Use these templates to turn client questions, professional experience, and research into content that helps readers assess a problem, understand a service, and evaluate the supporting evidence. Part B supplies client and referrer questions; Part D supplies approved firm and professional facts; Part E covers technical publication checks; Part C records subsequent AI-answer observations.
Fill the bracketed fields, retain supporting records, and publish approved material. Distinguish what the firm did, what was observed, and what the evidence supports. Google’s content guidance emphasizes useful original contributions and clear authorship.
Shared content and evidence record
[Content ID/type; intended reader; Part B question IDs; decision supported; accountable expert; author/reviewer; Part D dependencies; source/claim IDs; permissions; version; publication date; review trigger].
For each consequential claim, complete:
[Exact claim; evidence location; evidence basis; population/project scope; measurement period; calculation if applicable; qualifications; verification status; permitted public wording; reviewer/date].
Keep evidence basis, such as measured, client-reported, modeled, or professional interpretation, separate from verification status. A client-approved statement can still require qualification. If support is missing, assign a research task, narrow the wording, or remove the claim.
F.1 Service-page brief
Brief template
Brief field | Complete before drafting |
Reader and trigger | [Who is considering this service? What event or problem prompts action? Which decision must they make?] |
Questions to answer | [Primary question and supporting questions from Part B, in the reader’s language.] |
Service and fit | [Approved service name; suitable clients and situations; jurisdiction; scope; exclusions; prerequisites.] |
Work and deliverables | [Activities; stages; client inputs; decisions; outputs; dependencies; who implements recommendations.] |
Professional responsibility | [Responsible practice and people; links to current profiles and relevant credentials from Part D.] |
Supporting evidence | [Approved case, research finding, methodology, or worked example; source and qualifications for each proof point.] |
Engagement questions | [Timing factors; commercial approach; information needed to scope work; limits on what can be specified publicly.] |
Next step | [Appropriate contact or action; what the reader should prepare; content owner.] |
Suggested page structure
Open with a direct explanation of the service and who it helps. Describe the situations in which it is useful, then explain the work, deliverables, and client responsibilities. Present relevant evidence beside the claim it supports. Introduce the responsible professionals, answer material engagement questions, and finish with a clear next step.
Opening pattern:
“[Practice] advises [defined audience] on [problem or decision] in [relevant scope]. The work includes [activities] and produces [deliverables]. It is suitable when [conditions]; [important limitation or dependency].”
Use this as a drafting aid. Do not manufacture a fixed timetable, fee, process, or outcome to fill a field. Mark missing information for the practice owner to supply.
Adaptation across professions
Sector | Useful focus and boundary |
Consulting | Explain the decision or operating problem, diagnostic method, recommendations, and implementation ownership. Distinguish advice delivered from benefits subsequently realized. |
Accounting | Identify the particular accounting, tax, reporting, or advisory service and relevant period/jurisdiction. Describe any separately authorized assurance work accurately. |
Law | Define the matter type, jurisdiction, stages, and lawyer’s role. Describe possible approaches and dependencies without presenting an earlier result as a promised outcome. |
Engineering consulting | Specify discipline, asset or project stage, inputs, design basis, and deliverables. Distinguish appraisal, design, inspection, testing, and certification where relevant. |
Create separate pages when reader needs, service scope, or jurisdiction materially differ. For minor wording variations, improve the existing page and link to distinct supporting material.
F.2 Case studies and experience capture
Case-study record
[Case ID; reader question; engagement dates; service; responsible team; current-firm or prior-employer experience; evidence owner; named/anonymous presentation; permission scope; reviewer; approved version].
Case-study template
Context. [Describe the client’s relevant situation, sector, geography, scale, and decision. Include only approved identifying details.]
Constraints. [Record time, data, budget, technical, organizational, or jurisdictional conditions that shaped the work.]
The firm’s role. [State precisely what the firm was engaged to do. Identify client responsibilities, other advisers, subcontractors, and implementation ownership where material.]
Work and judgment. [Explain the investigation, options considered, decisions made, and reasons for the approach. Identify the professional contribution.]
Deliverables. [List what was produced: advice, design, analysis, controls, report, transaction support, or another defined output.]
Observed results. [State what changed, how it was measured, over what period, and who supplied or verified the evidence.]
Limits and lessons. [Explain other influences, unresolved matters, and the conditions under which the lesson may be useful elsewhere.]
Keep delivery, observed outcomes, and attribution distinct. HM Treasury’s evaluation methods guidance supports examining other explanations when assessing contribution; a before-and-after observation alone does not isolate the firm’s effect.
Outcome evidence record
[Outcome; baseline; comparison value; unit; denominator/sample; dates; calculation; evidence source; measured/client-reported/modeled status; verification method; other influences; approved wording].
Check that comparisons use compatible definitions and periods. Preserve unfavorable or inconclusive findings that materially affect the interpretation. If no outcome measure exists, explain the deliverable and supported qualitative result.
Illustrative wording using invented figures:
“Median review time was 18 days for 12 comparable projects in [baseline period] and 12 days for 12 projects in [comparison period]. The client also changed its staffing and approval process. The study did not isolate the contribution of the firm’s recommendations.”
Experience-capture questions
Ask the practitioner:
- What was difficult or uncertain, and what evidence did you have?
- Which options did you consider, and why did you choose this approach?
- What did you personally do, and what did others contribute?
- What changed your initial judgment?
- What would need to be true for the same lesson to apply elsewhere?
Retain notes and supporting artifacts. Practitioner recollections should remain identified as recollections until corroborated.
Publication permissions
Record approval for the exact names, logos, quotations, figures, images, channels, and duration of use. Check whether combinations of details could identify an anonymous client. Preserve confidentiality and any restrictions applicable to the engagement.
