Industry
Retail
Omnichannel Experience & Intelligent – The Future of Retail
Highlights
- Artificial intelligence (AI) is only beginning to show the wonders it can do for the retail industry. Shopping, as we know it, is bound to get redefined.
- AI will play a key role in offering enhanced personalized experiences to customers, positively impacting conversion rates. It will also add to the efficacy of blockchain and augmented reality applications.
- Additionally, by integrating AI, retailers can enable predictive and proactive carbon management.
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AI-powered personalization is revolutionizing retail
Artificial intelligence (AI), with its myriad applications, promises to revolutionize retail, expanding far beyond its current implementations.
In the rapidly evolving world of retail, technological advancements have continually shaped the landscape, enhancing both customer experience and operational efficiency. Among these innovations, AI stands out as a transformative force, promising unprecedented levels of personalization, automation, and insight.
However, despite these strides, the true potential of AI in retail remains largely untapped. AI is only beginning to show the wonders it can do for the retail industry, setting the stage for a revolution that could redefine shopping.
Today's consumers demand more than just products; they seek experiences tailored to their unique preferences.
AI, by analyzing intricate patterns in vast datasets like purchase histories, browsing habits, and social media activity, can offer personalized recommendations and advertisements. This level of granularity allows retailers to send tailored emails, suggest relevant products, and customize user interfaces.
In the future, we can envisage AI predicting customers' needs even before they realize them. For instance, based on past purchase data and online activity, a retailer might suggest winter apparel for a customer who has a high probability of traveling to a colder region soon. Similarly, with an understanding of customers’ health goals and preferences, AI can help retailers personalize their basket to offer relevant products. With AI-powered computer vision, retailers will be able to provide personalized content on interactive displays in stores. Similarly, digital signages outside stores could display tailored advertisements based on the demographic profile of the viewer, thereby enhancing promotion effectiveness.
Personalized experiences positively impact conversion rates by showing customers what they want and need, making them more likely to buy.
AI to enhance blockchain applications
Blockchain, when complemented with AI, can provide an unparalleled level of transparency and efficiency in the retail supply chain.
From the soil quality data of a farm to the manufacturing date of a shirt, information can be recorded on an immutable ledger. For retailers, this means keeping fraud and counterfeit goods at bay. For consumers, it guarantees product authenticity. AI can predict supply chain disruptions or demand spikes, and blockchain can ensure every entity in the chain fulfills its obligations, ensuring smooth operations. Smart contracts on the blockchain could automatically release payments to suppliers once AI-powered sensors at the retailer’s warehouse detect that the goods have been delivered and that they meet the required standards.
AR and AI chatbots to recontour shopping experiences
Modern chatbots, powered by AI, are a quantum leap from their rule-based predecessors.
They can understand context, handle multifaceted queries, and learn from interactions. For retailers, this means reduced operational costs as it would enable them to offer round-the-clock customer service without the need for extensive manual intervention. Chatbots can also facilitate understanding of the customer’s context and capturing relevant information to help convert what might have been a missed opportunity.
In the future, these chatbots might evolve into virtual shopping assistants, guiding customers through entire shopping journeys, offering personalized advice, and mimicking in-store, person-based assistance. Moreover, advanced AI chatbots could detect shopper emotions based on text inputs, adjusting their responses to align with users’ sentiments, ensuring more empathetic customer service.
Augmented reality (AR) is also set to redefine online shopping, and AI can enhance it even further. With AR glasses or even smartphone apps, consumers can wear a piece of clothing virtually or place furniture in their living room. AI can enhance this by suggesting products based on personal preferences, past purchases, or trending styles and context.
This will not only enrich the online shopping experience, but also reduce returns significantly, a challenge many retailers face. Using AR and AI, retailers can create a virtual shopping assistant that offers real-time product recommendations, answers queries, and provides in-store assistance. Shoppers will be able to ask a chatbot about the best hiking shoes, and it will respond by asking about their past hiking terrains and budget and even scan their foot size using AR to provide them with the best options.
