SAGE in Action: How a B2B Professional Services Firm Achieved Search Dominance in 6 Months
A detailed case study in integrated SEO, AEO, and GEO — with real metrics
Category: Case Study | SAGE Results | Read time: 11 min read
The Problem: Invisible Despite Investment
A regional professional services firm — providing compliance, risk advisory, and governance consulting to mid-market companies across Southeast Asia — had been investing in digital marketing for three years when they engaged Brandcore. They had a well-designed website, a consistent content programme, and an agency relationship that had delivered modest but respectable Google rankings for their core service keywords.
On paper, their digital presence looked functional. In practice, it was not working.
Qualified inbound leads had plateaued for eighteen months. Their sales team was generating most new business through referrals and direct outreach. When asked directly, the firm's leadership could not confidently say whether a prospective client searching for their services online would encounter their brand in any meaningful way.
The diagnostic phase of the SAGE engagement confirmed their suspicion. The firm ranked on page one for several branded and generic keywords. But they were entirely absent from featured snippets, Google AI Overviews, and AI assistant recommendations for the most commercially significant queries in their category.
KEY INSIGHT
When the engagement team asked ChatGPT 'what are the best compliance advisory firms in Southeast Asia,' the client's brand was not mentioned. Three direct competitors were. One of those competitors had been founded three years after the client and had approximately one-third of the client's revenue. Their AI visibility had no relationship to their real-world standing — which meant that AI search was actively distorting the competitive landscape in favour of a smaller, newer competitor.
The Diagnosis: Three Structural Gaps
The SAGE audit identified three structural gaps that were collectively responsible for the firm's AI search invisibility.
Gap 1: Content Written for Rankings, Not Answers
The firm's existing content was structured to perform in traditional search: articles with keyword-rich headings, adequate word counts, and internal links. But none of the content was written to answer specific buyer questions directly. The articles explored topics at length without ever synthesising a clear, citable conclusion. An AI scanning the site for an answer to 'how should a CFO approach regulatory compliance risk' would find extensive discussion of the topic but no extractable, structured answer.
Gap 2: No Structured Data or Schema Implementation
The firm's website had no schema markup of any kind. There was no Organisation schema establishing the firm as a clearly identifiable entity, no Service schema defining its offerings, and no FAQPage schema on any of its content pages. For AI systems that rely on structured data to accurately interpret and cite content, the website was effectively presenting itself in an unlabelled box.
Gap 3: Thin Entity Signals
The firm's name appeared consistently on its own website and LinkedIn profile, but its presence across third-party sources was sparse. There were limited directory listings, no published case studies with specific metrics, and minimal media mentions. Without these external entity signals, AI platforms had little basis on which to establish the firm as a recognised authority in its category.
The SAGE Implementation: What Was Done
Phase 1 (Weeks 1–4): Technical and Entity Foundation
The first phase addressed the structural and technical gaps before any content investment was made. Organisation, Service, and FAQPage schema were implemented across the site. The robots.txt file was reviewed and updated to ensure AI crawlers were permitted access to all relevant pages. The firm was listed consistently across twelve relevant third-party directories. A detailed llms.txt file was created and deployed at the domain root, providing AI systems with a clear briefing on the firm's expertise, services, and key differentiators.
Phase 2 (Weeks 5–10): Content Architecture Rebuild
The firm's top fifteen service and thought leadership pages were restructured using an answer-first format. Each page was rewritten to open with a direct, specific response to the most commercially important question that page was designed to address. FAQ sections were added to all service pages, drawing on questions the sales team had identified as the most common in buyer conversations. Each FAQ answer was structured to be extractable — beginning with the key point rather than building to it.
A pillar content programme was initiated across three topic clusters directly aligned with the firm's core service areas: regulatory compliance frameworks, governance for growth-stage companies, and risk management in cross-border operations. Two long-form articles were published per month, each containing specific, attributed data and structured for both reader comprehension and AI citation.
Phase 3 (Weeks 11–24): Authority Building and External Citation
The third phase focused on building the external authority signals that AI systems use to validate a brand's standing in its category. This included a targeted programme of contributed articles to three relevant regional publications, participation in two industry roundtables that generated media coverage, and the development of three case studies with client permission — each written with specific percentage improvements, timeline data, and named client context.
The Results: Six-Month Performance
The following results were measured at the six-month mark relative to the pre-engagement baseline.
Search Visibility
Featured snippet appearances for target queries increased from 2 to 19 — a 850% increase. The firm appeared in Google AI Overviews for 11 of its 25 target queries, compared to zero at the start of the engagement. Organic traffic to service pages increased by 63% over the period.
AI Search Citation
At the six-month mark, the firm appeared in ChatGPT's responses to four of the five category queries tested at engagement start, including the compliance advisory recommendation that had originally showed three competitors. Perplexity cited the firm in responses to six category queries. Google Gemini included the firm in AI Overview content for three of its core service areas.
Commercial Impact
Qualified inbound leads increased by 48% compared to the equivalent prior period. The sales team reported that prospects arriving via organic search were more informed, more specifically aware of the firm's differentiated approach, and more likely to be evaluating the firm as a primary rather than fallback option. Average deal cycle length decreased by 22% — a result the sales director attributed directly to buyers arriving having already encountered the firm's thought leadership content.
Cost Per Qualified Lead
Cost per qualified inbound lead decreased by 31% over the period, reflecting the combination of increased organic traffic and improved lead quality from better pre-educated prospects.
KEY INSIGHT
Perhaps the most significant result was not a metric but an observation. At the end of the six-month engagement, the firm's leadership team ran the original diagnostic test: they asked ChatGPT for a recommendation in their category. This time, their firm was named first. Their smaller competitor, who had led the AI results at the start of the engagement, was no longer mentioned.
Key Lessons from This Engagement
Several principles from this engagement are broadly applicable to B2B professional services firms considering a similar approach.
Technical implementation precedes content investment: Schema markup, crawlability, and entity establishment are the foundations. Content improvements built on a weak technical foundation deliver a fraction of their potential impact.
Answer-first content outperforms topic-coverage content: The restructured pages with direct, specific answers consistently outperformed the original topic-exploration format in both rankings and AI citation frequency.
External validation matters to AI systems: The published case studies and third-party media appearances had a disproportionate impact on AI citation — significantly more than equivalent internal content. AI systems weight independent validation heavily.
Results compound: The improvements at six months were already accelerating. Authority builds on authority. Early investments in structured content and entity signals delivered returns that grew larger, not smaller, as the engagement progressed.
QUICK WINS: WHAT YOU CAN DO THIS WEEK
- Ask yourself the diagnostic question: if a buyer asked ChatGPT for a recommendation in your category today, would your brand appear? If you don’t know the answer, test it immediately.
- Identify your three most commercially important service areas and audit whether each has a dedicated page that answers the primary buyer question directly in the first paragraph.
- Review your case studies. If they lack specific metrics, percentage improvements, and timeline data, they are unlikely to be selected as AI citation sources.
- Check whether your brand appears consistently and completely in the top relevant industry directories for your market. Inconsistent name, address, or service descriptions weaken entity signals.
- Consider a targeted content contribution to one or two credible industry publications. External citation from authoritative third-party sources is one of the highest-impact authority signals available.
READY TO TAKE ACTION?
The results in this case study were achieved through a structured, evidence-based process — not guesswork or shortcuts. If your business is ready to take the same approach to your search presence, a SAGE Strategy Session is the starting point. Book yours at brandcore.sg.