The Influencer Marketing Performance Report 2026 (Influencer Strategists)

Industry survey

Publisher: Influencer Strategists
Evidence:: Self-reported behaviour
Vendor interest:: Moderate
Sample:: Survey of 41 senior influencer marketing practitioners; sample skewed toward agencies and consultants (63% combined), with minimal brand-side representation (2%).
Methodology: Disclosed
Geography: Global
Published: 4 May 2026

Summary:

This report on influencer marketing was published by Influencer Strategists and co-authored with a Boston Consulting Group partner.

It explores how influencer marketing teams say they target people, choose creators, and measure results.

Influencer Strategists is a private publication and community for senior creator and influencer marketing leaders, so it has a clear industry angle. BCG also has a commercial consulting angle, and the report judges results against BCG’s own “precision influencer marketing” approach.

The study used a survey of 41 senior influencer marketing practitioners, then cross-tabbed answers person by person to compare what each respondent claimed with what they said they actually do. The sample leaned heavily toward agencies and consultants, with very little brand-side representation.

TL;DR:

• Only 3% said the industry targets consumers with high precision
• 44% called it immature
• 15% said it is basically guessing.

When campaigns underperform, 30% blamed picking the wrong influencer, but only 6% blamed targeting the wrong audience and 3% blamed lack of consumer research.

The workflow data points in the same direction.

94% use engagement rate when choosing influencers, 88% use audience demographics, and 81% use past campaign performance. Only 25% use social listening data on what target consumers actually talk about.

Even though 72% said they use “consumer tribe alignment” in influencer selection, the report says most of that likely means demographic matching, not deeper consumer understanding.

Note that this is a small preliminary survey of 41 people, and the report itself says the findings are directional, not statistically generalisable.

Many of the strongest-sounding cross-tabs are based on very small subgroups. The sample is heavily skewed toward agencies and consultants, with minimal brand-side input. The data is self-reported, so confidence and capability may be overstated.

Influencer briefs only include structured keyword strategy for both social and AI/LLM discoverability 13% of the time; most either provide only social search keywords or just general hashtags

Keyword and search guidance included in influencer briefs (% of marketers)
Guidance type	Share (%)
Keyword strategy for social search (TikTok, Instagram)	34%
General hashtag guidance but no structured keyword strategy	34%
Keyword strategy for both social search and AI/LLM discoverability	13%
Leave keyword and caption decisions to the influencer	9%
Have not considered search optimisation in influencer briefs	9%

Only 24% of marketers say they are very confident in proving influencer ROI to the C-suite, while 62% are only somewhat confident and 14% are not confident at all

ROI confidence vs measurement: confidence in proving influencer ROI to the C-suite (%)
Confidence level	Share of marketers (%)
Very confident	24%
Somewhat confident but attribution remains imperfect	62%
Not confident or not confident at all	14%

Just 24% of marketers always use social listening before briefing influencers, while the largest group (33%) only uses it sometimes if time and budget allow

How often marketing teams use social listening data before briefing influencers (% of respondents)
Frequency	Share (%)
Always, it is a core part of our planning process	24%
Often, for major campaigns	15%
Sometimes, when time and budget allow	33%
Rarely	15%
Never	3%
Not applicable	9%

Open full graph

100% of marketers report using software for influencer discovery, but less than half have consumer tribe identification or social listening in their stack

Adoption of influencer marketing tools by funnel functions (%)
Technology capability	Adoption (%)
Influencer discovery and screening (Find influencers)	100%
Performance measurement and reporting (Track results)	84%
Campaign workflow management (Manage process)	81%
Audience authenticity / credibility verification (Filter fraud)	63%
Cross-platform analytics (TikTok, IG, YouTube) — Unified view	53%

Open full graph

Marketers who say they are very confident in proving influencer ROI always track engagement and sentiment, but only 14% track efficiency and none use all advanced measurement methods together

ROI confidence vs measurement: capabilities held by 'very confident' marketers (%)
Measurement capability	Share of 'very confident' marketers (%)
Track engagement rate	100%
Track positive / negative sentiment	100%
Have a standardised measurement framework	43%
Use marketing mix modelling	29%
Track EMV (earned media value) per working spend	14%
Have all three: EMV per spend + sentiment + marketing mix modelling	0%

Open full graph

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%

Open full graph

Nearly half of all marketers allocate nothing to consumer research in influencer marketing, and no one allocates more than 10%

