90-Day Implementation Timeline: Discovered Labs vs. Growthx Optimization Roadmap

Updated January 20, 2026

When your CEO asks "What's our AI visibility strategy?" in next quarter's board meeting, you need more than a consultant's deck. You need a roadmap with dates, milestones, and proof that your investment is working.

Most marketing leaders hesitate to commit to Answer Engine Optimization because they fear paying for a 6-month black box with no visible progress. The gap between a generalist growth agency and a specialized AEO partner is not just methodology, it is the speed of feedback.

One approach produces audit reports and strategy decks. The other produces citations and qualified leads. This timeline breaks down exactly what happens in the first 90 days with Discovered Labs versus a traditional growth agency model (represented by firms like Growthx).

The velocity gap: Why traditional growth roadmaps fail in AI search

Traditional SEO agencies optimize for Google's crawl-based algorithm, which rewards technical perfection before scaling content. Traditional SEO typically requires 6-18 months of sustained effort before first-page rankings and ROI appear.

AI search engines operate differently. ChatGPT, Claude, Perplexity, and Google AI Overviews prioritize semantic query matching over keyword density, verifiable authority markers over marketing claims, and machine-readable structure over persuasive copy.

With 400+ million people using OpenAI products weekly and Gartner predicting 25% of organic traffic will shift to AI chatbots by 2026, businesses risk remaining undiscovered if they do not optimize for answer engines.

The methodology gap is fundamental. Traditional agencies follow a "Foundation First" approach with weeks 1-8 focused on audits, keyword research, and strategy documents. We follow a "Saturation First" model where daily content production begins on day 7 using our proprietary CITABLE framework.

We produce 20-60+ articles monthly, not the industry standard of 4-8. This velocity is strategic, not arbitrary. AI models need a critical mass of structured data to recognize your brand as an authoritative source.

The conversion advantage justifies this velocity. Ahrefs documented that AI search visitors convert at a 23x higher rate than traditional organic search visitors. When prospects ask ChatGPT "What's the best healthcare tech platform for mid-market hospitals?" and your brand appears in the answer with three specific reasons why you fit, that is pre-qualified demand.

Phase 1 (Days 1-30): Foundation and initial citation signals

Discovered Labs execution model

Day 1-7 focuses on establishing your baseline. Using proprietary technology, we conduct an AI visibility audit testing 75-100 buyer-intent queries across ChatGPT, Claude, Perplexity, Google AI Overviews, and Microsoft Copilot.

This audit reveals where competitors dominate and where you are invisible.

The audit delivers three tactical outputs. First, a competitive share of voice analysis showing which 3-5 competitors AI models cite most frequently and why. Second, a prioritized list of quick win queries where you are close to breaking through with targeted optimizations.

Third, a 90-day content roadmap mapping specific articles to specific citation opportunities.

Day 7-30 is where velocity creates advantage. Daily content production begins immediately using our CITABLE framework:

• C - Clear entity and structure (2-3 sentence direct answer)
• I - Intent architecture (answer main plus adjacent questions)
• T - Third-party validation (reviews, community, news citations)
• A - Answer grounding (verifiable facts with sources)
• B - Block-structured for RAG (200-400 word sections, tables, FAQs)
• L - Latest and consistent (timestamps, unified facts everywhere)
• E - Entity graph and schema (explicit relationships in copy)

We do not write traditional blog content. Each piece is engineered as a direct answer to a specific buyer question, structured in 200-400 word blocks that LLMs can extract cleanly, and grounded with verifiable third-party sources that AI models trust.

The average marketing team produces 2-3 pieces per week. We ship 5 pieces per week (20-22 per month) from day one.

By week 3-4, initial citation signals appear. You will not dominate share of voice yet, but your brand starts appearing in priority queries. This validates methodology and creates early proof for leadership.

Traditional agency model

Traditional agencies contact you within 3-5 business days of contract signing to begin discovery. The first 30 days focus on learning your business, industry landscape, competitive positioning, and existing online presence through strategy documents and audit reports.

By day 30, buyers asking ChatGPT for vendor recommendations this month are seeing only your competitors while foundational work is being laid for Google rankings.

Phase 2 (Days 31-60): Achieving competitive parity and citation growth

Discovered Labs momentum phase

We accelerate momentum in month 2. With 40-50 pieces of CITABLE-optimized content now live, AI models have sufficient entity data to recognize your brand as an authoritative source.

We intensify third-party validation during this phase. While owned content establishes what you do, external mentions establish that others trust you.

Our Reddit marketing service uses aged, high-karma accounts to shape narratives in relevant subreddits where your buyers congregate. We guide you through review campaign strategy on G2 and Capterra. We identify Wikipedia opportunities and industry forum discussions where your expertise adds value.

AI models weight external sources more heavily than owned content when making recommendations. A brand mentioned positively across Reddit, review sites, and industry forums sends trust signals that blog posts alone cannot create. According to Responsive's 2025 Buyer Intelligence report, 38% of B2B buyers use AI specifically for vetting and shortlisting vendors.

Weekly citation tracking reports show which content pieces drive the most citations and which topics need different approaches. Optimization becomes data-driven instead of guesswork.

First measurable increases in AI-referred traffic appear during this phase. Using tagged UTM parameters and traffic source analysis, you will see new sessions from AI platforms with higher conversion-to-MQL rates versus traditional organic search.

