Service: SEO, Generative Engine Optimization (GEO) & AI Search Visibility Industry: B2B SaaS — Public-Sector Grant Management Technology Duration: Not disclosed in the source material — the engagement is described as ongoing rather than fixed-term. Engagement: Ongoing SEO and GEO retainer, described in the source as extending into paid media, email marketing, geofencing, and website maintenance (specific scope of those adjacent workstreams not detailed).

6 AI-Assisted Leads Within 6 Months as AI Brand Appearances Increased 53%

Public-Sector Grant Management SaaS Company (client identity anonymized)

6 AI-Assisted Leads Within 6 Months
+53% Increase in Total AI Brand Appearances
+30% Increase in Branded Mentions Across Unique AI Queries
30+ Industry-Relevant Links Built

The Background

The client is a B2B SaaS company providing grant management technology for public-sector organizations. Its platform supports the full grant-management lifecycle — opportunity publishing, application workflows, award administration, reporting, monitoring, and closeout.

The product serves a research-heavy B2B buying journey in which prospective customers evaluate features, use cases, vendors, and alternatives well before a sales conversation begins, which made search visibility important throughout the buyer’s research process, not just at initial discovery.

Team SizeNot disclosed in the source material.
Volume30+ industry-relevant links built; content expanded across capability, comparison, audience, and long-form guide pages.
EngagementOngoing SEO and GEO retainer, described in the source as extending into paid media, email marketing, geofencing, and website maintenance (specific scope of those adjacent workstreams not detailed).
Platform AccessNot disclosed in the source material.

The Challenge

The company already had an established SEO presence, but AI Overviews and zero-click search experiences were changing how buyers discovered and evaluated software. Traditional search visibility no longer represented the entire discovery journey.

Several forces were converging at once:

  • Organic clicks were under pressure — AI Overviews and zero-click experiences were increasingly answering user queries without a click to a conventional organic result.
  • Traditional SEO did not fully address AI discovery — ranking a webpage was no longer the only objective; the brand also needed to be represented when buyers asked questions through generative AI systems.
  • Brand visibility in AI search was limited — the company needed stronger representation across emerging AI and zero-click discovery environments.
  • Existing content needed to adapt — content written for traditional SEO needed to be reassessed against the questions and answers actually appearing in AI-driven search.
  • Search visibility had to remain connected to commercial opportunity — the goal was never simply to generate AI mentions, but to build a real progression from AI discovery to brand recognition to website engagement to lead opportunity.

The source specifically frames the engagement as a response to declining organic clicks caused by AI Overviews and zero-click search.

Our Approach & Technical Decisions

The Strategy

The strategic principle: build the authority, content relevance, and technical foundation needed to remain discoverable as buyers move from traditional search results toward AI-generated answers. The program did not replace SEO with GEO — it extended SEO into a broader answer ecosystem.

Phase 1 — Build Authority Around the Brand

Decision: Strengthen topical authority beyond the company’s own website rather than optimize on-page factors alone.

Action: More than 30 industry-relevant links were built around themes tied to grant management, business software, and public-sector technology, as an ongoing link-acquisition workstream.

Why: The objective was to strengthen the external authority surrounding the company’s subject matter — not simply accumulate backlink volume — creating a stronger foundation for both traditional organic search and the broader AI-search environment.

Phase 2 — Rebuild Content Around AI-Driven Questions

Decision: Reassess existing content against how AI systems were actually answering buyer questions, rather than assume traditional SEO content was still sufficient.

Action: The team ran content-to-AI mapping (matching existing pages against AI answers to find gaps) and search-intent audits, then built expert content around AI-driven research questions, dedicated capability pages, long-form/guide content for research-stage buyers, competitor-comparison content, and refreshed “Who We Serve” audience pages.

Why: These activities were designed to make the website useful not only to conventional search engines but within an AI-assisted research environment — addressing vendor evaluation, competitor-branded research, and bottom-of-funnel relevance at once.

The Execution Challenge: Traditional SEO metrics could answer “are our pages ranking?” but not “is our brand appearing when the buyer asks an AI system the question?” A brand could lose website clicks while simultaneously becoming more visible inside generated answers — so the measurement framework had to expand to organic search visibility, AI brand appearances, branded AI mentions, and AI-assisted lead activity together.

The Strategic Shift

Before: Search visibility was measured primarily through organic rankings and website clicks.

After: The strategy expanded to include organic search, AI-generated answers, brand mentions, topical authority, commercial content, and buyer research queries — extending SEO rather than replacing it.

Phase 3 — Technical SEO

Decision: Keep technical SEO as a core, ongoing part of the program rather than a one-time cleanup, since it underpins both traditional search and AI discovery.

Action: The team restructured internal links around related themes (thematic internal linking), improved conversion-focused page elements (tables of contents, CTA placement, more conversion-oriented structures), personalized the homepage by industry, optimized title tags at scale for query alignment, and prepared LLMs.txt files to manage AI crawler access and attribution.

Why: This strengthened the foundation for both traditional search rankings and AI discovery, and connected page-level improvements directly to conversion paths rather than treating technical SEO as visibility-only work.

Phase 4 — Measure AI Search Presence

Decision: Track AI visibility through a defined, relevant prompt set rather than rely on anecdotal AI mentions.