Share of respondents by % of influencer budget allocated to consumer research and analytics before campaign execution
Budget allocation range	Share of respondents (%)
0% (no dedicated research budget)	48%
1-5%	35%
5-10%	19%
10-15%	0%
More than 15%	0%

Keyword and search strategy for influencer content ranks dead last in self-reported team capability, with a mean rank of 7.14 out of 8

Team capability by area, self-ranked from strongest to weakest (mean rank, 1-8)
Capability	Mean
#1 Influencer discovery and vetting	2.28
#2 Creative briefing	2.97
#3 Content review and quality control	3.86
#4 Consumer research and tribe identification	4.21
#5 Social listening and trend analysis	4.93

Open full graph

Most marketers check content for brand and quality alignment, but less than one in three review for resonance with the target tribe or for search optimisation

Content review criteria in the top 3, by what they check for (% of marketers)
Content review criteria	Share evaluated by (%)
Alignment with campaign brief (Brand)	81%
Visual quality and production value (Brand)	58%
Authenticity and natural tone (Brand / Consumer)	55%
Brand message accuracy (Brand)	52%
Compliance and disclosure requirements (Regulatory)	32%

Open full graph

Budget constraints are most often cited as the barrier to more precise influencer targeting

Biggest barrier preventing more precise consumer-targeted influencer marketing (% of respondents)
Barrier	Share (%)
Budget constraints	23%
Agency does not offer this capability	17%
Lack of consumer data / research capabilities	13%
Lack of appropriate technology / tools	13%
Organisational silos (IM disconnected from consumer insights)	13%
Leadership / C-suite does not prioritise this	13%
Skills and talent gap	7%

Open full graph

Less than half of marketers who say they have detailed, research-backed tribe profiles actually invest in research tools or use them for campaign decisions

Tribe-confident marketers capability stress test (% who actually do this)
Capability or behaviour	Share of tribe-confident marketers who actually do this (%)
Use social listening when selecting influencers	32%
Have tribe identification technology in your stack	42%
Have social listening technology in your stack	42%
Evaluate content for tribe resonance during review	37%
Track efficiency (EMV per working spend)	11%

Marketers are much more likely to track engagement rate than efficiency metrics, with engagement monitored by 91% but EMV per working spend tracked by only 9%

Share of marketers tracking each influencer campaign KPI (%)
KPI	Tracked by (%)
Engagement rate (likes, comments, shares) — How many people interacted	91%
Impressions / reach (How many people saw it)	84%
Click-through rate (How many people clicked)	78%
Sales / revenue attribution (Whether people bought)	72%
Customer acquisition cost (CAC) — What each customer cost	72%

Open full graph

97% of marketers say influencer marketing targeting is inconsistent, immature, or essentially guessing; only 3% say it is very mature with high precision

How marketers rate the influencer marketing industry's targeting maturity (% of respondents)
Industry targeting maturity	Share (%)
Very mature, targets consumers with high precision	3%
Somewhat mature, pockets of sophistication	44%
Immature, most campaigns lack structured targeting	29%
Very immature, essentially guessing	15%
Unsure	9%

30% of marketers say wrong influencer selection is the main reason campaigns fail, but only 6% blame targeting and 3% blame lack of consumer research

Top reason influencer campaigns underperform
Reason	Share (%)
Wrong influencer selection	30%
Poor creative / content quality	21%
Unclear campaign objectives	21%
Poor measurement / inability to prove impact	12%
Targeting the wrong consumer audience	6%
Insufficient budget / media amplification	6%
Lack of consumer research before campaign planning	3%

Open full graph

Marketers using social listening for influencer selection are over 4 times more likely to use advanced influencer marketing tactics

Influencer marketing capabilities: social listening (% of marketers)
Capability	Marketers who use social listening (%)	Marketers who do not use social listening (%)
Report detailed tribe understanding	75%	38%
Have tribe identification technology	88%	21%
Evaluate content for tribe resonance	63%	17%
Track EMV per working spend	25%	4%

Just over half of marketers say they have detailed, research-backed consumer tribe profiles, while a third have only a general understanding and 11% rely solely on audience data or tags

How well organisations understand consumer tribes for influencer campaigns (% of respondents)
Response	Share (%)
We have detailed, research-backed tribe profiles that inform every campaign	51%
We have a general understanding but no formal tribe mapping	32%
We rely on influencer audience data or paid media audience tags	11%
We don't have a structured approach to consumer targeting	0%
Unsure	5%

The Influencer Marketing Performance Report 2026 (Influencer Strategists)

Summary:

Cards from this research