Traditional agency progress in month 2

Traditional agencies publish their first 4-8 blog posts in month 2 and begin on-page SEO optimizations. By day 60, Google is still crawling and indexing the new content. Rankings might improve from page 3 to page 2, but traffic remains negligible and AI citations remain minimal because the content was not structured for LLM retrieval.

Phase 3 (Days 61-90): Measurable pipeline impact and ROI

Discovered Labs results phase

Month 3 is where citation volume translates to pipeline value. With 60-90 pieces of content live and growing third-party validation, your brand now appears alongside top 2-3 competitors in AI recommendations for key use cases.

One of our clients went from 550 trials per month to over 3,500+ trials in approximately seven weeks by implementing our content velocity model and citation optimization framework.

AI-sourced traffic converts 23x higher because prospects arrive pre-qualified. They asked an AI assistant "What's the best solution for my specific use case?" and the AI recommended you with specific reasons why you fit.

By day 90, you can calculate early ROI with confidence. Example calculation for a typical client:

• Monthly investment: $18,000
• AI-referred MQLs: 120
• SQL conversion rate: 40% (vs 25% for organic)
• Qualified opportunities: 48
• Average deal size: $80,000
• New pipeline: $1,040,000
• ROI: 58x in projected pipeline

The board presentation writes itself. You show before (minimal AI citation rate, declining organic pipeline) versus after (significant citation improvement, 4x+ increase in AI-referred leads, 23x conversion advantage) with clear competitive positioning gains.

Traditional agency outcomes at day 90

Traditional SEO foundations are typically built within the first 90 days, but complete ROI and first-page rankings for competitive terms require 6-18 months. By day 90, you might see early ranking movements, increased indexed pages, and preliminary traffic upticks from baseline.

The work is not wasted. Google rankings matter for brand discovery and long-tail traffic. The problem is opportunity cost while AI-referred pipeline compounds for competitors.

Benchmarking success: What metrics matter at every stage

Marketing leaders need concrete metrics to evaluate progress and justify continued investment. Here is the scorecard we use to track client success at 30, 60, and 90-day intervals:

The key is comparative measurement. You should track not just your absolute citation rate, but your share of voice versus your top 3-5 competitors.

Weekly reporting is critical. Monthly reports hide problems for 30 days. We provide clients with dashboards showing citation trends, competitive positioning, AI-referred traffic sources, and MQL conversion rates updated weekly.

Frequently asked questions about AEO timelines

How long until initial AI citations appear, and what does full optimization require?
Initial citation signals typically appear within 3-4 weeks with our high-velocity approach (20+ pieces/month). However, this means early visibility, not dominance. Full competitive positioning requires 90 days because AI models need time to incorporate new entity data into their knowledge graphs. You can accelerate this by increasing content velocity (30+ pieces/month) or intensifying Reddit marketing and review campaigns.

Why is my current SEO agency slower at generating AI visibility?
AI engines prioritize entirely different ranking factors than traditional search: semantic query matching over keyword density, verifiable authority markers over marketing claims, and machine-readable structure over persuasive copy. With 400+ million people using OpenAI products weekly and Gartner predicting 25% of organic traffic will shift to AI chatbots by 2026, traditional agencies optimize for Google's slow, crawl-based algorithm. AEO requires feeding LLMs a large volume of fresh, structured data immediately.

What happens if we see minimal citations after 90 days?
Limited citations after 90 days with proper execution indicates one of three problems: insufficient content volume, poor CITABLE framework implementation (content not structured for LLM retrieval), or conflicting brand information across sources (AI models skip brands with inconsistent data). We diagnose the root cause and adjust strategy, but month-to-month terms mean you can walk away if progress stalls.

How do we attribute pipeline to AI visibility versus other marketing activities?
We implement tagged UTM parameters and traffic source tracking for all AI-referred visitors, integrate with Salesforce to track AI-influenced opportunities, and provide weekly reports isolating AI-sourced MQLs with clear conversion rate comparisons versus organic search baseline. Multi-touch attribution is complex, which is why we emphasize conversion rate advantage (23x higher for AI traffic per Ahrefs research) in addition to absolute volume.

Key terminology for AI search optimization

Answer Engine Optimization (AEO): The practice of optimizing content to appear in direct answers provided by AI-powered search tools like ChatGPT, Claude, Perplexity, and Google AI Overviews, rather than traditional keyword-based search rankings.

CITABLE Framework: Discovered Labs' proprietary 7-part methodology for structuring content (Clear entity structure, Intent architecture, Third-party validation, Answer grounding, Block-structured for RAG, Latest and consistent, Entity graph and schema) specifically for LLM retrieval.

Citation Rate: The percentage of times your brand is mentioned by AI models when responding to specific buyer-intent queries within your category. Strong citation rates mean your brand appears consistently in relevant AI answers.

Share of Voice (AI context): Your brand's percentage of total AI citations compared to competitors when testing a standardized set of buyer-intent queries. This metric shows competitive positioning in AI-mediated buyer research.

Information Density: The depth of verifiable facts, structured data, and entity relationships per content unit. AI models prefer high information density (200-400 word blocks with specific data points) over long-form narrative content optimized for human persuasion.

The difference between winning and losing in AI search is not strategy complexity. It is execution velocity. While traditional agencies spend 90 days building foundations, buyers are asking AI for recommendations today. We help you show up in those answers starting week 3, not month 6.

We can show you exactly where you are invisible versus where your competitors dominate. Request an AI visibility audit to establish your baseline and get a custom 90-day roadmap. Or book a strategy call to discuss whether our month-to-month approach fits your timeline and budget. We earn your business every 30 days based on measurable results.