Updated January 19, 2026
TL;DR: SE Ranking tracks your visibility in traditional search and AI results but does not write the content that gets you cited. Discovered Labs executes the daily content production using the CITABLE framework (20+ articles/month) and builds the third-party validation AI systems trust. The winning strategy is hybrid: use SE Ranking to monitor gaps and progress, deploy Discovered Labs to fill gaps with content engineered for ChatGPT, Claude, and Perplexity.
Nearly 50% of B2B buyers now use GenAI for vendor research, which means optimizing only for Google leaves half your pipeline invisible.
Your competitor ranks fifth on Google but wins the deal.
Why? When your prospect asked ChatGPT "What's the best healthcare analytics platform for mid-market hospitals?" the AI recommended them first with three specific reasons why they fit. Your company never appeared.
This is the new reality for B2B marketing leaders. Traditional SEO tools like SE Ranking show you where you rank and can track your presence in AI results. But tracking the problem is different from solving it. SE Ranking tells you what's happening. Discovered Labs executes the strategy to change it.
This guide shows you how to combine both into a hybrid search strategy that covers traditional rankings and AI citations. You'll learn when to use SE Ranking's monitoring capabilities, when you need Discovered Labs' managed execution, and how to integrate both for measurable pipeline growth.
Use SE Ranking when you need to monitor keyword rankings, track traditional backlinks, and see baseline AI visibility across Google AI Overviews. It costs $52-$207/month and works if you have internal content team capacity.
Use Discovered Labs when you need to actually get cited by ChatGPT, Claude, and Perplexity at scale. We produce 20+ articles per month using the CITABLE framework, build third-party validation on Reddit and G2, and report on citation rates and AI-referred pipeline. Starts at €5,495/month, month-to-month terms.
The winning approach: Use both. SE Ranking identifies your gaps. We fill them with content engineered for LLM citations.
The new search reality: Traditional SEO vs. answer engine optimization
Traditional search engine optimization focuses on helping businesses rank higher on search engine results pages to drive organic website traffic. The goal is page-one visibility, measured through rankings, traffic volume, and click-through rates.
Answer Engine Optimization improves your brand's visibility in AI-powered platforms like ChatGPT, Claude, Perplexity, and Google AI Overviews. Instead of ranking pages, you optimize to get cited when AI systems answer questions. You succeed when AI platforms cite your brand in their recommendations with specific reasons why you solve the buyer's problem.
Gartner predicts traditional search engine volume will drop 25% by 2026 as AI chatbots take market share. Meanwhile, 48% of U.S. B2B buyers use GenAI for vendor discovery rather than starting with traditional search.
When prospects use Google, they're looking for links to click. When they use ChatGPT or Perplexity, they're looking for direct answers and recommendations. AI platforms synthesize information from multiple sources, then cite the brands that best match the buyer's specific context including their current tech stack, budget constraints, and use case requirements.
Google's algorithm prioritizes backlinks, domain authority, and keyword optimization. AI models prioritize clarity, verifiability, and entity structure. Your blog post optimized for "best project management software" might rank well in Google but remain invisible to ChatGPT, even with strong backlinks. The content is structured for keyword density rather than direct answers, uses marketing language instead of verifiable claims, and lacks the entity relationships that LLMs need to understand what you do.
| Traditional SEO Goal |
AEO Goal |
| Rank page one for target keywords |
Get cited when AI answers buyer questions |
| Drive clicks to website |
Build trust so AI recommends you |
| Optimize for backlinks and domain authority |
Optimize for clarity, verifiability, entity structure |
| Measure rankings and traffic |
Measure citation rate and share of voice |
SE Ranking is a SaaS platform that tracks your visibility across traditional search and AI-generated results. Discovered Labs is a managed service that produces the content and builds the authority needed to influence those results.
Think of it this way: SE Ranking is your fitness tracker showing the data. Discovered Labs is your personal trainer designing your program and coaching execution.
What SE Ranking does well
SE Ranking offers three features for monitoring AI-generated search results.
AI Overviews Tracker: Track your presence in Google AI Overviews and see where your website ranks within them. Compare your position in traditional results versus AI answers side-by-side.
