22nd July 2021 - 5 minutes

5 Essential Applications of Machine Learning In Ecommerce

Over the years, the relationship between ecommerce and machine learning has become stronger, with concepts such as artificial intelligence (AI) having a profound impact on how online businesses interact with their audience and how customers buy products.

In fact, a recent survey highlighted 51% of ecommerce players have introduced machine learning automation technologies across sales, marketing and customer services to create a better customer experience. Furthermore, the AI industry is expected to generate $118.6 (£84 billion) a year by 2025.

These stats highlight machine learning in ecommerce is going to continue going from strength to strength and in this article, we’ll explore five essential applications of machine learning in the ecommerce space.

1.      Personalised product recommendations

We’re living in an age where personalisation has become an expected part of the shopping experience. Consumers enjoy having products that are tailored to their specifications.

A great application of machine learning in ecommerce in this context is through personalised product recommendations. Modern machine learning algorithms are capable of making intelligent product recommendations based on past search behaviour.

For example, a consumer who liked shopping for ski equipment in a certain colour could be recommended similar equipment in the same colour when they returned to an online store.

2.      Customer service

Another machine learning ecommerce application is through the lens of customer service. Algorithms have the power to reduce the wait time for customer enquiries, speed up the buying process and sort out minor issues.

A specific customer service case is through chatbots aiding consumers in their purchasing decisions by answering questions and directing them towards the most helpful services.

Another example is robots being able to answer phone calls through advanced speech recognition and natural language processing. This has the benefit of freeing up human staff to take care of other challenges and having customer queries answered quickly.

3.      Product discovery and search

When it comes to companies that list millions of products in their online store, it’s vital that customers have a way to locate exactly what they are looking for. This means search engine algorithms need to be sophisticated enough that a consumer can find what they need in the blink of an eye.

Machine learning comes in handy in this scenario through helping with features such as search ranking. This refers to categorising search results based on estimated relevance and taking into consideration search terms, customer buying habits, product views etc.

In other words, machine learning has the benefit of personalising product discovery in search engines and giving customers the ability to find items that match their needs.

4.      Customer segmentation

To create the best possible online shopping experience, brands often need to have a complete view of their customers and understand how they shop, what their product preferences are, where they are based etc.

Without this data, it can be difficult to optimise the buying journey and machine learning is a game-changer in terms of customer segmentation. Machine learning enables important customer data to be collected quickly and be made available immediately.

Using this data, brands have the power to develop phenomenal marketing campaigns that boost sales and create better customer relationships.

5.      Error detection

Ecommerce brands that deal with vast quantities of product data face challenges such as detecting inconsistences in product titles, category errors, missing images and so on. Machine learning in an excellent error detection application in this context, as an algorithm can be used to analyse data patterns and advise on making corrections.

Another useful error detection application could be for recognising fraud. An ecommerce company may have to deal with instances of frustrated customers who’ve had their credit cards stolen and multiple products have been bought without their consent.

In this situation, an algorithm may be able to detect the inconsistency in purchasing behaviour and flag it as malicious activity.

Harness next level machine learning ecommerce technology with PureClarity

Intuitive ecommerce machine learning is at the heart of the PureClarity platform. It provides exceptional personalisation and customer segmentation benefits and to see it in action book a discovery call now.

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