Southeast Asia savvy online shoppers spend 31% more at $11.5 billion. Discerning online buyers in Southeast Asia spend 31 per cent more each month than general consumers. Across six regional economies, they will generate 11.5 billion dollars in annual marketplace sales in 2026. A joint study from Lazada and commerce analytics group Cube defines roughly 24 per cent of regional consumers as savvy shoppers. Another 18 per cent sit immediately below that threshold. These buyers demonstrate distinct commercial habits. They cross-check merchandise across channels, inspect merchant credentials, and routinely pay premiums for guaranteed authenticity and transaction safeguards. How purchasing behavior splits across markets. Penetration of these higher-spending consumers varies widely by country. The Philippines leads Southeast Asia with 36 per cent of its online buyers qualifying as savvy. Indonesia follows at 28 per cent and Vietnam at 25 per cent. Thailand registers 22 per cent, while Malaysia records 20 per cent. Singapore sits at the bottom of the regional ranking at 9 per cent. Friction points also differ across borders. Shoppers in Malaysia and Vietnam report product verification as their primary hurdle during online purchases. Buyers in Singapore, Indonesia, and the Philippines cite buyer protection and seller confidence as their main challenges. Thai consumers report an even split between verification and security concerns. Value replaces pure price discounts. Shoppers across Southeast Asia show an increased willingness to invest time to secure better transactions. About 43 per cent of surveyed consumers spend extra time searching for improved offers. Another 41 per cent delay purchases to find better timing. Meanwhile, 36 per cent conduct detailed price comparisons before checking out. Price concessions lose traction when they compromise trust. Only 14 per cent of consumers say they would sacrifice authenticity indicators for a lower price. Just 13 per cent would forfeit purchase protections to obtain a steeper discount. Among savvy buyers, 47 per cent state they will pay extra fees for certified order protection, compared to 30 per cent among general consumers. Discovery moves outside marketplace walls. Transaction journeys now start well before buyers enter marketplace apps. The study finds that 83 per cent of savvy consumers discover products outside primary marketplace catalogs, compared to 42 per cent of general buyers. 86 per cent consult third-party information channels during purchase evaluation. A full 91 per cent verify seller track records across external web sources. Savvy consumers also buy more frequently and spread their spending across competing channels. Some 58 per cent shop online several times each week, compared to 35 per cent of baseline consumers. Mall environments capture 53 per cent of this cohort, compared to 40 per cent for general shoppers. Multi-homing is standard practice. About 82 per cent of savvy shoppers actively use all three major marketplace platforms across the region, against 61 per cent among the general shopper base. Commercial demands on digital merchants. For marketplace merchants and brand principals, the findings demand a recalibration of promotional spending. Pure discounting drives immediate volume. However, higher-value shoppers demand verified supply chains, fast dispute resolution, and consistent branding across external touchpoints before committing their baskets. "Southeast Asia's eCommerce market is no longer defined by whether consumers shop online, but by how confidently and effectively they do so," said Simon Torring, Co-Founder of Cube. Platform operators now face the operational task of retaining these multi-homing consumers as growth shifts from user acquisition to basket optimization. Marketplaces that fail to guarantee authenticity will see the most profitable quartile of regional demand migrate to rival platforms offering tighter brand verification standards. Questions & answers. Q. What specifically characterises the shopping behaviour of these savvy online consumers? A. These buyers cross-check merchandise, inspect merchant credentials, and routinely pay premiums for guaranteed authenticity and transaction safeguards. They also invest time searching for improved offers, delaying purchases, and conducting detailed price comparisons. Q. Which Southeast Asian countries have the highest and lowest proportion of these discerning online shoppers? Q. What are the key challenges faced by online shoppers in Malaysia, Vietnam, Singapore, Indonesia, and the Philippines? Q. How do these savvy consumers typically discover products and evaluate purchases compared to general buyers? Reader pulse Is the shift from discounts to trust a good strategy? 18,446 votes so far

AI reshapes product discovery in Southeast Asia, but human trust still drives purchases, new report finds. by Caleb Baldo July 30, 2026. Its What's NEXT in Marketing 2026 Conference Series returns to the Philippines, Singapore, Hong Kong, Indonesia, Malaysia - and for the first time in Thailand! Brace yourself for bold ideas driving the next marketing wave. Click here to learn more! Singapore - Southeast Asian consumers are increasingly turning to generative AI to discover products. Still, human recommendations continue to determine whether they actually buy, according to a new report from impact.com, Cube, and Dentsu. The fourth edition of the annual E-commerce Influencer and Affiliate Marketing in Southeast Asia report found that one in four (24%) consumers in the region now use generative AI tools such as ChatGPT, Gemini, and Claude to support their shopping journey, marking AI's emergence as a new product discovery channel. However, the report found that recommendations from family and friends remain the most trusted source when it comes to purchase decisions, with respondents rating them 2.42 out of 4 for influence, ahead of online reviews at 2.36 and creators at 1.98. impact.com, described as the world's leading global infrastructure