AI-led demand and inventory management
Out-of-stock or overstock scenarios are costly for retailers – AI can prevent them.
AI, with predictive analytics, can forecast demand with high accuracy. By analyzing historical sales data, local events, weather forecasts, and global news, AI can provide actionable insights.
This means efficient warehousing, optimized supply chains, reduced wastage due to perishables expiring, and maximized profitability. With the integration of AI and IoT, real-time inventory tracking will become possible, enabling dynamic pricing strategies and promotion adjustments. AI-powered robots and drones will be able to manage warehouse operations, from restocking shelves to picking and packing orders.
AI systems could dynamically adjust supply chain operations based on real-time events. For instance, if a sudden weather event disrupted a supply route, the AI system could instantly reroute the shipments or adjust inventory distribution across locations. Moreover, it could assist business users in designing a supply chain based on different strategies such as cost efficiency or minimum lead times.
AI-powered IoT to pave the way for autonomous stores
IoT, comprising smart shelves, interactive displays, and other connected devices, provides a treasure of real-time data.
AI algorithms can analyze this data to offer insights about customer preferences, inventory levels, and in-store navigation patterns.
With applications such as personalized recommendations inside smart fitting rooms to automated checkout and predictive maintenance of in-store equipment, convergence of AI with IoT has already enabled higher operating efficiency and enhanced customer experience.
However, many more possibilities remain unexplored. In a connected store, if a customer is spending significant time in an aisle, a nearby screen might instantly display promotions or comparisons, aiding the purchase decision. Or based on smart shelf weight sensors, the store could automatically reorder stock or adjust pricing on the electronic shelf labels (ESLs) to move the inventory. Additionally, AI can enable insights such as quality of perishable products in the supply chain based on the data, such as temperature, humidity, and route, captured from the logistics provider.
The concept of autonomous stores, while seemingly futuristic, is already taking shape. In an autonomous store, with a complex web of sensors, cameras, and machine learning algorithms, products are automatically detected and billed as customers walk out, optimizing customer experience and operational efficiency with minimal retail colleague interventions.
Stores equipped with AI cameras could gauge a shopper’s emotional reactions to products and displays and could offer real-time deals that might appeal to their current mood. These cameras could also enable enhanced security features such as tracking potential shoplifters, controlling access to restricted areas within stores, and enabling facial-recognition-based payments and age verification for restricted products.
As technology evolves, stores might dynamically change layouts and automatically monitor and replenish shelves, with robots helping to move products within the store.
Accelerating the sustainability agenda with AI-led carbon tracking
Sustainability is becoming a priority for consumers and businesses alike.
As eco-consciousness rises, retailers are under pressure to showcase their sustainability efforts. By integrating AI, retailers can go beyond just tracking to predictive and proactive carbon management. AI can assist retailers in tracking their carbon footprint across the supply chain. From sourcing raw materials to product delivery, AI can provide insights into carbon-intensive areas and suggest strategies for reduction.
Apart from the standard parameters, AI can analyze data such as road and weather conditions and traffic situations to calculate the carbon footprint of a product or service with even higher accuracy. Generative AI (GenAI) can significantly reduce the effort required to consolidate data from multiple siloed systems for reporting purposes.
AI can also analyze historical data to predict future carbon emissions for planned activities and help retailers preemptively implement reduction strategies. Moreover, AI can be used to optimize energy consumption in stores, warehouses, and during transportation. By predicting demand, AI can also reduce waste, further contributing to sustainability.
As retailers look to AI to address problems, it is important to dovetail some aspects of the technology to critical business demands.
From forecasting to buying to merchandizing and further to selling, AI can yield quick wins for retailers. Overall, AI has the potential to revolutionize retail by driving operational efficiencies, improving customer experiences, and enabling data-driven decision-making.
