Declining MQLs? Discovered Labs vs Peec AI: Which AEO Agency for B2B SaaS?

Updated December 09, 2025

Your organic traffic looks healthy. Your blog ranks on page one for core keywords.

But your MQLs dropped 22% last quarter. Your CEO just asked a question you can't answer: "What happens when prospects research us in ChatGPT?"

Here's the uncomfortable truth: nearly half of U.S. B2B buyers now use AI for vendor research. They ask ChatGPT, Claude, or Perplexity to recommend solutions, and those AI models deliver synthesized answers with vendor shortlists.

If your brand isn't cited in those responses, you've become invisible to half your potential pipeline.

This guide compares two paths to solving the "Invisible Pipeline" problem: Discovered Labs (a specialized B2B SaaS AEO agency) and Peec AI (an AI search analytics platform). We'll examine methodology, technology, contract terms, and business fit so you can decide which approach matches your resources and growth stage.

At a glance: Discovered Labs vs. Peec AI

Discovered Labs and Peec AI both tackle AI search visibility, but each solves a fundamentally different problem for different types of buyers and organizational needs.

The contrast is stark.

Side-by-side comparison

The core difference: Full-service specialist vs. DIY analytics

Discovered Labs operates as a specialized Answer Engine Optimization agency that handles strategy, content production, technical optimization, and third-party validation building. The entire business model centers on B2B SaaS companies with complex products and long sales cycles.

Peec AI functions as an AI search analytics platform that tracks how your brand appears across ChatGPT, Perplexity, Gemini, and Claude. You get dashboards showing brand mentions, sentiment, and competitive benchmarks. However, you handle content strategy and optimization yourself.

The choice hinges on a simple question: Do you need a partner to execute AEO, or do you need visibility tools to inform your in-house team's work?

Methodology: How they engineer citations

Discovered Labs: The CITABLE Framework

Discovered Labs built the CITABLE Framework specifically to make B2B content citable by Large Language Models. The seven components target how AI models retrieve, verify, and synthesize information.

C - Clear entity & structure: In practice, every article opens with a "Bottom Line Up Front" (BLUF), a 2-3 sentence block identifying the subject entity and its primary function. This lets AI extract structured information immediately.

I - Intent architecture: Next, content answers the primary buyer question plus logical follow-up queries. For a B2B buying committee, addressing adjacent questions means a single article serves multiple stakeholders.

T - Third-party validation: Critically, AI models trust external corroboration more than owned content. Discovered Labs builds validation through strategic Reddit marketing, review site profiles, industry forum mentions, and authoritative citations.

A - Answer grounding: Content leads with direct answers and verifiable facts. This structure allows AI to extract and cite specific information accurately.

B - Block-structured for RAG: We break content into 200-400 word sections with descriptive headings to optimize for Retrieval-Augmented Generation. This structure dramatically improves citation rates compared to long-form essays.

L - Latest & consistent: To maintain relevance, regular timestamp updates signal freshness. Factual consistency across all sources prevents AI from skipping citations due to conflicting data.

E - Entity graph & schema: Explicit relationship definitions using schema markup help AI platforms understand context and authority.

In one case study, Discovered Labs reports that a B2B SaaS client grew from 550 to over 2,300 AI-referred trials in four weeks using this methodology, with a 600% increase in brand citations across platforms.

Peec AI: The analytics-first approach

Peec AI operates as a search console for AI platforms. The platform tracks several key metrics across major AI engines:

• Brand visibility (how often you appear)
• Sentiment analysis (positive, neutral, negative mentions)
• Position scoring (where you rank in responses)
• Source analysis (what content AI models cite)

The system works in three steps. First, it creates a bank of test queries. Next, it runs them across AI models. Finally, it tracks whether your brand appears in responses.

You receive metrics on mention frequency, sentiment, and competitive benchmarking showing how often rivals are cited instead.

Peec AI does not provide a content optimization framework comparable to CITABLE. The platform delivers data to inform your strategy. However, content creation, technical optimization, and third-party validation remain your responsibility.

Why B2B SaaS requires entity-based optimization

The average B2B SaaS sales cycle runs 90-180 days with 7-12 stakeholders. Each person researches different aspects: the CTO evaluates security, the CFO analyzes ROI, the end-user assesses usability.

