-mail, social media to hold your customer who are about to leave, specifically to keep them on board.

Machine learning in only channel support

24*7 only channel support is another initiative possible through Machine learning.
customer service is of utmost importance. It is characterized by delivering customer satisfaction, both how and when customers need it. Companies seek to magnify customer satisfaction via Machine learning.

Machine learning in managing supply and demand

More proactive and dynamic the inventory and supply chain more driven is the sales. Thus, demand forecasting is crucial and vital for online stores. Machine learning helps in predicting fluctuating needs, real time predictions. Machine learning algorithm balances consumer demands, performing quantitative forecasting (hard and solid evidence).

Machine learning as a recommendation engine

The ultimate reason behind Amazon’s success is its recommendation engine which is based on Machine learning algorithm. Recommendation engine are like frame work and trestle of magazines or eye catchy objects that is available at check-out counter reminding the customers to assemble items that has been forgotten or could be of regular use on daily basis. Recommendation engine congregate data and patterns from past behavior thus identifying customers ongoing and topical needs. When the ultimate purchase is done the engine go through, whether the outcome is favorable or not to improve the algorithm.   

There is a lot of scope for Machine learning and E-com which makes it effective and important part of online retail. Machine learning will automate jobs that most people thought could only be done by people. Still in its infancy, Machine learning will be a game changer by increasing productivity through supply chain. To flourish in E-com sector retailers should be fast and supple, thus Machine learning is a necessary investment for E-com players.  
“A baby learns to crawl, walk and then run. We are at the crawling stage when it comes to applying machine learning.”

Before going into the nitty-gritty of machine learning, it’s essential to understand the connotations and significance of machine learning.

Machine learning in simple terms is language of machine. It is a branch and subset of artificial intelligence used for improving the performance through experience. Going deeper machine learning allows E-com to create a personalized customer experience. 

In current milieu, customers expect personalization and interaction while shopping for their beloved and preferred brand. Machine learning helps in reduction of customer service affairs, thus reducing cart abandonment rate and increasing sales. Also, customer service bots provide unbiased solution around the clock. 

Machine learning improves search result of a website every time the customer shops, based on customers’ preferences and purchase history. Use of Machine learning avoids the use of traditional search methods, instead it helps in search rankings based on relevance/ preference of user. 

This has further added in predicting and displaying the most apposite search result.

Furthermore, visual discovery has replaced keywords search. For e.g.: pointing your camera at a desired object will find it online through use of algorithm thus further helps in avoiding a vague search. 

Machine learning helps in increasing conversion rates by analysis of data from various channels. This analysis stimulates the algorithm to identify purchase patterns and helps in anticipating what a customer actually desires. 

Earlier the personal shoppers were limited to only high-end consumers, but nowadays each one can take the advantage of this premium service. 

Withal Machine learning also helps in annihilating fraud. It helps in learning what is apt and normal and what is not and get notified when something is wrong. For e.g.: Shopping with stolen cards or retracting the payments after item delivery is the most common fraud which the retailers face. 

Machine learning is an application of wider tech area of Artificial intelligence, involving algorithm creation that can access and learn from data, without human interference/ programing.

Discipline of Machine learning began after the invention of how neurons in brain works, which was further executed by E-Com through application of Machine learning. 

Machine learning makes use of data to make predictions and perform actions. More the exposure to data more is the accurate output.