As we embark on the year 2024, with the increasing Generative AI democratization, businesses are undergoing a profound transformation in their data and artificial intelligence strategies to enhance consumer engagement. The words of Sam Altman, CEO of OpenAI, resonate strongly, highlighting society’s adaptability and intelligence, mentioning that “Society is capable of adapting, as people are much smarter and savvier than a lot of the so-called experts think”. According to Gartner1, by 2026, more than 80% of enterprises will have used generative AI APIs and models and/or deployed GenAI-enabled applications in production environments, up from less than 5% in 2023.
As generative AI continues to dominate current trends, it is crucial to acknowledge other significant developments that deserve equal attention. These include the growing significance of data compliance, leveraging AI to make creative advertising content, and the paradigm shift in our mindset to data mesh.
Key Data Analytics & Marketing Trends in APAC for 2024: As businesses in the Asia-Pacific (APAC) region seek to unlock invaluable consumer insights and enhance customer experiences, the following five data trends warrant close attention:
Rise of Prompt Engineering: The success of generative AI models relies heavily on the timely and skillful formulation of prompts as they directly impact the output quality. A carefully constructed prompt can produce text that emulates human-like precision, whereas a poorly devised prompt may yield text that is confusing, irrelevant, or offensive.
Responsible and ethical AI: The responsible use of AI and robust privacy practices are becoming paramount as organizations navigate the ethical and legal implications of advanced technologies. Implementing comprehensive AI governance frameworks ensures transparency, accountability, and the protection of individuals’ privacy rights. This allows AI to generate more positive impacts rather than a threat to society by making not only the right business decisions but also complying with ethical rights.
Multimodal Large Language Models (LLMs): LLMs are currently expanding their capabilities to comprehend and analyze multimedia content beyond just text. This advancement brings forth fresh opportunities for AI applications in various domains such as generating content, examining media, and interactive entertainment.
The Government Technology Agency (GovTech) in Singapore is developing a chatbot powered by generative artificial intelligence (GenAI) to assist individuals in their career transitions and decision-making. By asking a series of questions about a person’s interests and career journey, the chatbot can help them discover potential career opportunities, the necessary skills for transitioning, and available training courses. Chang Sau Sheong, the Deputy Chief Executive for product and engineering at GovTech, mentioned during an interview with Singapore media at Google Cloud Next 2023 in San Francisco that the chatbot will aid in expanding the government’s career coaching program, which is currently supported by volunteers2.
Learn more on Ekimetrics’ GenAI for Business offer here.
As per Statista3, an estimated 75% of marketers across the globe continue to rely on data gathered from third-party cookies to shape their advertising strategies and drive brand awareness and sales.
Therefore, Google’s announcement to phase out third-party cookies in Chrome by the end of 2024 has left marketers feeling uneasy. Not surprisingly, the deprecation of cookies and its associated consequences have emerged as the primary concerns for marketers in 2023. Together with Safari and Firefox limiting the ability to leverage third-party cookies as well as increasing awareness of data protection regulations, businesses need to prioritize first-party data strategy, which is collecting the data directly from customers. By respecting data privacy regulations and obtaining explicit consent, organizations can build trust and leverage valuable insights derived from first-party data to personalize customer experiences.
As a result, the demand for Data Clean Rooms (DCR) surged. DCR refers to a controlled and secure environment wherein multiple companies or divisions within a company can collaborate by pooling their data for joint analysis, it ensures that shared data usage continues to follow privacy laws. Within the data clean room, any personally identifiable information (PII) is anonymized, processed, and stored in a manner that complies with relevant regulations.
Data clean rooms provide numerous benefits to content providers, marketers, and advertisers, including:
HSBC recently conducted a proof of concept with the Global Shipping Business Network (GSBN)4, a blockchain consortium based in Hong Kong. The aim was to explore the use of DCR, for sharing supply chain data to support trade finance applications. During the trial, GSBN collected synthetic shipping records from its carrier members, which were then processed and aggregated in a privacy-safe environment provided by Decentriq. HSBC was able to access this data, including information on the number of shipments, cargo distribution, and average cargo quantity, to make more informed financing decisions. This innovative use of alternative data presents an opportunity to simplify trade finance by providing banks with timely, accurate, and relevant insights into their clients’ activities.
