AcademicJournal of Marketing, 2026

More unpaid posts about the same product type softened the downside of a heavier ad mix

Shortlisting creators

Reader Note:: This is hypothesis 3 of the paper, tested in the Douyin field study rather than in either experiment. "Organic product mentions" counts how often an influencer had mentioned products of the same type as the focal sponsored product in earlier unpaid posts. More of them flattens the U: the bottom of the curve shifts and the penalty for sitting in the middle gets smaller. The effect is measured on repost counts, and nothing was assigned — influencers chose their own posting mix, so what makes the curve flatter may also be what makes an influencer post about a category in the first place.
Evidence:: Observed behaviour
Vendor interest:: None
Sample:: Multimethod study: Instagram field study of 6,869 sponsored posts from 4,908 influencers; experiment with 168 Twitter users; experiment with 208 Instagram users; Douyin field study of 147,877 sponsored videos from 1,000 influencers, plus comment-text analysis on 2,015,022 comments from 24,199 sponsored videos by 250 influencers.

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Getting a rough orientation, and deciding what to check yourself.

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Saying that one thing caused another, or predicting what you would get.
This data is old for how fast this topic moves. A lot may have changed since then.
The source talks about this as cause and effect — that is its reading, not a finding.
The source says how much it looked at, but not how any of it was chosen.

Influencer selection is mainly based on engagement rate and audience demographics (94% and 88%), with only 25% using social listening on what consumers discuss

Share of marketers using each data input to select influencers, and what it measures
Data input	Usage (%)
Engagement rate (Influencer output)	94%
Audience demographics (age, gender, location) — Influencer audience	88%
Past campaign performance data (Influencer track record)	81%
Audience interest / affinity data (Influencer audience)	78%
Follower count and reach metrics (Influencer scale)	72%

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Sponsored posts got more engagement when influencers had either very low or very high ad loads, and did worst in the middle

In creator selection, brand fit mattered most and follower count mattered least

Most Important Factor Brands Use When Selecting New Creators to Work With
Selection factor	Brands (%)
Creator suitability or fit for brand	22%
Content performance	17%
Working with a diverse group of creators	14%
Brand affinity, or a history of posting about your client	12%
Follower audience demographics	10%

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Fixing your influencer marketing campaign: How to get into the top 10% of advertisers

1.95x

higher conversion odds came with stronger creator audience-brand fit in influencer marketing campaigns

People were about twice as likely to share the sponsored Instagram post when the influencer had low or high ad load instead of a middle one

89%

of marketers do not plan to work with virtual influencers AI avatars or digital clones of creators in 2026

More unpaid posts about the same product type softened the downside of a heavier ad mix

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