Generative AI (GenAI) has been a major point of discussion in corporate discourse for over two years now. Initially driven by fascination and experimentation, some companies are now advancing towards scaling GenAI applications. However, the pace of these implementations and their anticipated impact on the bottom line vary significantly.
This article is the first in a series focused on Southeast Asia that will explore the tangible impact of GenAI across various industries, beginning with its application in e-commerce. In a recent poll of business leaders from various industries across APAC1, opinions on whether GenAI would significantly impact their company's bottom line over the next 12 months were evenly split, with 50 percent expressing optimism and the rest, scepticism. In conversations with our clients, we see similarly split views. This makes the topic even more interesting and begs the question, 'Are some companies leaving money on the table by not adopting these technologies faster, or are others over indexing on the hype?'
From marketplaces, brands and marketing agencies to logistics providers and enablers, everyone in e-commerce is experimenting with GenAI. A few bigger players are beginning to even use the technology extensively.
Harnessing GenAI to revolutionize customer support
One area where nearly every company we spoke with is harnessing GenAI is in customer support, especially through chatbots. Most e-commerce players anticipate reducing their customer service agents by 20-50 percent over the next 2-3 years, all while boosting customer satisfaction metrics. The most bullish ones believe that up to 80 percent of agents could become redundant in the same time period. However, implementing GenAI in customer contact applications at scale and effectively is no easy feat.
First, there is the challenge of choosing the right solution and deciding whether to collaborate with a partner or tackle it in-house. Training the bot presents another obstacle; the reference materials that work well for humans do not always translate effectively for AI. Moreover, companies must navigate data privacy concerns and legal considerations.
Once these hurdles are cleared, another question emerges: Should support be made easily accessible, even if it means an influx of inquiries? For example, while AI can handle many tasks, it's not yet capable of independently managing actions like processing refunds. The right balance needs to be found, or one would run the risk of falling behind competition in terms of service levels, or on the contrary – overservicing customers in a way that reduces profitability.
Then, there is the critical question of the best operating model once the GenAI solution is implemented at scale. Should companies deploy a few super agents in each country to work alongside AI and address local nuances, or would a small, centralized Center of Excellence be more effective?
Navigating these decisions can be complex, but those who get it right stand to revolutionize their customer support operations and set a new standard in the industry.
Hyper-personalization of marketing content
The second area in which most e-commerce players are experimenting with AI is marketing copy production. Tasks that once required hours of work by skilled designers and copywriters can now be accomplished in minutes through AI-driven solutions. This includes generating various types of marketing copy, such as banners, ads and email campaigns. These can be tailored to individual customer preferences and produced at scale, enhancing both efficiency and relevance.
In the domain of live commerce, generative AI is increasingly utilized to create engaging scripts for live presentations and customer interactions. Observing trends in China, often a precursor for Southeast Asia, it is evident that digital humans and avatars will host at least some of the ever so popular live commerce sessions.
The strategic application of this technology is compelling due to its dual promise of higher efficiency and enhanced customer targeting, both of which have the potential to significantly improve margins and revenues. By leveraging AI, companies can create highly personalized marketing campaigns that resonate with individual customers, thereby driving engagement and conversion rates.
However, it is crucial to manage these technologies carefully. Overreliance on AI for targeting can lead to customer fatigue and the perception of being overwhelmed by AI-driven marketing efforts. This could erode customer trust and loyalty. Therefore, a balanced approach that combines the efficiency of AI with the empathy of human touch is essential to maximize the benefits while mitigating risks.
Product descriptions and reviews
Generative AI is revolutionizing how e-commerce platforms handle product descriptions and reviews, making life easier for sellers and improving the online shopping experience for customers. AI can automatically generate detailed, accurate, and engaging product descriptions and pictures by analyzing product attributes and customer feedback. This reduces the time and effort required by sellers, enabling them to focus on other critical aspects of their business.
For customers, AI simplifies the process of writing reviews by offering prompts and suggestions based on their interactions and purchase history. This not only encourages more customers to leave reviews but also enhances the quality and relevance of the feedback provided.
Ultimately, these advancements bring the online shopping experience closer to in-person shopping, where customers can gather comprehensive information about products. By providing richer product descriptions and more detailed reviews, AI helps customers make informed purchasing decisions, thereby increasing their satisfaction and trust in the platform. This leads to higher conversion rates and fosters long-term customer loyalty.
What is the impact on the bottom line?
E-commerce remains a highly manual industry. For instance, Shopee, the largest marketplace in Southeast Asia is part of Sea Group, which employs around 50,000 people2. Many tasks performed by employees in e-commerce companies, such as marketing content generation and responding to customer inquiries, can be automated using GenAI.
However, since all market players have access to this technology and the market is highly competitive, not all cost savings will be retained by the companies. Some of these savings will be reinvested into enhancing the customer experience. For example, several companies are already improving the accessibility and effectiveness of their contact centers and chatbots, leading to higher-quality support. This, in turn, has resulted in a disproportionate increase in the number of customer service tickets handled.
While some of the savings will translate into higher service levels rather than direct cost reduction, this investment also boosts the overall level of e-commerce compared to offline retail, thereby increasing the market size. Overall, we expect that GenAI will enhance the margins of those who successfully leverage it, while companies that fail to adapt may fall behind.
The lessons learned
As with any technology, there is a considerable risk of getting stuck in pilot mode and not progressing to production swiftly. The difference with GenAI is the rapid adoption rate seen in some companies, which creates the risk of falling behind for players who have stayed away. Competitors who adopt GenAI faster can reduce costs, improve service levels and quickly capture market share. Additionally, these early adopters can reset their margins to more sustainable levels, further widening the gap.
Footnotes
1 LinkedIn poll, N=85
2 Sea Group Annual Report, FY2023
Originally published 27 August 2024
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