CoChat
Sign Up
Cited by 326Digital Marketing and Social MediaMarketing and Advertising StrategiesSMEs Development and Digital Marketing

The DOI matches its Crossref record; 65 of the 65 references it cites were found in a registry or an index.

Finding Goldilocks Influencers: How Follower Count Drives Social Media Engagement

Open access
Wies, Simone, Bleier, Alexander, Edeling, Alexander·2023·Journal of Marketing
DOI 10.1177/00222429221125131
Open this paper in CoChat — free account

Abstract

Influencers’ follower count, or indegree, is a key criterion that advertisers use when devising influencer marketing campaigns. However, whether influencers with lower or higher follower count are more effective in generating engagement remains an open question. This multimethod research effort—involving an observational field data analysis, based on 802 Instagram marketing campaigns featuring more than 1,700 influencers, together with an eye-tracking study and laboratory experiments—establishes conclusive evidence of an inverted U-shaped relationship between influencers’ follower count and engagement with sponsored content. A higher follower count implies broader reach but also cues a weaker relationship that reduces followers’ engagement likelihood. That is, engagement first increases, then decreases, as influencer follower count rises. The authors further test the potential moderating effects of two campaign properties: content customization and brand familiarity. Higher content customization and lower familiarity of the sponsored brand signal that influencers value their relationships with followers and thereby flatten the inverted U-shaped relationship. Managers can leverage these novel results and the related actionable guidelines to improve their influencer marketing strategies.

Overview

Integrity signals

Registry

Crossref · 10.1177/00222429221125131

Cites

65 of 65 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Verification

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Citations

Cites

Research works printed but not linked: 6

  1. Cohen Jacob, 2003, Applied Multiple Correlation/Regression Analysis for the Behavioral Sciences
  2. 10.1509/jmkg.73.2.1 · DOI · Paper page
  3. Kerlinger Fred N., 1973, Foundations of Behavioral Research
  4. Leeflang Peter, 2016, Modeling Markets
  5. 10.1177/002224299405800403 · DOI
  6. 10.1287/mksc.1090.0520 · DOI

Cited by

Sorted by citations

See all 326

Related

See all

Metadata

Authors
Wies, S., Bleier, A., & Edeling, A.
Affiliations
Goethe University Frankfurt (DE)
Corresponding author
Wies, Simone
ORCID
Venue
Journal of Marketing
Publisher
SAGE Publications
Published
2022-11-29
Volume
87
Issue
3
Pages
383-405
ISSN
  • 0022-2429 (ISSN-L)
  • 1547-7185
DOI
10.1177/00222429221125131
OpenAlex
W4293217494
Cited by
326
References
65
Citations by year
2026: 107 · 2025: 103 · 2024: 85 · 2023: 26 · 2022: 4
FWCI
78.42
Type
journal article
Language
en
Open access
Licence
Locations
  • Journal of Marketing (publishedVersion, cc-by-nc)
  • Lirias (submittedVersion, cc-by-nc)
Topics
  • Social Sciences › Business, Management and Accounting › Marketing › Digital Marketing and Social Media
  • Social Sciences › Business, Management and Accounting › Marketing › Marketing and Advertising Strategies
  • Social Sciences › Business, Management and Accounting › Business and International Management › SMEs Development and Digital Marketing
Keywords
influencer marketing, follower count, social media engagement, Instagram, sponsored content, inverted U-shaped relationship, content personalization, brand familiarity, eye tracking, influencer selection

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review