Every retail business benefits from understanding customers’ behaviour. While AI is reshaping the retail industry, its influence on consumer behaviour is becoming increasingly evident.
Though its influence is most apparent in chatbots and personalized recommendations, AI has a deeper impact on retail, subtly changing consumer behaviour unexpectedly.
Further, integrating smart PCs powered by AI enhances the omnichannel experience. These systems can track customer behaviour in-store and provide insights into their buying patterns, which can then be used to tailor the online experience for those same customers.​
According to Future Market Insights, the demand for AI in retail is expected to expand at a compound annual growth rate (CAGR) of 28% between 2023 and 2033.
Read this article to explore how AI impacts consumer behaviour in the retail industry.Â
1. Personalized Shopper Trend
Artificial intelligence is transforming how retailers communicate and understand their customers. AIÂ algorithms provide highly customized shopping experiences by examining enormous volumes of data, such as browsing history, purchase trends, and the social media activity of customers.Â
This hyperpersonalization extends beyond product recommendations, including tailored marketing messaging, loyalty programs, and in-store interactions.
For example, Amazon’s “Eco Look” function makes outfit recommendations using AI based on user preferences and previous purchases. Similarly, Sephora’s Virtual Artist app uses AI-powered face recognition to let users virtually put on cosmetics.
These customized exchanges improve sales and loyalty by strengthening the relationship between businesses and their clients.
2. Smart Stores Innovation
Artificial intelligence is transforming physical retail spaces into “smart stores” that offer seamless and exciting shopping experiences. These retailers use modern technologies like computer vision, sensor fusion, and machine learning to analyze foot traffic patterns, monitor customer behavior, and enhance store layouts.
Amazon Go is one of the best examples of a smart shop. It eliminates checkout lines by utilizing advanced sensor technologies and computer vision.Â
The store’s AI system automatically charges customers’ Amazon accounts when they simply take what they want and leave. This smooth shopping experience is changing how we view the traditional retail environment.
3. Virtual Try-onÂ
One of the most inventive ways AI is influencing consumer behavior is through virtual try-on technology. This technology allows consumers to virtually try on apparel, accessories, and even cosmetics using a smart PC, laptop or smartphone.Â
Virtual try-ons that use AI algorithms can faithfully replicate how a product would seem on a person while accounting for variables like skin tone, body shape, and lighting.Â
This technology increases conversion rates and enhances customer satisfaction by eliminating the uncertainty and challenge associated with traditional try-ons.
4. In-store Analytics with AI
AI is completely changing how retailers understand and analyze customer behavior in physical stores. Retailers can use artificial intelligence-powered cameras and sensors to track customer movement, dwell time, and product interactions.
This information can be utilized to pinpoint high-traffic locations, enhance product positioning, and optimize shop layouts.Â
AI is also able to read the facial expressions and body language of consumers to ascertain their feelings regarding products and ads. This information can be used to improve marketing strategies and the overall in-store experience.
5. Social commerce powered by AI
Social media platforms have developed into effective means for retail firms to engage with their target audience. AI is significantly improving the experiences of social commerce.
On social media, for instance, chatbots driven by AI can immediately respond to consumer inquiries and offer tailored product suggestions.
Further, AI can look at social media conversations to identify brand mentions, consumer sentiment, and emerging trends. This information can help with product development, marketing campaigns, and customer service strategies.
6. Customer Sentiment Analysis
Customer sentiment analysis is a crucial use of AI in retail. It analyzes and understands the opinions and sentiments of customers as they are expressed in reviews, social media posts, and feedback using Natural Language Processing (NLP) techniques like Recurrent Neural Networks (RNNs) and transformers like BERT or GPT.
Artificial intelligence (AI) systems can classify client feedback as good, negative, or neutral by analyzing the sentiment. They can even extract certain features, such as customer service satisfaction or product quality.Â
This deep understanding of consumer emotion can be used by businesses to make data-driven decisions, improve customer experiences, offer better products, and effectively address issues—all of which increase customer satisfaction and loyalty.
Key Takeaway
AI and machine learning have made it feasible to comprehend consumer behavior. Using these new disruptive technologies, businesses can evaluate a range of customer behavior data through predictive modeling.
The latter can include demographics, price sensitivity, browsing habits, previous purchases, frequency and preferences of purchases, and much more.
As AI advances, it is likely to have even more inventive and unexpected effects on consumer behavior in the retail space.
