Profound plans Singapore hub for AI search marketing

Profound plans to hire more than 15 people in Singapore over the next 12 months, according to its Nov. 2 announcement. The AI-search marketing vendor says it will open an office in the city’s central business district in the fourth quarter of 2026 and place its Asia Pacific headquarters there.

The office will support regional leadership, customer and go-to-market teams serving Southeast Asia, Japan, Australia and New Zealand. Planned roles cover management, sales, engagement and account management. Some New York staff are expected to relocate for one year to help establish operations.

James Cadwallader, Profound’s co-founder and CEO, called AI “the new front door to every business.” He links the opportunity to brand strategy, search analytics and marketing execution, where customer context and local market knowledge matter. His case supports local investment, not proof of a mature regional market.

An office opening shows where Profound has invested. It does not establish that businesses across Asia Pacific have adopted AI-answer measurement at scale.

How much AI shopping activity is Profound reporting?

Profound’s analysis of 1.8 million anonymized Singapore conversations with ChatGPT and Gemini found a 23% relative increase from January to September 2026 in the share involving research, comparison or purchase of products and services.

This is a relative increase in the share of commerce-related conversations, not a 23-percentage-point jump and not a conversion-rate result. Profound did not disclose enough detail about the sample, intent classification or representativeness for an independent assessment. The figures measure conversations, not purchases.

What does Profound’s software do?

Profound began with a system for tracking brand visibility in AI-search answers. Its September product update describes AI Marketer as a tool for identifying opportunities and coordinating competitive analysis, content updates and paid campaign work.

Context Manager is intended to bring company and team information into those workflows. The product has therefore moved beyond reporting toward agent-supported marketing operations, although the November announcement did not disclose subscription prices, setup fees or other customer costs.

Ranked search rewards page position. An AI answer can name, compare, paraphrase or omit a brand inside one response. Marketers need to separate visibility, recommendation quality and downstream commercial results rather than treating them as one measure.

Visibility may become a reporting metric before it becomes a proven revenue metric. AI citations should not be treated as interchangeable with leads or sales.

Knowing that an answer omits a product does not identify which product page, review or third-party source deserves attention. Closing that gap may require SEO, communications, customer-content and advertising teams that do not normally share one operating dashboard.

Which competitors offer similar visibility tools?

• Profound: Links AI-answer monitoring with an agent workbench and campaign tools.
• Semrush: Combines AI brand-visibility tracking with established search-marketing tools.
• Peec AI: Tracks brand mentions and prompts, benchmarks competitors and analyzes cited sources.

Profound is not alone in AI-answer monitoring. These services overlap on measurement, although their product scope and operating workflows differ.

What does the Bazaarvoice partnership add?

Profound’s October partnership with Bazaarvoice connects AI-visibility analysis with product reviews and other user-generated content. The arrangement creates a path from identifying an answer-engine content gap to improving the information AI systems may encounter.

The harder issue is coordination, not the number of dashboards. As an AI agent proposes or performs more work, teams need to know who owns each decision, what evidence supports it and whether the change improved something beyond the visibility score.

What should buyers validate before adopting the platform?

• Separate exposure from business impact. Track mentions and recommendations as discovery signals, then assess lead quality and commercial results separately. More AI citations do not automatically mean more customers.
• Audit the source material. Product pages, reviews and external coverage can shape how AI systems describe a brand. Monitoring identifies gaps but does not correct the underlying information.
• Test brand context. Buyers should ask how accurately Context Manager uses approved claims, product details and tone of voice. Weak inputs can produce weak recommendations at scale.
• Require accountability. Ask about system access, human approval, measurement and rollback. The November announcement did not establish specific human approval controls, so marketers need to validate them directly.

Does the Singapore expansion guarantee results?

AI-mediated discovery reaches beyond organic-search specialists. Brand positioning, product data, public relations and paid media can all affect what information a buyer encounters before reaching a website. AI discovery therefore requires several teams to agree on what a brand should be known for and how to verify that the message reaches customers.

Singapore remains a regional service base, not a guarantee of commercial results. As more AI marketing platforms establish local operations, the stronger test will be whether marketers can connect answer visibility to accurate content, accountable workflows and measurable customer decisions.

The real test is not which vendor produces the most AI mentions, but which one can show why a mention matters and what the marketer should do next.