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ORIGINAL RESEARCH & NEWSWORTHY CAMPAIGNS
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Your learning path: 12 lessons.
Module 01 / Lesson 03 · Read, apply, check
Define the population, measures, exclusions and analysis before results create pressure to change the rules.
Write down exactly what the project includes: the participating organizations, relevant records or respondents, collection period and eligibility conditions. Then define the unit being counted. For RouteDesk, the operational unit is one eligible quote request, not a unique buyer or supplier. Several requests can belong to the same organization, so the results may reflect repeated activity within that group. Record how the available records differ from the broader audience the campaign hopes to reach. This description prevents a narrow dataset from becoming an industry-wide claim when a headline is shortened or a spokesperson answers a question without the full report nearby.
Create a short data dictionary with the field names, meanings, permitted values and calculation rules. Define what counts as a reply and which deadline applies when expectations change. Decide how to handle duplicate exports, requests outside the period and records missing the timestamp needed for classification. Document these rules before inspecting which exclusions create a stronger headline. If a legitimate problem requires a later change, record the reason, version and effect rather than silently rewriting the method. A reproducible rule should help another analyst reach the same classification from the same approved material, even when the result is less dramatic than expected.
List the main calculation, a small number of justified comparisons and the minimum evidence needed to discuss a subgroup. Distinguish planned questions from exploratory patterns found later. Small groups can produce extreme percentages through very few observations, so show their counts and avoid treating them as stable rankings. Survey precision also depends on design, not sample size alone: AAPOR distinguishes sampling error from model-based precision claims for opt-in research. Do not paste a conventional margin of error onto a convenience sample. Ask a qualified researcher to evaluate uncertainty when the campaign depends on population estimates or comparisons beyond the descriptive data.
Agree who checks the instrument, extraction, analysis and release claim. Pilot the survey or record extraction on a small approved set to identify confusing questions, missing fields or inconsistent timestamps. Fix those problems before the main collection where possible, and document any implications for already collected material. Establish a stop condition if the necessary measure cannot be recovered reliably. The agency should know what happens when the evidence fails the brief: narrow the claim, redesign the study or pause the campaign. These decisions protect time and budget by preventing a polished report from being built on a measurement the team cannot defend.
Specify population, unit, period and measures.
Write classification and exclusion rules.
Choose comparisons and state inference limits.
Test the process and set a readiness gate.
RouteDesk’s synthetic analysis plan starts with two hundred and forty exported rows. It specifies one record per request, a defined collection period and a usable communicated deadline plus reply timestamp. The documented cleaning sequence will remove twenty duplicate rows, ten requests outside the period and ten remaining records with missing classification information, leaving two hundred eligible requests. The primary calculation is the proportion whose recorded reply falls after the stated deadline. The plan does not infer satisfaction, revenue loss or national supplier performance. A regional subgroup contains only eight eligible requests, so the team will not promote its extreme percentage as a robust regional ranking. A pilot also reveals inconsistent time formats, which are standardized with a recorded rule. The resulting plan gives the editor a clear boundary before any story angle is chosen.
Another team begins by sorting every possible subgroup until it finds an alarming percentage. It removes records without logging why, changes the definition of late to increase the result and attaches a margin of error copied from an unrelated poll. Nobody can recreate the calculation from the raw export. Even if some individual numbers are arithmetically correct, the report conceals the choices that produced them and invites stronger conclusions than the design can support.
A method note is not a paragraph invented after the report is written. It is a record of the decisions that make the result interpretable and reproducible. Planning does not prevent every legitimate adjustment, but it makes changes visible. Exploratory findings can be interesting when labelled and checked; they should not be disguised as the original test simply because they produced a better headline.
Use the synthetic case to practise the plan without collecting real personal information. Seek appropriate research expertise for sampling, weighting, uncertainty and causal analysis beyond your competence. Never describe an opt-in sample’s precision using an unsupported conventional sampling-error claim, and preserve a clear record of changes to definitions or exclusions.
Do this today · 30 minutes
Write RouteDesk’s analysis plan and cleaning rules.
Use a document or spreadsheet and the fictional RouteDesk case. All course figures are synthetic teaching data. No purchase, confidential data, real survey recruitment or contact with journalists is required.
Before: A desired headline with an unclear evidence base, audience and release process.
After: A bounded, reproducible finding connected to a useful audience question and an accountable campaign plan.
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Ask a colleague to challenge the claim, denominator, permissions and audience fit. Record the revision, owner and review date before using the approach with a real client.
Before you move on
The team has two hundred and forty exported rows and expects to exclude duplicates, out-of-period requests and missing timestamps. A subgroup of eight requests looks dramatic. What should be settled before the agency chooses its headline or presents a population-level precision claim to journalists?
Next lesson →AAPOR: credibility intervals and sampling error
Lesson edition 1.0 · References reviewed 17 October 2026 · Practical exercise reviewed 17 October 2026. Examples are illustrative teaching scenarios.
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Illustrative cost comparison using October 2026 plan prices; check current terms before purchase. Assumes one eligible placement per credit and comparable selected opportunities, not a prediction of rankings, revenue, coverage or AI citations. Actual suitability depends on audience fit, editorial requirements and the current plan terms. DA/DR are third-party metrics, not Google scores.
Choose publications available on your plan, prepare useful content for the audience and submit it for editorial review. Track accepted placements in your dashboard and evaluate them against your campaign goals.
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