The measurement structure shared by all three examples
- Scope: selected products, modes, languages, locations, and buyer questions.
- Baseline: dated repeated runs with answers, citations, and screenshots retained.
- Intervention log: every technical, editorial, profile, or outreach change recorded.
- Rerun: the same panel repeated at the agreed cadence.
- Reporting: observations separated from explanations and causal claims.
Example A: Established brand with inconsistent public facts
Hypothetical starting condition: the brand has a healthy site and existing coverage, but service descriptions, locations, leadership information, or product facts conflict across official and third-party pages.
Possible work plan
- Build a bilingual prompt panel around brand facts and buyer due diligence.
- Audit owned-page facts, supported structured data, canonical signals, and official profiles.
- Correct information the brand controls and request corrections from legitimate third parties where appropriate.
- Rerun the panel and record whether answer accuracy changed.
What could be reported: pages corrected, schema validation, profile alignment, answer accuracy, brand mentions, and citations observed in the retained runs. None of these should be described as a client result until the work has actually occurred.
Example B: Challenger brand with useful content but little corroboration
Hypothetical starting condition: the brand publishes credible first-party material but is rarely covered by independent sources and is absent from relevant category answers.
Possible work plan
- Identify which buyer questions the existing material can answer with original evidence.
- Improve sourcing, authorship, dates, methodology, and clarity on owned pages.
- Pursue legitimate editorial, partner, customer, or expert coverage without presenting paid placement as independent proof.
- Track owned citations and third-party citations as separate outcomes.
What could be reported: new verifiable sources, answer inclusion observed in repeated runs, and prompts that remained unchanged. A later movement should not be attributed to outreach or content changes without stronger causal evidence.
Example C: Brand with weak Search foundations
Hypothetical starting condition: important pages are blocked, duplicated, poorly canonicalized, dependent on client-side rendering, or missing from ordinary search indexes.
Possible work plan
- Diagnose Google and Bing index status, rendering, canonical tags, robots rules, redirects, and CDN behavior.
- Distinguish crawler purposes, including OAI-SearchBot for ChatGPT Search and GPTBot for potential model training.
- Repair the Search foundation before prescribing entity or content-expansion work.
- Use AI answer tracking as a separate outcome rather than calling an indexed page “retrieved.”
What could be reported: technical eligibility and index status. A later AI citation would be a separate observation, not proof that one technical fix caused it.
What a future published case study must include
- Client approval and enough context to understand the market and starting point.
- The prompt panel, engines, modes, languages, locations, dates, and repetition method.
- Baseline and rerun evidence, including unchanged and negative results.
- A complete intervention timeline.
- Clear separation between observed chronology, plausible explanation, and demonstrated causation.
Until that standard is met, Epilog will call these pages program examples rather than case studies.