Discovered Labs vs First Page Sage: Real Results Compared

Updated December 19, 2025

87% of B2B buyers now use AI chatbots to research vendors before they ever contact sales. When they ask ChatGPT "What's the best solution for X?", the AI generates a shortlist of three to five companies with detailed explanations of why each fits their needs.

If your brand isn't in that list, you've lost the deal before your sales team knows the opportunity exists.

This is the AI visibility gap, and traditional SEO doesn't solve it. Google rankings don't guarantee citations in AI-generated answers. The methodology that worked for Google's algorithm doesn't automatically translate to LLM retrieval systems.

If you're evaluating agencies to solve this problem, you've likely encountered both traditional SEO firms and specialized AEO providers. First Page Sage represents the former, Discovered Labs represents the latter. This guide compares their methodologies, deliverables, contract terms, and results so you can choose the partner that fits your revenue goals.

The core difference: SEO heritage vs. AI-native methodology

First Page Sage built its reputation on traditional search engine optimization. Founded in 2009, the agency focuses on thought leadership content that ranks on Google's first page. Their approach centers on high-quality editorial, keyword mapping, and establishing topical authority through comprehensive guides and white papers.

Discovered Labs takes a fundamentally different approach. We engineer content specifically for AI retrieval using our CITABLE framework, a 7-part methodology built for how LLMs actually retrieve and cite information. Where traditional SEO optimizes for ranking algorithms, AEO optimizes for being quoted directly in AI-generated answers.

The distinction matters because optimization targets have changed. Google's algorithm evaluates page authority, backlinks, and keyword relevance to determine rankings. LLMs evaluate entity clarity, answer directness, third-party validation, and structural retrievability to determine citations. These are different technical challenges requiring different solutions.

Key terminology:

Answer Engine Optimization (AEO): The practice of optimizing content so AI platforms can directly provide your brand as the answer to user queries, whether through ChatGPT, Claude, Perplexity, or Google AI Overviews.

Generative Engine Optimization (GEO): The practice of adapting content for visibility in results produced by large language models, focusing on how AI systems retrieve, summarize, and present information.

Large Language Model (LLM): AI systems trained on vast text datasets that generate human-like responses and answer questions, including ChatGPT, Claude, Gemini, and Perplexity.

Citation Rate: The frequency with which your brand is mentioned or cited in AI-generated answers across relevant buyer-intent queries.

Methodology comparison: Hub & Spoke vs. The CITABLE Framework

First Page Sage describes their approach as understanding your brand, audience, and goals to produce content "like it was written by your own experts." They use a hub-and-spoke model, selecting keywords, organizing them into content hubs based on your most profitable products, then creating comprehensive thought leadership for each topic.

This methodology produces strong results for traditional search. Their case study with Cadence Design Systems shows a 934% increase in total keyword rankings and significant improvements in cost per conversion. They emphasize quality over volume, typically producing thoughtfully researched pieces targeting high-commercial-value keywords.

Discovered Labs uses the CITABLE framework, which stands for:

C - Clear entity & structure: Every piece opens with a 40-60 word direct answer establishing entity clarity.

I - Intent architecture: Content answers the main query plus adjacent questions buyers ask in sequence.

T - Third-party validation: We incorporate reviews, community mentions, and external citations that AI systems trust.

A - Answer grounding: Facts are verifiable and sourced, making content quotable without losing context.

B - Block-structured for RAG: Content uses 200-400 word sections, tables, ordered lists, and FAQ schema optimized for retrieval-augmented generation.

L - Latest & consistent: We include timestamps and ensure unified facts across all platforms AI systems check.

E - Entity graph & schema: We implement Organization, Product, and FAQ schemas with explicit relationship markup.

We ship daily for clients and continuously test content formats directly against AI systems to measure what actually gets cited. In one documented case study, we shipped 66 optimized articles in one month, achieving a 600% citation uplift across ChatGPT, Claude, and Perplexity within four weeks.