Read more on Data Clean Rooms here.
Discover our series on Customer Data Strategy in APAC here.
In today’s data-driven world, having the ability to analyze data quickly and accurately is essential for any business. By bringing Generative AI and Natural Language Processing (NLP) work together, non-technical users could “talk” with their business data, much in the same way you “ask Google” a question. The powerful backend algorithms empower them to handle and interpret vast quantities of data. It is like having a brilliant data analyst available for every employee. Trends and patterns can now be identified by utilizing machine learning and NLP embedded in the chatbots, and to further make well-informed judgments from the data. Thus, AI chatbots are being increasingly applied and have become more important in data analytics in recent years. AI chatbots are also capable of addressing the difficulties associated with manual data analysis. Here are several advantages of employing a human interface chatbot for data analytics:
As a prominent player in the tech industry, Google has introduced Duet AI5, an artificial intelligence assistant designed for business users. Duet AI enables fast and simple conversational queries that empower users to get answers and refine results into visuals and reports. This innovative assistant is capable of seamlessly navigating through business data, such as sales transactions and written reports, interpreting queries, retrieving necessary information, and generating insightful answers behind the scenes.
According to a survey by Wyzowl6, in 2023 91% of businesses use video as a marketing tool, with 96% of marketers stating that video has helped increase user understanding of their product or service, and it would be an important part of their marketing strategy. The rise of short video formats, popularized by platforms like TikTok and Instagram Reels, presents marketers with new opportunities to engage with consumers. With these platforms leveraging AI-powered algorithms, businesses can optimize their short video ad campaigns, targeting specific audiences and delivering captivating content in a concise and impactful manner.
In this dynamic landscape, companies are continually redefining their strategies to connect with consumers in more precise ways. A prime example is Coca-Cola’s recent campaign7, which leverages generative AI combined with captivating storytelling techniques to create intriguing ad videos.
Marketers are now harnessing AI to make creative content, optimize social media advertising, analyzing engagement behavior and audience preferences. By utilizing machine learning algorithms, they can automatically conduct A/B tests on various ad variations, optimize campaigns, analyze campaign performance, and maximize return on investment (ROI) for different customer segments.
In the age of Big Data, organizations are constantly faced with the challenge of managing massive volumes of data. Enter Data Mesh, a new paradigm that advocates for a decentralized, domain-oriented approach to data management within an organization. Coined by Zhamak Dehghani, a principal consultant at Thoughtworks, Data Mesh seeks to address the limitations of centralized data management by treating data as a product.
In APAC, Grab has successfully implemented data mesh. Grab is a Singapore-based ride-hailing and delivery company that expanded its services to include financial and food delivery services.
Grab implemented a data mesh architecture to efficiently manage and utilize their vast amount of data across different business units and functions. They adopted a decentralized approach where each business unit owns their data domain and is responsible for data governance and quality within their domain.
By implementing data mesh, Grab was able to democratize data access and empower domain experts to own and utilize their data effectively. This allowed for faster decision-making, improved collaboration, and innovation across various teams within the organization. Data mesh architecture enabled Grab to scale and expand its services across different verticals while maintaining data autonomy and agility.
Data Mesh represents a paradigm shift in the way organizations manage and utilize data. By treating data as a product and distributing the responsibility of data management, organizations can achieve improved data quality, faster decision-making, and increased innovation. As data continues to play a crucial role in driving business success, embracing
Data Mesh can be a game-changer for organizations seeking to unlock the true value of their data assets.
Learn more about Radians – Ekimetrics’ new Data Science Platform here.
In the ever-evolving landscape of consumer insights, APAC businesses must stay attuned to the prominent data trends shaping the year 2024. By embracing responsible AI practices, prioritizing privacy and compliance, capitalizing on AI-powered advertising, and recognizing the value of data mesh, organizations can unlock invaluable consumer data and drive better customer experiences. These trends underscore the significance of ethically leveraging data and advanced technologies to foster sustainable growth and customer-centric innovation.