How to Create Link-Worthy Research for Affiliate Sites Using Public Data
A useful comparison can give publishers a reason to cite an affiliate website beyond its product reviews. Public datasets offer a practical starting point: take a question your audience cares about, analyse reliable figures and publish findings that someone else can check.
The value comes from the work you add—cleaning records, making fair comparisons and explaining what the results mean. Effective original research for link building does not require an expensive survey, but it does require a clear method and a finding worth reporting.
Start with a question that serves readers
Choose the question before searching for an attention-grabbing result. This helps prevent selective analysis designed to produce a convenient headline.
For a travel affiliate site, a useful question might be: “Which destinations have accommodation demand spread most evenly throughout the year?” That connects to travel planning and gives regional publishers a potential local story.
Other possibilities include comparing changes in broadband availability or tracking household energy consumption across comparable areas. Each project needs a defined audience, geographical scope and measurable question.
Before collecting anything, write down:
- What decision could this research help readers make?
- What comparison would add something beyond the source tables?
- Which publications cover that question?
- What evidence would justify the intended headline?
For a limited budget, start with one market, one main dataset and one transparent metric. Expand after establishing that the data supports a worthwhile comparison.
Select sources for comparability as well as authority
Begin with national statistical offices, regulators, local authorities and established public research bodies. Download the underlying tables and read their accompanying documentation.
A reputable publisher is a starting point. You still need to establish whether its figures answer your question.
Check:
- Definitions: Does “accommodation” include hotels, holiday rentals or both?
- Coverage: Are domestic and international visitors included?
- Geography: Are you comparing cities, municipalities or wider regions?
- Timing: Do all observations cover the same period?
- Completeness: Are values missing, suppressed or provisional?
- Continuity: Have reporting methods or boundaries changed?
For research spanning the UK, Europe and the Gulf, verify these details for each source. English translations of similar category names do not establish that the underlying measures are equivalent.
Prefer a smaller, defensible comparison over a broad ranking assembled from incompatible figures. Describe the scope accurately: “among the 18 destinations included” is more precise than “the world’s best destinations”.
Check reuse rights before building the analysis
Public access and permission to republish are separate checks. Record the licence attached to each dataset, including its commercial-use conditions and required attribution.
For example, the UK’s Open Government Licence v3.0 permits commercial reuse of information covered by it, subject to its conditions, including attribution. It excludes personal data and third-party rights that the information provider cannot license. Its terms also prohibit suggesting official endorsement.
Check the terms for the exact material you intend to use. A downloadable table, an accompanying photograph and a publisher’s logo may have different permissions.
Preserve the licence details alongside your research files. If reuse rights remain unclear, resolve that before including the material in a public download.
Build a calculation readers can reproduce
Keep an untouched copy of every source file. Perform cleaning and calculations in separate files, recording each transformation.
Worked example: accommodation seasonality
Suppose a travel affiliate site wants to compare how concentrated overnight stays are during the year.
A straightforward measure is:
Share in the three busiest months = overnight stays in those months ÷ overnight stays across all 12 months × 100
Calculate each destination’s three busiest months separately. They need not be consecutive or fall in the same season.
The following figures are hypothetical and illustrate the calculation:
| Destination | Annual overnight stays | Stays in its three busiest months | Share |
|---|---|---|---|
| Area A | 1,000,000 | 450,000 | 45% |
| Area B | 800,000 | 240,000 | 30% |
Area B has a smaller share of annual stays concentrated in its three busiest months. That supports a narrowly defined finding about seasonality.
Claims about cheaper hotels, quieter streets or better availability would require additional evidence.
Set inclusion rules before ranking destinations. For this example, require 12 usable monthly observations, consistent accommodation coverage and a positive annual total. Treat missing or suppressed values as unavailable; never silently replace them with zero.
If source data supports only a partial comparison, narrow the research question.
Test the finding before writing the headline
Check both the arithmetic and the interpretation.
Manually recalculate several results, including the highest and lowest values. Inspect unusually large changes against the original records. Confirm that joins between datasets have not duplicated rows or confused similarly named places.
Rank using unrounded values, then round for display. Explain how ties are handled. Where estimates include substantial uncertainty, avoid presenting small differences as decisive.
If you create a combined score, justify its ingredients and weights. Recalculate it using plausible alternative weights. A leaderboard that changes dramatically under small adjustments needs that instability explained.
Also review the editorial claim. “Lowest measured concentration among included destinations” describes the example metric. “Best place for an affordable holiday” introduces a judgement the calculation cannot support.
Use a reusable research template
Complete this brief before publication. Keep it with the working files and use its contents to write the public methodology.
| Field | What to record |
|---|---|
| Research question | The precise question, intended reader and practical relevance. |
| Scope | Countries or regions covered, reporting period and unit of comparison. |
| Source selection | Publisher, dataset title, table identifier, source address and reason for choosing it. |
| Source version | Release date, retrieval date and saved filename or version identifier. |
| Licensing | Applicable licence, commercial reuse terms, attribution wording and exclusions. |
| Inclusion rules | Which observations qualify, which are excluded and why. |
| Cleaning | Treatment of duplicates, missing values, suppressed figures and geographical changes. |
| Methodology | Formulas, denominators, conversions, weights, rounding and tie rules. |
| Validation | Manual checks, reconciliation with source totals and sensitivity checks where relevant. |
| Limitations | Coverage gaps, uncertainty, reporting differences and conclusions the data cannot establish. |
| Publication | Findings, charts, downloadable results, attribution and public methodology. |
| Updates | Review owner, expected source release schedule, revision process and correction history. |
Make the public explanation specific enough for another analyst to reproduce the result. “We analysed official statistics” leaves too much unexplained.
Publish something journalists can cite
When using public data for digital PR, make verification easy. Publish the research on a stable page with a clear publication date, reporting period and concise explanation of the main finding.
Include the full comparison table, a readable chart, source references and methodology. Where permissions allow, provide a downloadable file containing the calculated results and source identifiers.
Distinguish your contribution from the underlying collection. Describe the work as your analysis of public data; credit the organisations that collected it.
For an affiliate website, disclose the commercial relationship with the topic. Explain any affiliate links, and make sure commission arrangements do not determine which places or products enter the research.
Pitch a relevant finding to each publication: a regional comparison for a local outlet, or a broader pattern for a specialist editor. Citeable research gives editors evidence to assess; coverage remains their decision.
Control costs and plan the next update
Set a time budget for checking feasibility before committing to design or outreach. If essential definitions are incompatible, stop or narrow the scope while the investment is small.
A spreadsheet may be sufficient for a modest dataset. Prioritise reliable calculations, clear documentation and one useful chart before commissioning interactive features.
Measure the campaign through relevant editorial citations, referral engagement and affiliate conversions where attribution is available. Review search impressions and organic clicks alongside other site changes; a change in Domain Rating alone is insufficient evidence of commercial value.
Assign someone to check the next source release. Preserve dated versions, record corrections and distinguish revised historical figures from newly added observations. That makes the research easier to maintain—and gives publishers a dependable reference they can return to.