The technical difference is significant. Traditional SEO content prioritizes keyword density and backlinks. AEO content prioritizes quotability and entity structure. AI models need facts and structure, not just keywords, to confidently cite your content.

Deliverables and cadence: Monthly blog posts vs. daily answer engine optimization

Content production velocity matters more in AEO than traditional SEO. Here's why.

When you optimize for Google rankings, you target specific keyword positions. Ranking #1 for "project management software" delivers traffic from that one query. You can achieve strong results with 2-4 high-quality posts per week, which is the industry sweet spot for balancing quality and consistency.

When you optimize for AI citations, you're optimizing for passage retrieval across thousands of long-tail queries. A prospect asking ChatGPT for recommendations provides extensive context in their prompt - current tech stack, team size, budget constraints, specific pain points. Your content needs to explicitly address these entity combinations to get retrieved and cited.

This requires higher content volume. According to our analysis of successful AEO programs, achieving meaningful share of voice in AI answers requires daily content production to build topical authority across the full question spectrum your buyers ask.

Our standard packages start at 20-60+ articles monthly, structured as direct answers to specific buyer queries. These aren't generic blog posts but researched, CITABLE-framework pieces we structure as quotable facts blocks. One of our clients saw AI-referred trials increase from 550 to 2,300+ in four weeks after we shipped 66 optimized articles targeting their category.

Traditional agencies typically emphasize quality and depth. Their content is comprehensive, well-researched, and written at an expert level. This approach works well for establishing thought leadership and ranking for high-value keywords where buyers show clear purchase intent.

The trade-off is velocity. Premium content production takes time. Most SEO agencies require 6-12 month contracts because building domain authority and accumulating ranking signals requires sustained effort. For traditional SEO targeting a defined keyword set, this timeline makes sense.

For AEO targeting passage retrieval across thousands of variations, you need a different cadence. AI models process queries with extensive context, and your content surface area needs to match that query diversity.

We also provide AI Visibility Audits that track where you appear across platforms. Traditional SEO audits measure keyword rankings and technical health. AI visibility audits measure citation frequency, share of voice versus competitors, and which content pieces earn mentions in generated answers.

Contract terms and flexibility: 12-month lock-ins vs. performance-based sprints

Contract flexibility represents a significant practical difference.

Most traditional SEO agencies require long-term commitments because SEO takes time to demonstrate results. Traditional search optimization typically shows meaningful ROI at 6-12 months, with best returns appearing after 12-18 months. Annual contracts make sense when you're building domain authority and accumulating ranking signals over time.

Discovered Labs operates on 30-day rolling agreements with no long-term commitment. You can scale up, down, or pause anytime based on results.

We structured our contracts this way because the AEO category is nascent and methodologies continue to evolve. Month-to-month contracts reduce your risk when testing AEO for the first time. If after 8 weeks you're not seeing citation improvements or AI-referred traffic, you're not trapped in a 12-month obligation.

This flexibility matters when you need to prove value quickly to internal stakeholders. B2B buyers spend 83% of their time researching independently, away from sales reps. If your brand isn't visible during that AI-assisted research phase, you've already lost the deal before your sales team knows the opportunity exists.

Our approach delivers initial citation movement in 2-4 weeks as AI models incorporate new content, with meaningful share-of-voice gains in 6-8 weeks. You see progress fast enough to justify continued investment on a rolling monthly basis.

Traditional agencies delivering thought leadership SEO may resist short-term contracts because their methodology requires sustained effort before rankings materialize. This isn't a criticism of their model, it's an acknowledgment that traditional SEO and AEO operate on different timescales.

Head-to-head comparison: A feature-by-feature breakdown

This table illustrates the fundamental strategic difference. If your goal is page 1 Google rankings for defined keywords, traditional SEO agencies deliver proven results. If your goal is getting cited when prospects ask AI for recommendations, you need technical AEO optimization.

