Benchmark identity
benchmark_id, subject, canonical domain, market, locale, and frozen prompt ID
Free CSV spreadsheet
AI search prompt tracking spreadsheet
A long-format worksheet for preserving prompt context, provider conditions, brand outcomes, citations, competitors, raw evidence, and comparable reruns.
Published:
One row per observation
Keep provider results separate until analysis
The worksheet uses long-format rows: one frozen prompt, one provider surface, one run, and one date per row. That structure preserves coverage and avoids blending materially different answer environments into a single cell.
Duplicate the starter rows for each provider and rerun. Keep raw answers outside the sheet when they are large or sensitive, then store only an owner-controlled reference in the evidence column.
Six column groups
Enough context to explain every metric
Collection conditions
date, provider, product surface, model label, web-search state, session state, and run number
Answer outcome
eligible, brand mentioned, prominence, recommendation, sentiment, and representation accuracy
Source evidence
claimed-domain cited, cited URLs, cited domains, and stored-answer reference
Competitive context
competitors mentioned, leading competitor, and answer-level share-of-voice inputs
Action mapping
likely gap, next action, owner, priority, and rerun notes
Common questions
Use the resource without overstating the result
What should an AI prompt tracking spreadsheet include?
Use one row per prompt, provider, run, and date. Record the prompt ID, collection conditions, eligibility, brand mention, prominence, citations, competitors, sentiment, accuracy, raw-answer reference, and next action.
Why use long-format rows instead of one tab per provider?
Long format makes filtering, pivoting, provider comparison, reruns, and coverage calculations easier while preserving one consistent schema as platforms change.
How many prompts should I track?
Start with a small frozen core that represents important buyer decisions. A 20-to-30 prompt directional set is easier to review rigorously than hundreds of generic prompts with weak business context.
How often should prompts be rerun?
Choose a cadence that matches the decisions and content changes you need to evaluate. Keep the core set and conditions stable, and do not treat normal answer variability as a trend after one rerun.
Evidence before conclusions
See a complete benchmark before running your own
Review the questions, stored answers, citations, competitors, coverage, and five prioritized actions in the sample report.