AI Mode Tracker: Compare your visibility in AI Mode, AI Overviews, and traditional organic results. Check search volume of queries triggering AI responses and see what mentions your business receives.
AI Visibility Tool: Monitor AI answers tied to your tracked keywords. See linked and unlinked brand references and track competitor citation frequency.
SE Ranking shows you where competitors appear in AI answers while you remain invisible. It quantifies the gap but does not close it. The platform does not write content, structure it for LLM retrieval, build third-party validation, or publish at the daily velocity required to capture buyer-intent queries.
Annual billing for SE Ranking starts at $52/month for the Essential plan, $95.20/month for Pro, and $207.20/month for Business. You pay for tracking and insights. You still need an internal team or agency to act on them.
What Discovered Labs executes
Discovered Labs is an organic search agency specializing in getting B2B brands cited by AI platforms. We handle both the strategy and the execution.
Our packages start at 20 articles per month using the CITABLE framework, which stands for:
C - Clear entity and structure: Open with a 2-3 sentence BLUF that explicitly identifies who you are and what you do.
I - Intent architecture: Answer the main question and adjacent questions users are likely to ask next.
T - Third-party validation: Include reviews, user-generated content, community mentions, and news citations.
A - Answer grounding: Provide verifiable facts with sources, not vague claims.
B - Block-structured for RAG: Use 200-400 word sections, tables, FAQs, and ordered lists AI retrieval systems can parse.
L - Latest and consistent: Include timestamps and ensure your facts are unified across your site, G2, Wikipedia, and other sources.
E - Entity graph and schema: Make explicit relationships clear, such as integrations with Salesforce and HubSpot.
We ship content daily, not monthly. We build third-party validation through Reddit marketing using aged, high-karma accounts. We track citation frequency across ChatGPT, Claude, Perplexity, and Google AI Overviews, then report on AI-referred traffic, trials, pipeline, and revenue.
One B2B SaaS company increased AI-referred trials from 550 to 2,300+ in four weeks after we shipped 66 optimized articles. Their citation uplift across ChatGPT, Claude, and Perplexity grew by 600%.
Discovered Labs pricing starts at €5,495 per month with month-to-month terms. No long-term contracts. You pay for execution, results, and the internal technology we use to track what content drives citations.
| Dimension |
SE Ranking |
Discovered Labs |
| Primary function |
Track and monitor visibility in traditional search and AI results |
Engineer content and authority to get brands cited by AI |
| Output |
Reports showing rankings, visibility metrics, competitor insights |
Daily published content following CITABLE framework plus citation reports |
| AI capability |
Monitor presence in AI Overviews, AI Mode, AI-generated answers |
Influence AI citations through content optimized for LLM retrieval |
| Resource requirement |
Internal team needed to act on insights and execute strategy |
Managed service with no internal execution burden |
SE Ranking can show you that competitors appear in 65% of high-intent buyer queries while you appear in 0%. That data creates urgency. But data alone does not change the outcome.
The execution gap has three parts: volume, structure, and validation.
Volume: Why daily publishing matters
To win in AI search, you need content that answers hundreds of specific buyer questions. Not 8-10 blog posts per month. You need 20-60+ pieces per month, each structured as a direct answer to a question prospects actually ask AI.
Buyers ask ChatGPT highly specific questions that include their current tech stack, budget range, and use case requirements. If your content answers adjacent but not exact questions, you lose the citation to a competitor whose content nails the context.
Discovered Labs' packages start at 20 articles per month, with larger clients reaching 2-3 pieces per day. This is not generic blog content but researched, structured pieces designed as direct answers to buyer questions. SE Ranking shows you the gap but does not write the content to fill it.
Structure: The CITABLE framework for LLM retrieval
Standard blog posts optimized for Google fail to get cited by AI because they lack the structural elements LLMs prioritize. Our CITABLE framework ensures every piece includes clear entity identification, block structure with tables and FAQs, verifiable facts with sources, and third-party validation from reviews and community mentions.
SE Ranking can show you whether content gets cited. But the platform cannot restructure your existing content to match what LLMs retrieve, and it cannot produce new content at the velocity you need to capture your category.