When these stakeholders ask AI for recommendations, the models synthesize answers from multiple sources. Generic content optimized for broad search terms fails because it doesn't address the specific entity relationships and validation signals B2B buyers need.

Include the long tail of entities and relationships explicitly in your content to capture these high-intent AI queries.

Technology and reporting transparency

Tracking the AI visibility challenge

The fundamental problem with AI search is measurement. Traditional SEO gives you clear metrics: keyword rankings, click-through rates, conversion paths tracked in your analytics dashboard.

AI search operates as a black box. You're flying blind.

You don't know what queries buyers asked, which sources the AI cited, or how your brand was positioned. Research from Ahrefs found only 12% overlap between URLs cited in AI-generated answers and those ranking in Google's top 10 for the same query. You can rank #1 on Google and remain completely invisible in ChatGPT responses.

Discovered Labs' AI Visibility Audit and tracking

Discovered Labs built proprietary technology to audit brand presence across ChatGPT, Claude, Perplexity, Google AI Overviews, and Microsoft Copilot. The AI Visibility Audit process involves:

1. Query bank creation: Map 50-200 buyer-intent queries across awareness stages and persona roles
2. Multi-platform testing: Run queries through each AI system to capture actual responses
3. Citation analysis: Track whether your brand appears, positioning (1st, 2nd, 3rd mention), source URLs AI cites, and competitive share of voice percentage
4. Gap identification: Pinpoint specific topic clusters where competitors dominate (50%+ citation rate) while you remain absent

The deliverable is a baseline benchmark showing your current AI visibility, a competitive map, and a prioritized content roadmap. Ongoing monthly reporting tracks citation rate improvements, share of voice trends, and (critically) attribution to pipeline.

Discovered Labs also offers a free ROI calculator that models the pipeline value of improving your citation rate by 10%, 20%, or 30% based on your average deal size and sales cycle.

Peec AI's analytics dashboard

Peec AI's platform provides real-time tracking of brand visibility metrics across AI search engines. You can monitor position scoring, sentiment trends, and competitive benchmarking.

The platform's strength is breadth: it tracks multiple AI engines simultaneously and provides historical trend data. However, Peec AI's feature set focuses on visibility metrics rather than end-to-end attribution. You'll need to layer on additional analytics infrastructure to connect AI visibility improvements to website visits, form fills, or closed deals.

For teams with existing content and technical resources, Peec AI's data can inform optimization priorities.

Commercial terms and agility

The risk of long-term lock-ins

In our experience, traditional SEO agencies often require 6-12 month contracts. The rationale is that organic search takes time to compound.

But in the fast-moving AI landscape, long-term commitments create risk. If an agency can't show measurable citation improvements within 60-90 days, you're stuck paying for underperformance.

The month-to-month model shifts accountability. Agencies must earn your business every month by showing progress.

Discovered Labs' month-to-month performance model

Discovered Labs operates on rolling monthly contracts with no long-term commitment. The service includes:

• Minimum 20 AEO and SEO-optimized articles per month
• Complete AI visibility audit and ongoing tracking
• Technical optimization (schema, entity structure, site crawlability)
• Reddit marketing and third-party validation building
• Monthly performance reviews with citation metrics and pipeline attribution

You can scale services up or down based on results. The model is designed for companies between $10M-$50M ARR that need predictable costs and measurable outcomes.

For comparison, Peec AI offers monthly subscriptions starting at €89 (tracking 25 prompts) to €499+ (tracking 300+ prompts). Annual contracts require 30-day termination notice. The lower price reflects a different value proposition: you get data, not execution.

Content velocity: 20-66+ articles per month

Discovered Labs emphasizes high-volume, high-velocity content production. Their packages start at 20 articles per month. In their B2B SaaS case study, they produced 66 optimized articles in a single month to rapidly build topical authority.

This volume is significantly higher than typical SEO agency output. The rationale is that AI models prioritize recency and comprehensive coverage.

Daily content publishing keeps your brand "fresh" in the training data and retrieval systems.

For perspective, Demand Gen Report found that 91% of B2B marketers are increasing content output, with many aiming to produce 3-5x more than the previous year. Discovered Labs' model aligns with this shift toward volume without requiring you to build in-house capacity.

Verdict: Which partner fits your goals?

