How AI can transform consumer experience and business efficiency in India

Personalized recommendations: AI is significantly influencing customer decisions through personalized recommendations. The survey states 48% of Indians trust AI for tailored promotion and deals compared to 23% globally.

E-commerce platforms, streaming services, and social media platforms leverage AI algorithms to analyse user preferences, past purchases, and browsing history. This data-driven approach enables AI to offer tailored product recommendations aligned with individual interests and preferences, leading to improved shopping experiences, customer satisfaction, and loyalty.

Confidence in AI-based purchase decisions: Indian customers are increasingly comfortable with using AI-based tools to make purchase decisions. The survey reveals that an impressive 82% of Indian participants are open to improving their purchase decisions using AI, while globally, only 58% express the same sentiment. Indian consumers exhibit higher confidence in AI-generated personalized recommendations and trust AI for tailored promotions and deals. 82 % of Indians are open to chatbots helping with their queries.

Industry use case: The world’s largest e-commerce platform uses a machine learning algorithm to analyse customers' purchase history, search records, and other behavioural data, to predict products the customer can be interested in, and recommend them in real-time.

Seamless checkout process: AI-powered checkout systems such as cashier-less stores, are becoming more prevalent. These systems use computer vision and sensor technologies to automatically detect and charge customers for the items they select, streamlining the checkout process and minimizing wait times.

Industry use case: A global sporting goods retailer has introduced the concept of a technology-powered, hassle-free shopping experience with self-checkout counters equipped with a scan and pay app for billing. The ‘scan and go’ app allows customers to scan and pay for items using their smartphone, automatically disabling the RFID security tag so as to leave them free to exit the store without any need to wait in a queue for checkout.

Empowering companies

AI offers a plethora of benefits for consumer companies, particularly in providing valuable insights into logistics and supply chain management, resulting in cost savings and operational efficiencies.

Personalized engagement: By integrating and training AI models with customer data, companies can deliver highly personalized services at a rapid speed to the market, while also reducing content design costs. AI-driven analytics provide retailers with real-time insights into customer behaviour and buying patterns. Retailers can adjust pricing strategies and product offerings based on these insights, effectively staying ahead of market trends and increasing sales.

Industry use case: A leading e-commerce company has enabled dynamic pricing in stores. Customers use their phones to scan products or an in-store kiosk to check prices, thereby enabling the company to offer different prices depending on the type of customer.

Optimized operations and supply chain management: AI algorithms can be implemented to predict demand more accurately, optimize inventory levels and improve the efficiency of product distribution. This helps to reduce the risk of overstocking or understocking leading to cost savings and improved resource allocation.

Industry use case: The Indian subsidiary of the world’s largest food and beverage company has used AI to customise consumer choices and plan new launches. They have used AI to assess multiple types of data that give insights down to a postal code and demographic level leading to effective demand and supply planning.

Data-driven decision-making: AI's capabilities enable data-driven prioritization, resource allocation, and decision support, allowing company leaders to make strategic choices on how they engage with consumers.

Industry use case: A multinational fast fashion clothing brand based in Sweden uses AI to optimize inventory, predict market demand, and offer personalized offline experience.

Improving consumer experience: Continuous feedback loops between consumers and Generative AI platforms can refine and enhance the overall experience.

Industry use case: A large fast food retail chain has collaborated with a major internet company to offer personalized meal suggestions with facial recognition software basis customers’ age, mood, previous orders and time of the day (breakfast, lunch, dinner).

The future of retail with Gen AI

With Gen AI, consumer companies will be able to curate experiences and content specifically tailored to individual users, driven by an increasing tide of AI-generated content. Adoption of filtering tools ensures the most relevant information reaches consumers.

The exponential growth of conversational platforms is set to revolutionize customer decision-making processes, empowering companies with deeper insights into their customers and enabling the creation of intelligent solutions.

Along with this, in the not-too-distant future, Large Language Models (LLM) powered virtual assistants will gain the capability to fetch and visualize consumer behaviour and preferences, further enhancing customer understanding and interaction.

As Indian retailers embrace AI technologies, they will leverage the power of personalization, data-driven insights, and advanced AI models to create intelligent solutions and drive successful outcomes in the competitive retail market.