Authors: Kenneth Koh, Yahoo and Michele Yeung, Teads
Introduction
The application of Artificial Intelligence (AI) in the advertising industry across Southeast Asia and India has been rapidly evolving, driven by technological advancements and the expanding digital landscape. These regions, with significant growth in internet and smartphone penetration, are fertile grounds for AI-powered advertising solutions.
This article is the second part of a two-part series from the IAB SEA+India Regional AdTech and Innovation Council. Building on the strategic insights presented in the first article, here we explore the practical, tactical execution of AI in advertising, offering a comprehensive view of how this technology is applied on the ground. From personalisation and targeting to enhanced customer interactions, this article aims to provide concrete examples and case studies demonstrating AI’s transformative impact on advertising tactics
In Southeast Asia, countries have shown considerable interest in adopting AI for advertising purposes. Some notable trends and developments include:
1. Chatbots and Customer Interaction: Chatbots powered by AI have
gained popularity for customer interaction. Companies like AirAsia and Traveloka use chatbots to provide real-time assistance to users, answering queries and helping with bookings.
AirAsia’s new AI-powered concierge, Ask Bo, will provide guests with a more proactive, attentive, and hassle-free experience. Ask Bo will offer live updates on flight status, baggage information, and real-time departure timings. Additionally, guests will be able to use Ask Bo to change flights, request refunds, and choose service recovery options. The most significant difference between Ask Bo and its predecessor, AVA, is that Ask Bo will allow guests to speak in person to human agents during the interaction.
Overall, Ask Bo is a significant improvement over AVA and represents a major step forward in AirAsia’s commitment to providing its guests with the best possible travel experience.
2. Personalisation and Targeting: Companies are using AI to analyse user behaviour, preferences, and data to deliver personalised ads. Brands like Lazada and Shopee are using AI algorithms to offer personalised recommendations and promotions based on users’ browsing and purchase history.
India’s advertising industry has also embraced AI-driven solutions to enhance efficiency and reach. Some trends specific to India include:
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Video Content Enhancement: AI is being utilised to enhance video
content. Britannia Industries, an Indian multinational in the FMCG sector, demonstrated the transformative power of AI in video production with its 2023 campaign, “1947 & More.” The company’s use of AI, specifically deep learning and neural networks, played a critical role in developing highly realistic and engaging videos of Indian freedom fighters. This approach highlights AI’s expanding capability in enhancing video content, setting new standards in the advertising industry for creating deeply impactful and emotionally resonant narratives.
Source: Britannia Industries
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Language Localisation: India is a linguistically diverse country, and AI is being used to personalise ads in regional languages. Brands like Amazon India use AI to translate its ads into seven regional languages: Hindi, Tamil, Telugu, Kannada, Malayalam, Bengali, and Marathi. This allows Amazon India to reach a wider audience of Indian consumers and to deliver more relevant ads to each individual user, without having to shoot and dub separate videos for each language.
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E-commerce and Recommendation Engines: E-commerce giants like Flipkart use AI-driven recommendation engines to suggest products to users based on their browsing and purchase history, enhancing the shopping experience. For example, if a customer frequently purchases electronic accessories, Flipkart’s recommendation algorithm will display similar products when the customer visits the website. By tailoring product recommendations to individual customers, Flipkart is able to enhance the customer experience and increase sales.
Best Practices for Leveraging AI in Advertising Across Southeast Asia and India
Specific applications and advancements in AI-driven advertising can vary within each country in Southeast Asia and India due to cultural, linguistic, and market differences. As the digital landscape continues to evolve, AI’s role in the advertising industry in these regions is expected to grow further, driving more personalised and effective ad campaigns.
As AI evolves and becomes more integrated into our daily lives, advertising professionals need to adopt best practices when using AI to enhance advertising and marketing activities. These best practices include:
Start with your goals
What do you want AI to help you achieve? Do you want to automate tasks, personalise ads, or target audiences more effectively? Once you know your goals, you can choose the right AI tools and techniques.
Shopee, a popular e-commerce platform in Southeast Asia, aims to enhance the user experience and increase the likelihood of conversion. It utilises AI to personalise its homepage for each user based on their browsing history and preferences.
Consider the data you have
AI algorithms need data to learn and make accurate predictions. Make sure you have enough data that is relevant to your goals. If you don’t have enough data, you may need to collect more data or use a different AI tool.
Tokopedia, an ecommerce platform in Indonesia, enhances user experience with the use of data such as purchase history, browsing behaviour and demographics that is analysed by AI to deliver targeted advertisements with the higher likelihood of engagement and conversions.
Across its ride-hailing, deliveries and financial services offerings, Grab processes over 10 million transactions daily across Southeast Asia. The volume of people transacting daily on Grab across the region means there are ample opportunities to get noticed by new audiences–and potential buyers. Based on this year’s first and second quarter data, Grab’s ad division – GrabAds – will contribute approximately $100 million to overall revenue on an annualised basis.