for partnership-driven commerce, produced the report in collaboration with e-commerce market intelligence provider Cube and global advertising and marketing agency network Dentsu. The findings draw on insights from 2,400 consumers, alongside Cube's regional e-commerce market data and interviews with marketers, creators, publishers, and industry experts across Singapore, Indonesia, Thailand, Vietnam, Malaysia, and the Philippines. The report found that two in three consumers (67%) have bought a product specifically because a creator recommended it, reinforcing that trust and authentic reviews remain central to commerce even as AI reshapes discovery. It also found that AI-generated answers are themselves shaped by third-party voices, including creators, publishers, and reviewers, whose content trains and informs what these tools recommend. For brands, this means activating partners does not just drive sales directly; it also shapes how a brand is surfaced and recommended by AI. The report concluded that AI is not replacing existing discovery channels but is instead becoming another layer within an increasingly interconnected commerce ecosystem. As consumers move between AI assistants, marketplaces, creators, publishers, retail media, and brand-owned channels, brands need integrated, always-on partnership strategies to stay visible and relevant at every touchpoint. "Every major shift in e-commerce has changed how consumers discover products, from search engines and marketplaces to social media, and AI represents the next evolution," said Nick Randall, AVP, Customer Growth, APJ at impact.com. "But while discovery continues to evolve, trust remains remarkably consistent. Consumers still look to creators, publishers, and trusted recommendations to validate their purchasing decisions. The opportunity for brands isn't choosing between AI and partnerships, it's understanding how they work together to create more meaningful customer journeys and ultimately drive commerce." Randall added. The report also identified marketplaces as the leading discovery channel, with seven in ten (71%) consumers discovering new products through platforms such as Shopee, Lazada, and TikTok Shop, followed by search engines at 57%. AI adoption varied significantly across the region, with Vietnam (34%) and Indonesia (31%) leading in generative AI use for product discovery, while Singapore recorded the lowest adoption at 14%. The findings further showed that AI is reinforcing reliance on creators rather than replacing it, with 40% of consumers saying generative AI has not changed how much they rely on creators for product recommendations. Trust between the two remains closely split, with 38% trusting both equally, 36% leaning toward creators, and 25% leaning toward AI. Nearly half (49%) of affiliate purchases were found to be driven by trust and validation, followed by utility and convenience at 28%, with consumers continuing to cite convincing recommendations and trusted reviews as stronger purchase drivers than discounts or promotional offers. With tighter regulations reshaping APAC's social-led financial sector, managing agent activity and misinformation have never been more critical. Discover how banks and insurers are strengthening oversight and protecting their brands in this new industry study by Meltwater - download the free guide here. With public conversations reshaping Australian insurance reputation, managing online sentiment and the trust gap has never been more critical. Discover how providers are addressing friction and protecting their brands in this new industry report by Meltwater - download the free guide here.

Cube raises US$3.7M to fix e-commerce's visibility problem. Cube, a startup that tracks e-commerce markets for consumer brands, internet platforms and investment firms, has raised a US$3.7 million Series A round led by Betatron Venture Group, with follow-on backing from M Venture Partners and participation from strategic angels. The funding lands at a moment when the economics of online commerce are becoming harder, not easier, to read. Brands have long relied on established data providers to understand what is happening in supermarkets, pharmacies and other offline retail channels. Online, that same visibility is far less developed. Product listings shift constantly, sellers bundle items in different ways, pricing changes by the hour, and marketplaces do not always present clean, consistent data. That chaos is precisely where Cube has built its pitch. Founded in 2022 and headquartered in Bangkok, the startup sells market intelligence to more than 20 enterprise customers, including global consumer goods groups, internet platforms and investment firms. Its core promise is simple: take fragmented e-commerce data, structure it, enrich it and turn it into something companies can actually use to make decisions. For brands, that means tracking online market share, identifying where demand is growing and understanding how pricing, promotions and product visibility affect performance. For investors and platforms, it means building a clearer view of the size, shape and trajectory of digital commerce categories across emerging markets. Why this matters now. The broader market backdrop is helping startups like Cube make their case. In offline retail, measurement has been built over the course of decades. Categories are relatively stable, product attributes are standardised, and distribution channels are familiar. E-commerce is a different beast. Categories can fragment overnight - cross-border sellers muddy comparisons. A single item can appear in multiple formats, pack sizes or promotional bundles. In many high-growth markets, the data infrastructure around all of this remains thin. That leaves brands trying to answer basic questions with imperfect tools: Which sub-category is actually growing? Where is the share being won or lost? Are consumers shifting to smaller packs, premium products or multipacks? What is happening to visibility on digital shelves