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6 Ways eCommerce Stores Benefit From Algorithms

6 Ways eCommerce Stores Benefit From Algorithms

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Algorithms are one of the key tools used in eCommerce today, being an integral element of the artificial intelligence and machine learning apps that many businesses rely on. They are able to spot patterns in data and, from this, make exceptionally accurate and useful predictions. Importantly, they are also able to learn and modify their predictions when new data is added. Readily available and affordable, almost any company can benefit from this cloud-based software. Here are just some of the way eCommerce companies are taking advantage of algorithms.

1. Customer segmentation

Customer segmentation is nothing new. Retailers have long been grouping customers based on different factors. Traditionally, these include things like age, gender and income. Today, online eCommerce stores also consider browsing behaviour, purchase history, lifetime value and even whether the user is accessing the site on a mobile or PC.

All these additional factors make it significantly more complex to group customers. However, the upside is that there is far more data to analyse and the powerful algorithms now available make it possible for online stores to find new groupings based on data patterns that, previously, were not known to exist. Understanding these new segments opens up important new marketing opportunities for eCommerce stores.

2. Recommending products to customers

Algorithms known as ‘product recommendation engines’ are used extensively in eCommerce in order to find the most suitable products for customers. These engines use a range of data to show relevant products which are more likely to be purchased. This helps improve both user-experience by cutting down the amount of time a customer searches and, consequently, improves sales.

Importantly, the algorithm learns how long customers will spend looking for a product before they get fed up and look elsewhere and will aim to deliver the right choices to the customer within that time frame.

3. Intelligent site search

Although virtually every website now offers customers a site search facility, the standard search that comes built into your theme or is added through a plugin is, by modern standards, rather basic. These tend to work by matching products in your database with the key terms inputted by the user’s search query. While these can provide accurate results, this is not always the case and often leads to customers having to modify or filter their query before they find what they are actually looking for.

Modern machine learning algorithms are able to provide more relevant results by taking into consideration other kinds of data, such as purchase histories and add to cart behaviour that can list items that similar shoppers have purchased.

4. Dynamic pricing

The retail sector is enormously competitive and margins are increasingly slim. Getting the pricing right can sometimes be the difference between staying in business or going under. Today, many eCommerce sites rely on dynamic pricing algorithms to help them achieve the optimum price for their products, ensuring they remain both competitive and profitable.

Dynamic pricing applications do a number of jobs, not only do they tell companies the best prices, they can also be used to automate the setting of those prices on the website, saving the company the hassle of having to do it manually. This can be very helpful as prices may change often to take into account such things as purchasing costs, competitor price changes, seasonal fluctuations, customer demand and product availability. In addition, the algorithm can be used to split test pricing points in order to fathom what customers are willing to pay. 

5. Predicting inventory demand

Sourcing the products customers want and purchasing them in the right quantities to satisfy demand without leaving large volumes on the warehouse shelves is a difficult process.

Today, many procurement teams are making use of demand estimation algorithms that use a wide range of data to more accurately predict the stock levels their company will need. As a result, they are able to provide better choices of products for their customers and fewer items end up in the sales.

6. Personalisation

Personalisation is one of today’s most important marketing techniques as it provides each user with a shopping experience tailored to their own needs and wants. Personalisation is far more than putting the customer’s name on the website when they log in and showing them products related to the last items they bought or looked at.

Using algorithms, companies are now able to communicate over the user’s preferred channel (email, app notification, text message, etc.) the products can be displayed in the way the user prefers, the actual products shown can be far more relevant and they can be given offers and deals that are  more likely to be taken up. Not only does this increase sales; it can have a significant impact on customer loyalty.

Conclusion

AI and machine learning algorithms are being increasingly adopted by eCommerce stores to improve the way they operate. They are being used in almost every aspect of running an online store, from purchasing to marketing to aftersales and, at each step, are providing insights that make the company perform better. Cloud hosting is an essential requirement for companies wishing to adopt AI or machine learning algorithms. For more information check out our cloud hosting page.

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