Validation: Building authority beyond your website
AI models trust the consensus more than your opinion. When ChatGPT considers citing your brand, it checks whether Reddit discussions mention you positively, whether G2 reviews validate your claims, whether industry publications reference you. If your information conflicts across sources or third-party validation is sparse, AI systems cite competitors instead.
We build this validation systematically. Our Reddit marketing service establishes organic presence in relevant subreddits. We help clients build review profiles on G2 and Capterra. SE Ranking can monitor competitor mentions. It cannot execute campaigns to build your own third-party authority.
How to build a hybrid search strategy (the both and approach)
The winning strategy combines SE Ranking's monitoring with Discovered Labs' execution. Use the tool to see where you stand and track progress. Use the managed service to change where you stand.
Step 1: Establish your baseline with SE Ranking
Use SE Ranking's AI Overviews Tracker to identify which target keywords trigger AI-generated results. Track your presence over a 2-4 week period to establish a baseline.
Use the AI Visibility Tool to monitor how often competitors get cited for the same queries. Look for patterns in which brands AI platforms recommend.
This baseline tells you where the gaps are. If competitors appear in 60-75% of AI answers while you appear in 0-5%, you have a clear target.
Step 2: Deploy Discovered Labs to fill the gaps
Once you know which queries matter and where you are invisible, we build the content strategy to close those gaps.
We start with an AI Visibility Audit testing buyer-intent queries across ChatGPT, Claude, Perplexity, Google AI Overviews, and Microsoft Copilot. The audit shows exactly which competitors are cited, what content they have that you lack, and which questions represent quick wins.
From there, we produce 20+ articles per month using the CITABLE framework. Each piece targets specific buyer questions where you are currently invisible. We structure content for passage retrieval, include verifiable facts AI can cite with confidence, and ensure entity relationships are explicit. Research shows that AI search visitors convert at a 23x higher rate than traditional organic search visitors, and for Ahrefs those visitors generated 12.1% of signups despite accounting for only 0.5% of traffic.
Step 3: Validate progress using SE Ranking data
As we ship content and build third-party validation, use SE Ranking to track the change in your AI visibility. Check weekly whether your citation rate is growing for target queries.
Compare traditional keyword rankings with AI citation rates. You may find that some keywords drive strong traditional traffic but zero AI citations. Those represent opportunities to optimize existing content using the CITABLE framework.
Use SE Ranking's AI Mode Tracker to monitor whether search volume is shifting toward queries that trigger AI responses.
Step 4: Create a feedback loop between insights and execution
Your hybrid strategy works best when you feed insights from SE Ranking into the Discovered Labs content calendar, and citation performance from Discovered Labs validates what SE Ranking is tracking.
For example, SE Ranking might reveal that competitors are cited frequently for "healthcare analytics platform with Epic EMR integration" while you are invisible. Feed that insight to Discovered Labs, and we produce a targeted cluster answering that question plus adjacent ones like "Does [your product] integrate with Epic?" and "Best healthcare analytics for hospitals using Epic and Cerner."
One to two weeks after publishing, check SE Ranking again to see whether your citation rate improved. If it did not, we analyze why and adjust. This feedback loop creates continuous improvement. SE Ranking identifies problems. We solve them. SE Ranking validates the solution.
Measuring success: Integrating SE Ranking data with Discovered Labs reporting
Track three metrics to demonstrate ROI.
Metric 1: Share of voice in AI citations
Share of voice measures how often you get cited versus competitors for a defined set of buyer-intent queries. We track this across ChatGPT, Claude, Perplexity, Google AI Overviews, and Microsoft Copilot.
SE Ranking complements this by showing your presence in AI Overviews and traditional rankings. Compare the two datasets to see whether traditional ranking strength correlates with AI citation frequency. Often it does not.
Target: Grow share of voice from 0-5% to 20-30% within three to four months.
Metric 2: AI-referred traffic and pipeline contribution
AI-referred traffic converts better than traditional organic search because prospects arrive after being told you fit their needs. They are not browsing. They are validating what ChatGPT or Perplexity already recommended.