Choose Discovered Labs if you need specialized B2B execution

Discovered Labs is the right fit when:

• Complex product: Technical B2B SaaS, fintech platforms, healthcare technology, or professional services with long sales cycles and multiple stakeholders
• Lack in-house AEO resources: Your content team is stretched thin, and you need a partner to handle strategy, production, and optimization end-to-end
• Need pipeline attribution: You must connect AI visibility improvements to qualified leads and revenue to justify the investment to your CFO and board
• Want contract flexibility: Month-to-month terms let you scale based on results without being locked into underperforming relationships
• Speed matters: High-velocity content production (20-66+ articles per month) can rapidly build topical authority and competitive share of voice

Watch a full walkthrough of how Discovered Labs approaches B2B SaaS AEO strategy, from audit through execution.

Choose Peec AI if you have content resources and need tracking

Peec AI makes sense when:

• Strong content team: Your writers, strategists, and SEO specialists can handle optimization in-house once they understand where gaps exist
• Need visibility data, not execution: You want dashboards showing brand mentions, sentiment, and competitive positioning across AI platforms
• Budget constraints: €89-€499 per month for analytics is more accessible than full-service agency costs
• Serve broader markets: Peec AI works across industries and doesn't specialize in B2B SaaS, making it suitable if your audience includes consumers or simpler purchasing decisions

The platform provides valuable data. However, you'll need to translate those insights into content strategy, production, and technical optimization yourself.

Stop losing pipeline to invisible competitors

The shift from traditional search to AI-mediated research is not a future trend. It's happening now.

If your brand isn't cited when prospects ask ChatGPT, Claude, or Perplexity for vendor recommendations, you're invisible to half your potential pipeline. Your competitors who moved early on AEO are building category authority while you optimize for yesterday's search behavior.

The choice between Discovered Labs and Peec AI comes down to your resources and needs. If you're a B2B SaaS leader who needs specialized execution, transparent reporting, and flexible terms, Discovered Labs delivers a proven methodology with measurable results. If you have content resources and need visibility data to guide your in-house team, Peec AI provides valuable tracking at a lower price point.

Find out where you stand. Request a free AI Visibility Audit from Discovered Labs. You'll get a baseline benchmark showing how often your brand is cited across ChatGPT, Claude, Perplexity, and Google AI Overviews for buyer-intent queries in your category, plus a competitive gap analysis showing where rivals dominate while you remain absent.

Frequently asked questions

How long does it take to see citation improvements from AEO?
Initial citations typically appear within 2-4 weeks for high-intent queries. Measurable pipeline impact usually takes 60-90 days once you reach a 20-30%+ citation rate.

Can I use Peec AI and Discovered Labs together?
Technically yes, but it's often redundant. Discovered Labs includes proprietary AI visibility auditing and tracking in their service, so you'd be paying twice for similar data.

What if my SEO agency says they already do AEO?
Ask for evidence. Most traditional SEO agencies lack specialized AEO methodology. Request to see their framework for entity optimization, third-party validation building, and citation rate reporting. Ask to see a sample report showing citation rate over time and pipeline attribution, not just traffic increases.

What citation rate should I target?
Aim for 30-40% citation rate across buyer-intent queries in your category within 90 days. Top performers achieve 50%+ citation rates. The ROI calculator shows pipeline value of different citation rate improvements based on your deal size and sales cycle.

Key terms glossary

Answer Engine Optimization (AEO): The practice of structuring content so AI-powered platforms like ChatGPT, Claude, and Perplexity cite your brand when answering buyer questions. Our complete guide to AEO fundamentals covers the strategic foundations.

Citation Rate: The percentage of relevant buyer-intent queries where AI models mention your brand in responses. A 30% citation rate means your brand appears in 3 out of 10 test queries.

CITABLE Framework: Discovered Labs' proprietary seven-component methodology (Clear entity, Intent architecture, Third-party validation, Answer grounding, Block-structured for RAG, Latest & consistent, Entity graph & schema) for creating content optimized for LLM retrieval.

Share of Voice: Your brand's citation frequency relative to competitors for a defined set of buyer-intent queries. If you're cited 20 times and your top rival is cited 60 times across 100 test queries, your share of voice is 25%.

Invisible Pipeline: The phenomenon where B2B buyers use AI for vendor research and form opinions without visiting your website, leading to declining MQLs despite stable SEO performance. Use our AEO checklist to diagnose your risk.