Originally developed as a way for businesses across the globe to simplify B2B trading, few could have predicted just how popular digital shopping would become among the average consumer. Figures published in 2023 illustrate the remarkable growth of the e-commerce industry in recent times, rising from 7.4% to 19.5% of total global retail sales in just 8 years.
As more general consumers gravitate towards the simplicity of e-commerce stores, digital apps and live shopping experiences, experts believe this market could account for almost 25% of all retail purchases by 2026. But can digital retailers keep up with rising demands?
As we enter the digital shopping season, e-commerce retailers must consider how general consumers approach online retail. Studies show that factors like variety of channels (74%), flexible shipping and returns (88%) and personalization (71%) rank among the top demands for modern consumers, so brands must optimize online stores while remaining cost-efficient.
How can this be achieved? Well, the answer may lie in the growing utilization of AI software.
How is AI used in e-commerce?
To understand the benefits of AI technology in e-commerce, it’s necessary to define the key types of AI models commonly used to optimize core elements of online shopping platforms.
- Machine learning – Self-learning algorithms are designed to forecast market trends, adjust inventory management systems and make accurate predictions with regards to customer preferences, helping retailers maximize efficiency across key operations
- Natural language processing (NLP) – NLP tools are used to improve the customer experience by optimizing the way that sites interpret typical human language, these tools analyze search intent to ensure users always receive relevant search results
- Computer vision – This form of AI is configured to extract useable information from images and videos, allowing for image search functionality and helping teams to promote accurate product recommendations related to stored customer preferences
Top AI tools for digital shopping season
Using a combination of the above AI technologies, e-commerce retailers are able to develop a wide range of smart tools designed to improve the customer experience. Below are just a few examples of actionable ways AI tools are already used to optimize digital shopping sites.
Virtual assistants
AI chatbots ensure that customer requests are always answered accurately and promptly, a consideration that 90% of consumers look for in digital shopping experiences. Supported by machine learning and NLP tools, AI virtual assistants analyze search intent in relation to past interactions ensuring users receive accurate responses even during periods of high demand.
Inventory management
AI tools can be deployed to maximize efficiency in inventory management. AI algorithms are programmed to analyze historical data, as well as live information pertaining to supply chains and vendors, helping teams with storing, organizing and purchasing inventory in response to realistic demands. Stock can also be tracked in real-time with levels communicated to users.
User personalization
As account-holding users navigate through digital shopping environments, AI software can be used to track user behaviors as well as make note of previous purchases and search prompts. This data can then be used to suggest new products that customers are likely to find desirable, a consideration that as many as 91% of users look for in e-commerce sites.
Dynamic pricing tools
Especially useful during the digital shopping season, a time when customer demand is high and competition for traffic reaches its peak, dynamic pricing tools can help retailers structure sales with optimal efficiency. AI tools analyze live user behaviors, supply data and competitor pricing to suggest price points most likely to convert sales without negatively affecting profits.
Voice search features
With 74% of e-commerce traffic now coming from smartphones, digital retailers must adapt some aspects of their sites to cater for mobile users. One aspect of this can be seen in the rise of voice search features, machine learning and NLP tools can be used to interpret voice prompts accurately, connecting users with relevant results to improve shopping experiences.
Summary
As e-commerce retail continues to capture the attention of consumers around the world, it’s up to retailers to optimize their platforms to reliably meet client demands. By utilizing smart AI tools like chatbots, inventory management solutions, dynamic pricing and personalization technologies, businesses can better address modern demands this digital shopping season.