Track AI-referred visitors using UTM parameters and traffic source tags. Measure how many convert to MQLs, SQLs, and opportunities. Compare conversion rates to traditional organic search to quantify the quality advantage.
We provide dashboards tracking AI-referred traffic, trials, pipeline, and revenue. Integrate this with SE Ranking's traffic estimates to see the full picture of organic performance.
Target: Grow AI-referred MQLs from fewer than 20 per month to 100-200 per month within 90 days, with conversion rates 2-3x higher than traditional organic search.
Metric 3: Competitive positioning over time
Use SE Ranking to monitor competitor visibility trends. If their citation rates drop while yours climb, it signals you are winning share of voice. Track which competitors are cited most often and for which queries.
Combine SE Ranking's competitor tracking with our citation reports to build a competitive positioning narrative for board presentations. Show the CEO that six months ago competitors dominated 70% of AI citations while you had 0%, and now you own 35%.
When SE Ranking is enough (and when it is not)
SE Ranking alone works if:
- You have a strong internal content team with capacity to produce 20+ articles per month
- You have deep expertise in AEO and LLM retrieval patterns
- Your category has low competition in AI search
- You can manage third-party validation campaigns across Reddit and G2
You need Discovered Labs when:
- Competitors are already cited by ChatGPT and Perplexity while you remain invisible
- Your internal team is maxed out managing traditional SEO and demand generation
- You need measurable pipeline impact within 90-120 days
- You lack the technical expertise to structure content for LLM retrieval
The hybrid approach works because SE Ranking and Discovered Labs are complementary. One is for seeing, the other is for doing.
Conclusion
Traditional search is not dead, but it is no longer the only battlefield. With Gartner predicting a 25% drop in search volume and nearly half of B2B buyers using GenAI, the question is not whether to invest in AI visibility but how fast you execute before competitors own your category.
The winning strategy is hybrid. Use SE Ranking to monitor your baseline and validate progress. Use Discovered Labs to fill the gaps with content engineered for citations. Together, they cover both traditional search and the AI platforms where your buyers now start research.
See exactly where you are invisible compared to competitors. Book an AI Visibility Audit with Discovered Labs and we will show you which buyer-intent queries cite competitors while missing you, then build the roadmap to close those gaps.
FAQs
Can I use SE Ranking for AEO? SE Ranking tracks AI visibility but does not create content. You need a team or agency to produce 20+ articles per month structured for LLM retrieval.
Does Discovered Labs replace my SEO agency? We handle both traditional SEO and Answer Engine Optimization, so we can replace a traditional agency or work alongside one that focuses on link building.
How fast does AEO deliver results? Initial citations typically appear within 1-2 weeks after publishing content using the CITABLE framework. Full optimization with 20-30% citation rates takes three to four months.
What is the ROI of combining SE Ranking and Discovered Labs? SE Ranking costs $52-$207/month for tracking. Discovered Labs starts at €5,495/month for execution. If this grows AI-referred MQLs from 20 to 150/month with 2-3x higher conversion rates, the pipeline value justifies investment within 90 days for most B2B companies with $80K+ average deal sizes.
Should I track AI citations myself or use a tool? Manual tracking across multiple AI platforms is time-intensive. SE Ranking automates this, while we include citation tracking as part of our managed service with competitive benchmarking and share of voice reporting.
Key terms glossary
Answer Engine Optimization (AEO): The practice of optimizing content to get cited by AI-powered platforms like ChatGPT, Claude, Perplexity, and Google AI Overviews when they answer user questions.
CITABLE Framework: Discovered Labs' 7-part methodology for structuring content that AI systems cite, covering clarity, intent, third-party validation, answer grounding, block structure, latest information, and entity relationships.
Share of Voice: The percentage of AI-generated answers that cite your brand versus competitors for a defined set of buyer-intent queries in your category.
AI Overviews: Google's AI-generated summaries that appear at the top of search results, synthesizing information from multiple sources with citations.
LLM Retrieval: The process by which Large Language Models search for, extract, and cite relevant passages from indexed content when generating answers to user queries.
