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How Artificial Intelligence is Impacting eCommerce

Artificial intelligence (AI) is beginning to embed itself into all aspects of our lives. From the growing number of self-checkout cash registers to advanced security checks at the airport, AI is just about everywhere.

But how can we use AI in eCommerce?

Whether you’ve yet to realize it or not, AI is making major waves in the eCommerce industry too. AI, at its core, focuses on making intelligent machines capable of solving problems as well as (or better than) people can. It provides new ways to create problem-solving systems by assessing data and learning and adapting to patterns or features within that data.

Many eCommerce businesses are already using forms of AI to better understand their customers, generate new leads, and provide an enhanced customer experience. Here are some of the ways AI is impacting today’s eCommerce businesses.

Quick and Responsive Customer Service

One of the most widely-used forms of AI in eCommerce is chatbots. Chatbots, which are designed to simulate conversation with human users over the internet, can actively take on some of the responsibilities of running an eCommerce site, especially when it comes to customer service. Surveys have shown almost 89 percent of messages that require responses are ignored by brands, with an average wait time of 10 hours for those that do get a reply. Unfortunately for those brands, consumers expect a reply within four hours.

This is where chatbots come in. They give online shoppers an instantaneous response when they have a concern about a product detail or shipment information. eCommerce sites are open 24 hours a day, 7 days a week and need to be available to potential customers regardless of the time. Chatbots provide consistent and more-than-satisfactory customer service while saving time for both customers and vendors.

Customized Product Recommendations

The deep learning capabilities of AI can collect data on customers’ previous purchases, returns, and other buying habits, and then can suggest similar goods based on these preferences. This method is fast and easy, allowing customers to find items of interest without spending time and effort searching for them. More importantly to eCommerce vendors, the suggestions are relevant because AI intelligently identified what the individual wants. For example, Amazon’s “item-to-item collaborative filtering” algorithm provides tailor-made content direct to the homepage as soon as the user arrives. When it began using targeted recommendations, Amazon sales increased by 29%. For eCommerce sellers, AI can customize  “Customers Who Bought This Also Bought,” or “Frequently Bought Together” collections of items as well as product pages, home pages, and category pages.

AI is even becoming sophisticated enough to anticipate buyers’ needs: How have their tastes evolved? How will their age affect purchasing as they get older? Is their style becoming more modest or risqué? With an estimated 51% of consumers expecting companies to anticipate their buying needs and provide appropriate suggestions by 2020, staying ahead of the trend is just as important as catering to customer needs now.

Strategic Customer Retargeting

The average conversion rate of any eCommerce website is ~2%. Essentially, 98 out of every 100 consumers that come to your website leave without making a transaction. For this reason, many eCommerce retailers have enabled retargeting, or remarketing, tactics that deliver ads to users based on their previous interactions with the company. This allows the advertiser to deliver the right ad to the right person at the right time, greatly increasing conversion rates when compared to regular ads.

Predictive retargeting takes traditional retargeting tactics a step further, thanks to AI’s ability to re-engage customers. This method takes a lot more into account than just a user’s browsing history, and will often uncover hidden patterns that are sometimes counter-intuitive. In typical retargeting, marketers can segment audiences based on the actions they took on their sites — visited product pages, abandoned a cart, completed a purchase, downloaded a white paper and so forth. On the other hand, predictive retargeting can add layers of data to map out customer intent signals beyond actions taken on their sites to provide much richer targeting capabilities.

Accurate Inventory Management

Managing inventory across multiple channels is one of the biggest concerns for eCommerce businesses. Being out of stock is a nightmare scenario, as it can take days to replenish and can heavily affect sellers’ revenues. On the other hand, overstocking can also be detrimental to cash flow and revenue. 46% of US companies have admitted they don’t track inventory, even though proper inventory management is vital to overall business success.

AI-equipped inventory management tools can help optimize inventory at all levels in the demand chain. It can predict future buying behavior and also detect and act upon supply chain anomalies in a timely fashion. By giving them insights into what customers want and when they want it, eCommerce businesses are better able to anticipate demand and plan their inventory accordingly. This goes beyond having Christmas decorations in stock in the final months of the year. It’s about knowing how many Christmas decorations are going to be bought each week in the lead-up to the 25th of December and bringing in merchandise accordingly.

AI is not only going to impact the future of eCommerce, but it’s also already impacting the present. It’s here now, and the time for today’s eCommerce businesses to work alongside it is as soon as possible.

Topics: AI, artificial intelligence, General

Written by Marie Johnson