How to Read Influencer Data: Median Views, Audience Fit and Risk + Free Influencer Data Audit Template (Word)
Follower count is useful context, but it cannot show how many people typically watch, whether they match the customer or whether one viral post hides ordinary performance. Start with the campaign outcome.
Read four evidence layers together
Dimension | Weak evidence | Stronger evidence | Brand decision |
|---|---|---|---|
Audience | Followers only | Location and demographics | Target fit |
Consistency | Best view only | 10–20 post median | Typical expectation |
Engagement | Likes only | Comment quality and saves | Intent and trust |
Risk | No record | Identity, partners, issues | Suitability |
Start with the outcome, not followers
Awareness needs relevant reach and recall; enquiries or sales need links, codes, WhatsApp or store evidence; asset production may value quality, rights and delivery reliability more than account reach.
Why median views matter
An average can be lifted by one viral post. Sort the last 10–20 comparable organic posts and take the middle value. Keep the minimum, maximum and sponsored-content notes so the summary does not hide variation.
Audience fit needs geography and role
“Hong Kong audience” may include local Chinese-speaking residents, cross-border visitors, students, parents or professionals. A tourism offer and a local regulated service need different people.
Engagement quality beats one rate
Comments about product use, price, booking and purchase carry more intent than generic praise. Compare like-for-like platform formats and write down the denominator used for any rate.
Identity and brand safety
Confirm the creator's own profiles and cross-platform links, then review recent work, previous partners, disclosure and material controversies. Identity verification is not a safety guarantee; refresh the review before contracting.
Hong Kong planning budget and timing
Allua may scope HK$8,000–30,000 for initial review of 10–30 candidates and deeper review of five to ten, or HK$30,000–150,000+ for a managed campaign covering outreach, briefing, content and reporting over roughly four to ten weeks. These are service-planning ranges, not creator quotes or outcome guarantees.
Free resource: Influencer Data Audit Template
Record median views, audience fit and evidence to support creator shortlisting. Get an editable Word version to adapt and reuse for your team.
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Use one row per creator. Date every screenshot and reporting period. Mark missing evidence as “not provided,” never as an estimate. Set knockout rules before weighted scoring.
01 | Identity
Do official profiles, other platforms and the creator's link hub corroborate one another?
02 | Content category
How many of the last 20 posts truly match the brand use case?
03 | Followers
Record date; do not treat followers as reach.
04 | Median views
Sort 10–20 comparable organic posts and take the midpoint.
05 | View range
Keep minimum, median and maximum, flagging viral or paid work.
06 | Engagement quality
Sample 20 comments: specific questions, experience, generic praise or suspicious activity.
07 | Saves and shares
Where available, assess whether they match research, tutorial or buying intent.
08 | Audience geography
Use native screenshots and distinguish resident from traveller assumptions.
09 | Audience profile
Keep only age, gender or interest fields material to the campaign.
10 | Commercial history
Review recent ad density, competitors, performance and disclosure.
11 | Brand safety
Record controversies, sensitive claims and conflicts with brand values.
12 | Measurement readiness
Can the creator provide native data, UTM/code support and a dated report?
Worked example
Creator A has 200,000 followers but 8,000 median views across 12 comparable posts and no audience-location evidence. Creator B has 60,000 followers, 15,000 median views, more Hong Kong users in native screenshots and comments about store visits. For a Hong Kong retail enquiry objective, B may be stronger, subject to tracked validation.
Frequently asked questions
Which engagement-rate formula should we use?
Choose one denominator—followers, views or reach—then compare the same platform, format and period and write the formula down.
Can a third-party tool detect fake followers?
It may flag anomalies, not prove misconduct. Combine native evidence, distribution, comment quality and identity checks.
How many posts are enough?
There is no universal number. Ten to 20 comparable organic posts is a practical start; seasonal or low-frequency accounts need a longer period.
Does strong data guarantee fit?
No. Audience, safety, creative style, rights, timing and reliability must also match.
Turn data into an explainable shortlist
Share the audience, platform, market, budget, content use and success definition. Allua can organise candidates, evidence gaps and risks. Contact Allua to audit influencer data
Creator partnership invitation
Creators may submit the Allua creator partnership form with official profiles and collaboration information for future campaigns and editorial consideration. Submission does not guarantee selection or work.
Information checked: . Public and third-party data changes; reconfirm native analytics and formal terms before engagement. Budgets are Allua planning recommendations.
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