Artificial Intelligence (AI) technologies are opening up new opportunities for brands and retailers to push the boundaries of online shopping and customer experience. While global retailers are expected to spend $7.3 billion on AI this year and the global AI software market is expected to reach $126 billion by 2025AI presents many benefits and opportunities in the context of the e-commerce industry, including more targeted marketing and advertising, increased customer loyalty, efficient sales processes, better product development and experiences innovative purchases.

Here are eight applications of AI in e-commerce that can take both backend processes and customer experiences for brands to the next level.

8 Applications of AI in Retail and Ecommerce

1. Real-time data analysis

With the availability of real-time analytics, AI creates unique shopping experiences that matter to customers. Brands can better target potential buyers, walk them through the buying funnel, and even predict what would entice them to buy based on their past, real-time behavior. Insights generated by AI-powered solutions can help strengthen a brand’s relationship with new and returning customers by understanding shoppers’ wants and needs more deeply..

2. Interactive and immersive shopping experiences

Today’s shoppers, especially Millennials and Gen Z, are more willing to try new shopping methods. Tools such as visual search and virtual shopping rooms can enable a retailer to create the interactive shopping experiences that today’s discerning customers are looking for. The same group of shoppers are also comfortable drawing inspiration from content from visual channels like YouTube and Instagram, driving the need for on-site features that fit that browsing habit. Tools like visual search and virtual shopping rooms can enable brands to create interactive shopping experiences that modern, tech-savvy customers are looking for.

3. Deeper customization

Eighty percent of adults expect and desire personalized experiences, making personalization a popular use case for AI in e-commerce. Leveraging data that goes beyond demographics to include behavior and intent can deliver personalized purchase journeys in several ways:

• Product research and discovery. AI quickly connects shoppers to the products they are looking for. Search results can be more accurate if the on-site search engine can detect misspellings and similar words. This can help augment the product creation process, ensuring that new items produced match consumer demands.
• Cross-channel messaging and promotions. Leverage intent data to personalize offers to customers. Personalize promotions based on individual user profiles and the channels they interact with to increase willingness to purchase.
• Product recommendations. In e-commerce, relevant product recommendations powered by AI can improve up-sell and cross-sell opportunities, from “see similar” to “complete the look”.

4. Improved customer service and CRM

Advances in natural language processing have encouraged the application of virtual assistants and chatbots. These AI-powered tools help mitigate customer service and support, ensuring buyers get timely responses while giving internal resources more time to perform other tasks. Chatbots are versatile and can be used throughout the customer journey. Enriching customer relationship management (CRM) systems with AI capabilities can result in a streamlined process that leads to more conversions.

5. More accurate demand forecasting and supply chain management

The pandemic has exposed supply chain inefficiencies that can be improved with the help of AI. With the right tools, retailers can gain better visibility into consumer buying behavior and use it to enrich their demand forecasts. AI models can predict purchase demand and optimize global product distribution and delivery.

6. Dynamic pricing and merchandising

More and more brands are leveraging machine learning to optimize pricing and merchandising strategies. The technology enables brands to extract insights and predict outcomes from complex datasets. This information is then used to diversify prices and assortment based on several factors, avoid potential losses due to manual price optimization and better gauge consumers’ willingness to buy.

7. Last mile logistics

the share of last mile delivery on the total cost of shipping, there is 53%, which paves the way for the improvement of AI. AI can help provide visibility throughout the delivery process. Thanks to real-time updates, buyers are always informed of the location of their packages. Data can also reveal and solve problems, preventing delays and unsatisfactory customer experiences. Another application of last mile delivery is route optimization and the use of autonomous vehicles.

8. Seamless customer journeys that bridge the online/offline divide

AI has the power to create omnichannel experiences that seamlessly connect shoppers from one stage of the buying journey to another, across multiple channels and devices. Offering convenience and personalization at scale, this can be made possible by leveraging not just data, but also IoT infrastructure that creates a true single view of the customer.

The inevitable and lasting impact of AI on e-commerce

As AI technology continues to evolve, so do the many creative applications that can augment the end-to-end customer journey to purchase. AI is here to stay, and it will continue to revolutionize e-commerce and retail.

Photo credit: NicoElNino/Shutterstock

With a background in creating innovative, game-changing technology solutions, Ohad Greenshpan is an unstoppable serial entrepreneur with a wealth of experience in advanced big data and machine learning technologies, security and e-commerce. Greenshpan is co-founder and chief technology officer at Namogoo.