The CORE methodology

The Research Behind TopCited

A practical, effective way to improve your product's visibility in AI search is the CORE methodology — Controlling Output Rankings in Generative Engines. Unlike traditional SEO tools built on keywords and backlinks, CORE is a peer-reviewed, data-driven method designed to optimize how large language models rank and recommend products in AI-powered search.

Your products are invisible to AI

When a customer asks an LLM 'recommend a good camera,' the AI's answer is almost entirely determined by search engine retrieval order. Products at the bottom of retrieval have a 0% chance of being recommended.

The gatekeeper changed

ChatGPT processes 2.5 billion queries per day. Consumers are replacing 'Google it' with 'ask AI.' If your product isn't optimized for AI search, you're losing customers every day.

SEO alone isn't enough

Traditional SEO gets you into Google results. But LLMs re-rank and synthesize those results before showing them to users. Your Google ranking doesn't guarantee an AI recommendation.

No existing playbook

Keywords, backlinks, and meta tags don't influence how LLMs rank products. Until now, there was no systematic way to improve your visibility in AI-powered search.

Research, rewrite, simulate, repeat

CORE closes the loop that monitor-only tools leave open. Every pass moves a page measurably closer to the answer an LLM names first.

  1. 01

    Research the signals

    We start from the published evidence on what makes AI engines cite a source — leading statistics, named sources, and explicit comparisons drive the largest visibility gains. CORE encodes those findings instead of guessing at keyword density or backlinks.

  2. 02

    Rewrite answer-first

    Your content is restructured to answer the buyer's question in the first 40 words, lead with a verifiable statistic and source, and make an honest comparison to the alternatives — the structure LLMs are happy to quote.

  3. 03

    Simulate the AI ranking

    Before anything ships, we run the rewrite through the same major LLMs your customers use and score how readily each one cites it — a 0–100% ranking-fit measure, not a gut feeling.

  4. 04

    Iterate until you win

    Each pass feeds the score back into the rewrite. We refine and re-simulate until the page reliably earns a top recommendation across models — then keep monitoring as the models change.

Tested across 15 categories, 3,000 products, 4 LLMs

Our CORE optimization method was rigorously evaluated in a peer-reviewed study using ProductBench, a benchmark of 15 product categories with 200 products each, tested on four major LLMs with search capabilities.

Validation coverage
  • 4
    LLMs monitored
  • 3,000+
    Products validated
  • 15
    Product categories
Measured lift after optimization
91.4%
Top-5 promotion
86.6%
Top-3 promotion
80.3%
Top-1 promotion
0→91%
Baseline to optimized

Find out where CORE can move you

We'll audit your top 10 products across ChatGPT, Gemini, Claude, and Grok and show you exactly where you rank today — and where CORE can take you. Free, no commitment.

The CORE Methodology: How TopCited Wins AI Search