Action: Two core visibility measures were tracked — total brand appearances across relevant AI chatbot queries, and branded mentions across unique AI queries.

Why: This created a practical, ongoing way to monitor the company’s presence within generative search rather than relying exclusively on traditional organic rankings.

The Numeric Story

Metric Reported Result
AI-Assisted Leads 6 within 6 months
Total AI Brand Appearances +53%
Branded Mentions Across Unique AI Queries +30%
Industry-Relevant Links Built 30+

Note: these are the percentage and count figures reported in the source. No absolute AI appearance counts, total prompt volume, or baseline figures were provided, so none are presented here.

Measurement & Attribution

Reported performance is measured through four categories: AI discovery (total brand appearances in relevant AI chatbot queries), branded AI visibility (branded mentions across unique AI queries), commercial activity (6 leads within six months where AI channels assisted organic), and authority (30+ industry-relevant links built).

The source does not provide: absolute AI appearance counts, total prompt count, the exact analytics platform used, a detailed multi-touch attribution model, revenue attributed to AI, or revenue influenced by the six leads. None of these figures are invented or estimated here.

Competitive Search Context

The strategy included competitor-comparison content and content addressing competitive evaluation searches. However, the supplied source does not provide verified competitor AI visibility, share-of-voice, traffic, ranking, or lead figures, so no competitor performance data is presented as fact. The competitive opportunity was instead addressed through the content strategy itself — competitor-comparison content, competitor-branded research coverage, research-stage content, capability pages, and bottom-of-funnel audience content.

Ongoing Engagement

The source describes SEO and Generative Engine Optimization as ongoing strategies, with additional support across paid media, email marketing, geofencing, and website maintenance. No retainer value or specific ongoing contract terms are stated here, since none are provided in the source.

The Strategic Lesson

AI search should be treated as an extension of the buyer journey, not a separate content experiment. The most important shift was moving from a narrow question — “how do we rank?” — to a broader one: “how do we remain discoverable wherever our buyers are researching?” That required building authority, answering real questions, clarifying product capabilities, strengthening commercial content, increasing AI visibility, and measuring AI-assisted lead activity as one connected system rather than isolated tactics.

The Takeaway

For B2B SaaS companies, the search journey increasingly extends beyond the conventional results page — buyers discover and evaluate vendors through organic search, AI Overviews, AI chatbots, research questions, comparison searches, and brand mentions. A resilient search strategy needs to make the business discoverable, understandable, credible, and relevant — and ultimately considered. The objective isn’t to appear more often; it’s to appear when the buyer is asking the questions that influence a purchasing decision.

Implementation Timeline

PhaseDurationDeliverables
Phase 1 — Build Authority Around the BrandNot disclosed in source30+ industry-relevant links built around grant management, business software, and public-sector technology themes
Phase 2 — Rebuild Content Around AI-Driven QuestionsNot disclosed in sourceContent-to-AI mapping, search-intent audits, expert content, capability pages, long-form guides, comparison content, refreshed audience pages
Phase 3 — Technical SEONot disclosed in sourceThematic internal linking, conversion-focused page improvements, homepage personalization by industry, title-tag optimization at scale, LLMs.txt AI crawler preparation
Phase 4 — Measure AI Search PresenceOngoingTracking of total brand appearances and branded mentions across unique AI queries as the two core visibility measures

Technology Stack

TechnologyPurposeWhy This Choice
Content-to-AI MappingMatch existing pages against AI-generated answers to find content gapsImprove relevance and representation within AI-search results
Search-Intent AuditsRe-evaluate pages against the intent behind relevant searchesRealign existing content with how buyers actually search
Industry-Relevant Link BuildingBuild 30+ links around grant management, business software, and public-sector technology themesStrengthen external authority supporting SEO and AI visibility
Capability & Comparison PagesRepresent product capabilities clearly and address vendor evaluationSupport commercial discovery and capture competitor-oriented research
Long-Form Guides & Audience PagesCapture research-stage demand and strengthen bottom-of-funnel relevanceExpand informational coverage across the full buyer journey
Thematic Internal LinkingStructure internal links around related themesStrengthen topical architecture and connections between important pages
Conversion EnhancementsAdd tables of contents, improve CTA placement, personalize the homepage by industryConnect discovery to measurable lead activity
Title-Tag OptimizationUpdate title tags at scale for tighter query alignmentImprove organic relevance across the site
LLMs.txt / AI Crawler PreparationManage AI crawler access and attributionPrepare the technical foundation for AI search discovery

Measurable Results

  • 6 leads recorded within six months where AI channels assisted organic — the strongest commercial result in the source
  • 53% increase in total brand appearances across relevant AI chatbot queries
  • 30% increase in branded mentions across unique AI queries
  • 30+ industry-relevant links built around grant management, business software, and public-sector technology themes
  • Content expanded across capability pages, long-form guides, comparison content, and audience pages to support both traditional SEO and AI-driven discovery
  • Technical SEO adapted for AI crawler access via LLMs.txt preparation, thematic internal linking, and title-tag optimization at scale

Post-Launch & Ongoing Engagement

The source describes this as an ongoing SEO and Generative Engine Optimization engagement, with additional support across paid media, email marketing, geofencing, and website maintenance. No specific retainer value or contract term is stated here, since none is disclosed in the source material.