Verdict: When to choose First Page Sage vs. Discovered Labs

Choose First Page Sage or similar traditional SEO agencies if you want comprehensive thought leadership content targeting high-commercial-value keywords, you have a stable market where buyer behavior changes slowly, and you're willing to commit 12+ months to see meaningful ranking improvements materialize.

Their expertise in editorial quality and strategic keyword targeting has helped companies like Cadence achieve 934% increases in keyword rankings. For traditional search visibility, they represent a proven approach.

Choose Discovered Labs if your prospects use AI for vendor research (87% of B2B buyers do, as we noted earlier), you need to close the gap between Google rankings and AI invisibility, you want flexible month-to-month contracts that reduce risk, and you need rapid citation improvements to prove value to internal stakeholders.

We engineered our methodology specifically for LLM retrieval. Our clients typically see AI-referred leads contribute 15-30% of marketing-sourced pipeline within 6 months, with conversion rates significantly higher than traditional organic search because prospects arrive pre-qualified by the AI's recommendation.

The reality is you may need both. Traditional SEO still drives significant traffic for most B2B companies. But buyer behavior is changing fast, with more buyers using AI assistants for research every quarter. The question isn't "Should I abandon SEO?" It's "How do I capture the growing percentage of buyers who research with AI instead of Google?"

How Discovered Labs helps

If you're evaluating whether specialized AEO makes sense for your business, start with an AI Visibility Audit. We'll show you exactly where your brand and top 3 competitors appear (or don't) when prospects ask AI for vendor recommendations in your category.

The audit includes:

• Citation tracking across ChatGPT, Claude, Perplexity, and Google AI Overviews
• Share of voice analysis versus competitors
• Content gap identification showing which buyer queries you're invisible for
• Predictive performance modeling showing forecasted AI visibility gains over 3-6 months based on your content plan
• Strategic recommendations for closing visibility gaps

Book a strategy call and we'll walk you through how the CITABLE framework works, share examples of content that gets cited versus ignored, and be honest about whether we're a good fit for your situation.

Frequently asked questions

Is AEO different from SEO?

Yes. AEO optimizes for being quoted in AI-generated answers, while SEO optimizes for ranking in search result lists. The technical requirements differ significantly in entity structure, answer directness, and third-party validation.

Can I do both SEO and AEO simultaneously?

Absolutely. The CITABLE framework produces content that performs well in both traditional search and AI citations. Our clients typically see improvements in both Google rankings and AI visibility simultaneously because structured, quotable content benefits both algorithms.

How long does it take to see results from AEO?

Initial citations typically appear within 2-4 weeks as AI models incorporate new content. Meaningful share-of-voice gains usually occur within 6-8 weeks, with compounding effects over 3-6 months as your entity authority builds.

What if I already have an SEO agency on retainer?

Many of our clients work with traditional SEO agencies for baseline optimization and add Discovered Labs specifically for AI visibility. The approaches complement rather than compete, similar to having separate paid search and content marketing partners.

How do I measure ROI from AI citations?

We help clients track AI-referred traffic in GA4 using custom channel groups and regex patterns. This lets you measure sessions, conversions, and pipeline contribution specifically from AI platforms versus traditional organic search.

Key terminology

Share of Voice: The percentage of AI citations your brand receives compared to competitors across relevant buyer-intent queries. A 40% share of voice means you're cited in 4 out of 10 AI answers where your category is discussed.

Entity Optimization: Structuring content so AI systems recognize and understand your brand, products, and expertise as distinct entities within knowledge graphs. This includes schema markup and clear relationship definitions.

AI-Referred Leads: Traffic and conversions originating from AI search platforms rather than traditional search engines. Research shows these leads convert at significantly higher rates than traditional organic search visitors because they arrive pre-qualified by the AI's recommendation.

Passage Retrieval: The process LLMs use to extract specific text segments from content to construct answers. Optimizing for passage retrieval requires block-structured content with clear entity relationships rather than traditional long-form narrative.