as marketplaces tweak search and recommendation algorithms? Cube is betting that enterprises will increasingly pay for answers. The company says its AI-enabled product tagging systems are central to its edge, allowing it to classify products at a deeper level than standard market dashboards typically allow. That includes breaking down dimensions such as pack size, primary benefit and target age group, and more recently, splitting bundled products to identify what is actually being sold inside combo offers. That type of granularity matters because online shelves are not organised like physical ones. A shampoo is no longer just a shampoo; it might be a travel-size anti-dandruff bundle sold with a conditioner under a time-limited promotion by a third-party merchant. If a brand cannot see those layers, it can misread both consumer demand and competitive pressure. As Cube co-founder Simon Torring put it, "enterprises would need more reliable and accurate market data and insights to win online, and this has proven even more true in the age of AI". Expansion beyond Southeast Asia. Cube started with a focus on Southeast Asia, where marketplace-led e-commerce growth has created large but uneven pools of digital demand. That regional base remains important, but the startup is now pushing further into North Asia and Latin America, two markets it describes as priorities for expansion. Part of that plan includes expanding operations in Hong Kong SAR, which the company says will serve as a hub for North Asia-based clients and strengthen support for investment managers using its Tradewinds strategic market data product. The move is notable. Many startups serving Southeast Asia struggle to scale beyond the region because local market structures differ sharply across countries. Consumer behaviour, marketplace dominance, language, logistics and regulatory environments all vary. Expanding into North Asia and Latin America suggests Cube believes the underlying data problem it solves is broad enough to travel, even if local execution will still matter. That is also where the new funding is likely to be tested. Raising a Series A is one thing; proving repeatability across multiple geographies is another. Betting on infrastructure, not just dashboards. Betatron's backing reflects a wider investor appetite for business-to-business software that sits underneath major industry shifts rather than merely riding them. In Cube's case, the bet is not just on analytics dashboards but on the infrastructure needed to make e-commerce data usable. That includes data collection, product normalisation, tagging, enrichment and interpretation. If the raw material is poor, the insight layer on top quickly becomes unreliable. Matthias Knobloch, Managing Partner and CEO of Betatron Venture Group, bluntly framed the gap, arguing that brands have solid tools for brick-and-mortar performance but still lack the same visibility in digital channels, where data is "messy, fragmented, and constantly in flux". That assessment is hard to argue with. Legacy market intelligence firms remain powerful in offline channels, but online commerce has produced a different set of technical challenges. Marketplaces do not expose data uniformly. Sellers manipulate listings. Product taxonomies vary from one platform to another. Promotional mechanics are more dynamic. In frontier and emerging markets, those problems are often magnified. Cube's opportunity lies in turning those pain points into a subscription business that feels indispensable to large customers. The startup says its revenue has more than doubled annually since launch, and its business model is built predominantly around enterprise subscription plans. That is encouraging on paper, although the release does not disclose absolute revenue, retention or customer concentration figures, which remain key markers for any software company claiming strong enterprise traction. The AI angle, minus the hype. Like many startups raising capital in 2026, Cube is leaning into the language of AI. But unlike businesses that sprinkle the term over generic automation, its use case is at least rooted in a concrete problem: making chaotic commercial data more precise and searchable. That distinction is crucial. For all the noise around generative AI, many enterprise buyers still care more about whether a system can improve data quality, reduce manual classification work, and surface useful signals faster than about flashy interfaces. In e-commerce intelligence, those gains can directly translate into pricing decisions, assortment planning, category expansion, and investment strategy. Cube co-founder Sarabjit Singh said recent advances in AI have helped the company push reporting into deeper levels of detail, including the ability to separate bundled products and examine what sits inside them. That may sound technical, but it points to a practical reality: better parsing of online listings can lead to better business decisions. What comes next. Cube is now entering a more demanding phase. The company has moved beyond proving that there is demand for better e-commerce market data in Southeast Asia. The next challenge is scaling that proposition across regions while defending the quality and accuracy of its insights as datasets become larger and more complex. That will require more than good fundraising headlines. It will require sustained product performance, strong enterprise retention and the ability to show that its intelligence is not merely interesting, but operationally valuable. Still, the direction of travel is clear. As consumer spending continues to migrate online and digital shelves grow more crowded, companies that cannot properly read e-commerce markets risk flying blind. Cube is trying to become the system that tells them where the market is moving before their competitors see it. For a startup born in Southeast Asia, that is an ambitious play. The new capital gives it more room to make it. Post navigation. 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