Reading Pugongying Audience Profiles: From Follower Counts to Real Due Diligence

Judging a creator by follower count alone is the easiest way to waste a campaign budget. A 100k account can have 80% of its audience outside your target cities, or a dominant age band a full generation away from your buyers. The Pugongying (Dandelion) data endpoints expose the platform's own audience profile — here is how to read those fields.

Four endpoints, four questions

The profile tells you who the audience is; note performance tells you whether those people actually watch. You need both — profile alone will hand you accounts with the right audience and no reach.

Reading the profile

City distribution. What matters is the concentration across the top N cities, not whether your target city appears. "Beijing 12%" means something very different when second place is 3% (genuine regional concentration) versus when places 2–5 all sit near 10% (that's just the platform baseline, and says nothing about this account).

Age distribution. Check whether the dominant band overlaps your buyers or merely covers them. A baby-care brand wants 25–34 dominant — not 18–24 at 40% with 25–34 at 30%, where your band is diluted by a younger pool.

Gender split. Be wary of extremes. Above 95% single-gender, combined with a sudden follower jump, often signals bought growth or a very narrow content mix. Cross-check the curve with fans-history.

Due diligence via the growth curve

fans-history is the most revealing of the four. Healthy growth looks like a series of small steps: a bump when a note lands, then a gentle slope. Two shapes deserve a second look:

• Vertical jumps — dozens of times the usual daily gain over one or two days, then straight back to flat.
• Sawtooth — gains and losses cancelling out, net growth near zero.

Neither is automatically disqualifying, but both are worth one more question: what got published then? Pull the notes from that window with POST /api/v2/pgy/blogger/notes. If there is no matching hit, price the risk in.

A screening order that works

1. blogger/list — build a candidate pool by category and follower band.
2. fans-profile — hard-filter on city and age. This step usually removes most of the pool.
3. notes-rate — drop the "right audience, no reach" accounts on engagement rate.
4. fans-history — due-diligence the survivors on growth shape.
5. blogger/detail — pull collaboration rates and compute cost per effective reach.

Filtering before pulling rates cuts your call volume noticeably. The rates endpoint is the last step, not a screening tool.

Get started

Sign up free and call the Pugongying endpoints directly — only successful calls are billed. Fields and pagination are in the docs. For the wider workflow, see influencer selection with the Pugongying API.