Five Trends in Digital Analytics and AI Solutions in Asia

The beneficial conveniences of intelligent analytics are all around us. They inform the push notifications on SuperApps, QR code payments in cafes and supermarkets, biometric check-in at airports, and the videos and memes liked and shared on social media.

As we enter an era of 5G, connectivity and data-enabled mobility innovations, like autonomous cars and electric vertical take-off and landing aircraft, will no longer seem futuristic.

Custom-designed drones use AI and data analytics to assist farmers to automate cultivation processes and boost crop yields in China, Vietnam, and Indonesia. Conference presentations feature complex graphics and images created by AI design apps. In Japan, an autonomous in-car safety system uses intelligent technology to take control if the driver suffers a heart attack or stroke. 

Takeaways: 
•    AI applications are transforming consumer interactions with brands, governments, and service providers
•    Enhanced data assimilation and analytics increasingly influence daily consumption decisions and transactions
•    AI-powered technologies will revolutionize urban mobility and zero-carbon transport and travel

Expanding and optimizing digital economies is a stated objective of governments across Asia. Sustained growth in eCommerce combined with advances in intelligent and interactive technologies will stimulate business growth and investment. Research into AI and machine learning innovation is also powering the region’s vibrant start-up sector. 

Investment in technical capacity will increase as companies face competitive pressures to innovate and upgrade existing capabilities. Spending on big data analytics solutions will rise 19 percent in 2022 across the Asia Pacific, according to IDC’s Worldwide Big Data and Analytics Spending Guide. Regional spending could exceed USD 53 billion by 2025. China’s AI spending alone is forecast to be valued at over USD 26 billion in 2026, or nearly nine percent of global big data investment.

Takeaways: 
•    Significant AI-related investment will focus on four major endpoint industries: professional services, government and public services, digital finance, and telecoms
•    Roll-outs of 5G networks will broaden the scope of AI applications across B2B and B2C sectors to boost intelligent marketing and enhance decision-making
•    In addition to driving revenue growth, AI tools will improve process efficiency within teams and across companies

Business-to-business data tools enhance sales performance and operational planning and help customers deliver better service to consumers. DKSH developed bespoke optimization tools that use machine learning and data modeling to improve efficiency across Business Units. 

Portfolio Optimization Engine uses data clustering to help sales agents make real-time recommendations of new and complementary products to their Consumer Goods and Healthcare customers. This helps customers improve their product offerings for consumers. A conversion rate of around 30-50 percent combines both new sales and repurchase volumes. 

Lead Optimizer is deployed in Technology and Performance Materials markets, where the sales process can be longer. Data analytics help qualify the lead pipeline to analyze the percentage likelihood of winning a sale. It recommends which follow-up actions, such as a product demonstration, quotation, or customer visit, would be most beneficial to complete a sale.

Transport Optimizer uses data from transport operations to optimize the fleet, bundling, timing, and routing of shipments to customers. The tool was tested in Singapore. The simulation modeling identified an optimal delivery schedule that could be achieved using a few less trucks, thereby delivering cost savings.

Takeaways: 
•    Sophisticated data modeling enables sales teams to prioritize product recommendations based on specific business criteria
•    AI-enabled optimization learns and becomes more accurate as more data is captured and analyzed
•    Analyzing shipment and transport route data can identify operational efficiencies and cost savings

Data-enabled customization is driving the Direct-to-Consumer (D2C) sales model, which is burgeoning across Asia. Consumers are using online tools combining personal, brand, and scientific data with machine learning to personalize their favorite products. They are also experimenting with data-powered apps with bespoke colors, flavors, and designs before deciding whether to purchase items.

For young consumers, personalization is a reflex not a nice-to-have. Data tools enable people to participate in the tailoring of everything from digital banking and fashions to meals and travel experiences. In China, consumers can use an olfactory culture map and an AI-powered scent assistant to blend their digital fragrances. A cosmetic brand in South Korea uses AI technology to analyze each consumer’s skin condition and assign a personal skincare consultant to work with them for two months to create fully personalized products.

Takeaways: 
•    Real-time data analytics and machine learning are powering in-the-moment decisions made by consumers
•    Personalized products and services are highly prized by youthful shoppers
•    Hyper customization shows how AI and data analytics are making the consumer purchase cycle more interactive and participative

Commercial decisions based around on collation and analysis are attracting greater scrutiny from government regulators. In 2021, China implemented a Personal Information Protection Law with new rules for firms that collate and store data. The stated goal is to crack down on “the common practice by technology companies of profiting from private information.” The Ministry of Industry and Information Technology also sanctioned leading internet companies for antitrust and infringing consumer rights. 

Singapore recently amended its rules regarding data breaches, with stricter penalties imposed from October 2022. New personal data protection laws are in place in Indonesia and Thailand, with Malaysia preparing to amend its Personal Data Protection Act. Meanwhile, a new law introduced in Vietnam in 2022 requires online companies selling products and services to local consumers to store all data in the market and not offshore. 

Takeaways: 
•    Enforcement across Asia will strengthen relating to online customer data collection, storage, and usage across Asia
•    Companies utilizing data analytics tools should monitor the situation in each market to ensure they comply with changing legal requirements
•    Demonstrating compliance with personal data protection rules builds trust with consumers in increasingly competitive markets