Artificial hallucination is a phenomenon where AI models generate outputs that are not real or factual. It can happen in a variety of ways, such as when an AI model is trained on biased data, when the wrong model is chosen for the task at hand, or when the model is not properly monitored for signs of hallucination.
There are a number of best practices that can be followed to reduce the risk of artificial hallucination, including:
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Using high-quality data to train the model: AI models are trained on data, and the quality of the training data has a significant impact on the performance of the model. By using high-quality data, organisations can help to ensure that their AI models are less likely to hallucinate.
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Being careful with biased data: AI models can learn the biases that are present in their training data. If the training data is biased, the AI model will be more likely to generate outputs that reflect those biases. By being careful with biased data, organisations can help to reduce the risk of AI hallucination.
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Using appropriate models for the task at hand: There are a variety of different AI models available, each with its own strengths and weaknesses. It is important to choose the right model for the task at hand. If the wrong model is chosen, it is more likely to hallucinate.
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Monitoring the performance of the model for signs of hallucination: It is important to monitor the performance of AI models for signs of hallucination. If a model is hallucinating, it is important to identify the cause of the hallucination and take steps to address it.
Be patient with the learning curve
AI models need time to learn and improve. Don’t expect them to be perfect right away. It may take several weeks or months for an AI model to reach its full potential.
SeaMoney is a digital financial services platform in Southeast Asia that uses AI to assess credit risk and provide personalised financial products and services to its users. However, like any AI model, SeaMoney’s AI model needed time to learn and improve in order to accurately assess the creditworthiness of its users. At first, the model was not very accurate, and some users were denied loans even though they were qualified. However, over time, the model improved its performance, and SeaMoney was able to provide loans to more users.
Use AI in conjunction with human judgment
AI is a powerful tool, but it’s not perfect. It’s important to use AI in conjunction with human judgement to make sure the results are accurate and ethical. For example, AI can be used to identify potential customers who are likely to be interested in a product. However, it’s up to the human marketer to decide whether or not to target those customers. This is to also avoid the potential danger of artificial hallucination where the AI generates a confident but false response.
Traveloka, a travel booking platform, implemented AI-driven chatbots for customer support. Initially, the chatbots required human intervention, but over time, they improved their responses and reduced the need for manual intervention.
Be transparent about your use of AI
In general, users trust generative AI. A survey by the Capgemini Institute found that 70% of Singaporean consumers, compared to 73% of consumers globally, trust content created by generative AI. This spans many aspects of life, from financial planning and medical diagnosis, to relationship advice.
The trust can be enhanced if your customers know that you’re using AI to target ads and personalise their experience, such as including a disclosure in your privacy policy stating that you use AI to target ads. For example, eCommerce platform, Lazada, clearly communicates to its users that AI algorithms are used to recommend products based on browsing history and purchase behaviour, fostering trust and acceptance.
Make sure you follow all applicable laws and regulations. For example, the Personal Data Protection Act (PDPA) in Singapore restricts the use of personal data for the purpose of advertising. This includes targeting ads based on race, ethnicity, or gender.
Specifically, the PDPA prohibits the processing of personal data for the following purposes:
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To discriminate against any individual or group of individuals
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To engage in unlawful activities
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To cause harm to any individual or group of individuals
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To violate the privacy of any individual or group of individuals.
The PDPA also requires organisations to obtain the consent of individuals before using their personal data for marketing purposes. This includes consent for the use of personal data to target ads.
In addition to these best practices, here are some additional tips for advertising professionals who want to use AI effectively:
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Start small. Don’t try to implement AI across your entire marketing campaign all at once. Start with a small pilot project to test out the technology and see how it works. This will help you to identify any potential problems and make sure that AI is a good fit for your business.
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Get buy-in from your team. AI can be a disruptive technology. Make sure your team is on board with the changes before you start implementing AI. This will help to ensure that everyone is working together towards the same goals.
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Set realistic expectations. AI is not a magic bullet. It can’t solve all of your marketing problems. Set realistic expectations for what AI can do and don’t expect it to replace human creativity and judgement.
Conclusion
As we look back at each significant phase of the internet advertising industry, how marketers respond to innovative technology is as equally important as how ad-tech companies adapt to the emerging use-cases and demands of consumers.
The tactical execution of AI in AdTech across Southeast Asia and India is shaping a rapidly evolving advertising landscape. This evolution is marked by key trends such as AI-driven personalisation and targeting, as evidenced by Lazada and Shopee, and enhanced customer interactions through chatbots, like AirAsia’s and Traveloka’s initiatives. In India, particular focus is placed on language localisation in ads and AI-enhanced video content, with notable efforts by Amazon India.
This article’s insights into the tactical applications of AI complement the strategic perspectives covered in the first part of our series. Together, these articles highlight the comprehensive impact of AI in AdTech, underscoring the importance of technological responsiveness to consumer needs and behaviours. The future of AdTech is poised for even faster AI advancements, focusing on deeper content personalisation and insightful automated ad campaigns.