Retailers have invested in eCommerce strategies, whether it’s lockdowns, shutdowns, or consumers changing their shopping habits. However, what will enable you to thrive and compete with the big brands if the playing field is leveled for you?
Modern technologies, such as artificial intelligence for search, merchandising, and personalization, have helped small businesses establish an online store, provide a great customer experience, and deliver what consumers want when they want it.
Furthermore, it has made it easy for brick-and-mortar retailers to shift to an eCommerce strategy. Technology can enhance the creative work of expert human designers and eCommerce conversion rate by predicting intent instantly. It’s also driving higher conversion rates, higher average order volumes, and higher brand satisfaction.
What does Merchandising mean in Ecommerce?
As defined by Practical Ecommerce, e-commerce merchandising is “the art and science of displaying products or offers on a website to increase sales.”
That’s an excellent starting point. However, you need to dig deeper if you want to matter succeed. No where users enter your website or where they are on the path to purchase. Great online merchandising isn’t just about displaying products attractively – it’s also about optimizing their way to buy. It’s about getting users to the products they’re looking for (or the developments most likely to generate desired business metrics) as quickly as possible.
Ways to boost eCommerce conversion with AI
Collections can be dynamically defined and altered
In all types of commerce, collections in categories like summer fashion, back to school, and “on-sale” serve as powerful merchandising techniques. Merchants can sell experiences (rather than just products) with collections, align with buyer emotions and logically help buyers sort through large amounts of information to speed up and simplify shopping.
Collections work only when they meet buyers’ needs, keeping up with digital changes. Automating and artificial intelligence can now help you create better groups, such as those that sell together most frequently, and adapt them on the fly to make quick substitutions before a customer leaves. In addition to the arrival of new products, the sale of others, and the emergence of new patterns, AI can update collections without human intervention.
Match merchant requirements with buyer opportunities
Merchants run businesses. As a result of updated data, collections now better and certainly more quickly match business needs. Can you tell us how much inventory you have? Do you have too much or too little?
Are there any sales bundles you can use to push product add-ons? Would it be possible to send buyers an alert when inventory is low on a particular SKU to motivate them to convert? Loss leaders can be paired with high-margin products to attract customers and still profit.
Act on every signal immediately
There isn’t time for human guesswork anymore since shoppers aren’t always clear on what they want. A product display must reflect the buyer’s intent with technology that instantly reads the signals. Geographical signals are examples.
Virtual Search
eCommerce store and sites also use visual search, which uses artificial intelligence to analyze a photo that a shopper submits. Customers used to search for their desired object using a text search.
Today, however, many companies use visual search to identify products based on the shopper’s image. Hence with the help of modern-day artificial intelligence future and merchandising, many retailers and eCommerce sites can help customers look upon what they want and require.
Conclusion
In retail, artificial intelligence is a powerful and flexible tool that empowers companies to leverage big data instead of accumulating new information. Through the use of artificial intelligence in ecommerce, you can discover more about your customers’ purchasing patterns, identify new prospective target audiences, monitor competitors’ activity, and achieve new levels of automation and optimization.
AI in eCommerce is poised to offer more and more comprehensive solutions in the future; therefore, it is best to start small and build up from there, integrating AI into more key processes without disrupting them.
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