Attribute prior-employer experience accurately. Label composite or hypothetical examples prominently and keep them separate from claims about actual engagements. Never invent a client quotation or convert an estimate into a measured result.
F.3 Research methods and reporting
Research protocol
[Study ID/version; question; intended use; lead researcher; sponsor/funder; population or material examined; unit of analysis; inclusion/exclusion rules; method; recruitment or source selection; collection dates; instrument; analysis plan; permissions; data access/retention; limitations; publication plan].
Choose the method from the question. Check whether suitable existing evidence can answer it before collecting new data. AAPOR’s survey research guidance recommends considering alternative methods and designing specific, neutral questions rather than seeking predetermined findings.
Method selection map
Method | Useful application | Evidence and limits to record |
Interviews | Understand decisions, language, tradeoffs, and experiences. | Participant selection, guide, notes/transcripts, coding, contradictory views, and whose perspectives are missing. |
Survey | Describe responses to defined questions. | Population, recruitment, mode, questionnaire, achieved sample, missing responses, weighting, and uncertainty. |
Project-record analysis | Examine patterns across engagements, transactions, or assets. | Inclusion rules, record completeness, comparable definitions, denominators, selection effects, and permissions. |
Evidence review | Compare published findings, standards, decisions, or technical approaches. | Sources searched, dates, queries, selection criteria, extraction method, study quality, and conflicting evidence. |
Technical test or simulation | Evaluate performance under stated conditions. | Setup, equipment/software versions, assumptions, test cases, repetitions, calibration or validation, and uncertainty. |
For consulting, a study might examine how implementation decisions were made. For accounting, it might analyze recurring reporting-process issues. For law, it might examine a defined set of published decisions or contract provisions. For engineering, it might compare measured or simulated performance under a documented test protocol. These are possible study designs, not findings.
Research execution checklist
- Specify the question and analysis. Define outcomes and comparisons before reviewing results. Record later changes and identify exploratory analysis.
- Test the collection method. Pilot questions, coding rules, extraction sheets, or test procedures. Confirm that terms mean the same thing to respondents and analysts.
- Preserve the evidence. Retain source versions, dates, instruments, permitted records, and analysis files. Restrict access according to the data and engagement.
- Check the analysis. Review exclusions, duplicates, missing values, denominators, calculations, and sensitivity to assumptions. Have another qualified reviewer reproduce consequential calculations.
- Challenge the interpretation. Look for contrary evidence and alternative explanations. Match the conclusion to the study design, population, and conditions.
Interpretation rules
Interview themes can explain experiences without establishing their prevalence in a wider population. Case studies selected for particular characteristics need explicit limits on generalization. Distinguish association, plausible contribution, and evidence supporting a causal conclusion.
For surveys, report the number answering each material question and identify the sampling method. For an opt-in sample, do not report a conventional sampling margin of error. Any model-based precision measure needs its model, assumptions, validation, and calculation explained, as set out in AAPOR’s transparency guidance.
Public methodology statement
“[Organization] conducted [method] during [dates] to examine [question] among [population/material]. We selected [number and selection method] and analyzed [data] using [method]. [Sponsor] funded the work. Principal limitations are [limits]. The instrument, definitions, and permitted supporting materials are available at [location].”
Add response, weighting, quality-control, and uncertainty details where relevant. Explain access restrictions without publishing confidential raw data.
If AI assists collection, coding, or analysis, record its task and human validation and disclose material use in the methodology. Identify generated responses separately; they are not evidence of real participants’ experiences. Current AAPOR transparency guidance explicitly addresses these distinctions.
F.4 Publication and maintenance checklists
Publication review
Complete each check with [Pass / revise / not applicable; evidence; reviewer/date]. Explain “not applicable.”
Check | Acceptance question |
| Does the content answer the defined question and support a practical decision? |
| Does it add supported experience, analysis, evidence, or explanation? |
| Can every consequential assertion be traced to adequate evidence, with qualifications beside the claim? |
| Are calculations, units, dates, samples, denominators, and comparisons correct? |
| Has the responsible expert checked scope, jurisdiction, terminology, credentials, and current Part D facts? |
| Are methods, funding, limitations, and material AI use disclosed? Are observations and estimates distinguished? |
| Are client details, quotations, images, third-party material, and research data approved for the intended use? |
| Are authors and reviewers accurately identified, their roles clear, and source links functional? |
| Are headings, tables, captions, alternatives, downloads, links, and applicable Part E checks complete? |
| Are the approved version, publication owner, review date, correction route, and monitoring references recorded? |
Never fabricate authors, references, credentials, interviews, or findings. If AI assists drafting, the named expert remains responsible for the published claims. Disclose substantial automation where readers would reasonably expect to understand how the content was produced, consistent with Google’s guidance.
Release record
[Content ID/version; decision: publish / revise / hold; approvals; unresolved issues; approved limitations; canonical publication URL; related pages/assets; release date; owner; review date].
Resolve unsupported material claims and missing publication permissions before release. Confirm the live page and downloads match the approved version. Preserve qualifications in summaries, charts, promotional excerpts, and linked service pages.
Maintenance and correction record
[Content ID; change trigger; affected claims/assets; correction; evidence; reviewer; publication date; related Part D change; Part E retest; Part C monitoring reference].
Reopen review when source evidence changes, a credential or service changes, a study is superseded, or a material error is found. Record substantive corrections and their dates; distinguish publication, review, and modification dates.
Use Part C to observe whether subsequent AI answers represent the published work accurately. Keep content changes, observation dates, and other concurrent changes visible so later results are interpreted with appropriate limits.
