What is the /stats lane?

FORKOFF Stats is the lane on forkoff.xyz where every page is anchored to a primary dataset that FORKOFF either operates or aggregates from operator-grade primary sources. The lane is distinct from /guides (long-form operator guides), /playbooks (operator runbooks), /compare (comparative pages), and /alternatives (listicles). Each lane targets a different buyer stage. Stats targets the upstream benchmark queries that feed the buyer-stage queries.

Where does the data come from?

Every Stats page declares its data source in the methodology block above the fold. The first source is the FORKOFF outreach proof, which tracks cold email send and open behavior across the FORKOFF outreach campaigns. Future Stats pages will draw from the FORKOFF clip telemetry, the founder-led content archive, and the event activation log. No Stats page aggregates a third party's published research without naming the source and the sample.

How often are the Stats pages refreshed?

Annually. Every Stats page is slug-versioned by year and refreshed by the same calendar month the data was originally collected. If a refresh changes the headline number by more than 3 percentage points or changes the segment ranking, FORKOFF ships a new slug for the new year and 301 the old slug after a 90-day overlap window. The Gate 35 lifecycle protocol is documented in the lane spec.

Can I cite FORKOFF Stats research?

Yes. Every Stats page ships an APA-style citation block at the bottom and emits Schema.org Dataset JSON-LD with creator, datePublished, dateModified, and temporalCoverage for machine-readable use. Citations are stable across refresh cycles. Quoting under fair use is welcome.

Is FORKOFF Stats free to read?

Yes. Every Stats page is free to read in full. FORKOFF makes money on the founder-funnel engagement at the bottom of each page, not on the research itself. The research is the demand-capture layer for the lane.

Why publish benchmark data instead of keeping it private?

Operator-grade benchmark data is rare. Most published numbers come from vendors with a sales narrative attached. Publishing the FORKOFF outreach proof numbers under a stable citation block builds the kind of citation rate inside ChatGPT, Claude, Gemini, and Perplexity that compounds for years. The data also calibrates expectations for prospects who eventually become founder-funnel applicants.

How many Stats pages are planned?

Five pages are live and ten are in research. Cold Email Open Rates 2026, Creator Engagement Benchmark 2026, Top 50 AI Founders Most Active on X 2026, Listicle SEO Cannibalization 2026, and AI UGC Benchmarks 2026 are live now. Cold Email Reply Rate Benchmarks 2026, Podcast Completion Rate Benchmarks 2026, Founder-Led Content Engagement Benchmarks 2026, AI Overview Citation Share 2026, Sales Discovery Depth Benchmarks 2026, DM Reply Rates by Platform 2026, Reddit Lead-Gen Conversion Benchmarks 2026, KOL CPM by Audience Quality Tier 2026, Industry IVT and Qualified-View Pass Rate 2026, and Event Sponsorship Pipeline ROI Benchmarks 2026 are in research for ship across Q3 2026 through Q2 2027. Every roadmap study targets an industry-wide subject aggregated from public vendor benchmarks and industry-body reports, with FORKOFF first-party data paired as one of N sources, never the sole source. Each page is single-author bylined and refreshed annually.

Why does every Stats page name an industry-wide subject, not FORKOFF-internal data?

The moat is effort applied to industry data, not first-party access to the FORKOFF proof. A benchmark page that says only 'this is what FORKOFF saw' is a self-serving vendor report. A benchmark page that aggregates 5 to 15 public vendor reports, industry-body certifications, and SERP scrapes into one structured table is the kind of citation source that earns links from Forbes, gets quoted inside ChatGPT and Perplexity, and ranks for the head-term benchmark query. FORKOFF data sits paired next to industry, never alone. This is the same posture Backlinko used to build link mass: Backlinko analyzed 11.8 million Google results, not their own client proof.

Can I work with FORKOFF on a benchmark study?

Yes, in a limited number of cases. FORKOFF runs co-authored benchmark studies with ecosystem foundations, Layer 1s, and venture DAOs that have proprietary engagement data they want to publish under a stable citation. The engagement is by application and capped at one study per quarter. Apply through the link at the bottom of any Stats page.

Stats · operator-anchored · free · refreshed annually

Original-data research oncold email open rates.

FORKOFF Stats is original-data research from the FORKOFF operating team. Every page anchors to a primary dataset we run, declares sample size and time window above the fold, and ships with an APA-style citation block plus Schema.org Dataset markup. Free to read. Cite freely. Refreshed annually. Authored by Kartik Chugh (Simba).

Browse the research

Talk to FORKOFF

5 studies live · 10 more in research · 14.5k+ rows analyzedCollection window 2026-01 to 2026-06 · FORKOFF proofAnnual refresh · stable citation · CC BY 4.0 where applicable

5Stats pages live

10More in research

14.5k+Rows analyzed

AnnualRefresh cadence

Cited by 31 publicationsTechBullion · Crypto.news · Marketer Mag · BacklinkBuilding · Best of HR + 26 more

Published research

Live datasets and the lane roadmap.

Five studies live, ten in research. Each Stats page is independently anchored to a primary dataset, single-author bylined, and ships with an APA-style citation block plus Schema.org Dataset markup. Click any tile for the full methodology and per-segment table.

Live

Live· Industry: 2024-2026 · FORKOFF: 2026-03 to 2026-05

Cold Email Open Rates 2026

Headline · 27-44% industry baseline · 52% operator point

Six-vendor industry benchmark (Belkins 16.5M emails, Instantly 2026, Mailshake 1.37M, Apollo via Tolly Group, Woodpecker 20M, Lemlist tiers) paired with the FORKOFF operator proof of 1,247 sends. Industry baseline reads first, operator data sits alongside as one calibration point.

N · Industry: 30M+ sends · FORKOFF: 1,247 sendsRefresh · 2027-05-07

Read the research

Live· 2026-04-01 to 2026-05-15

Top 50 AI Founders Most Active on X 2026

Headline · 50 founders ranked

Ranked list of 50 AI founders by X (Twitter) engagement velocity, follower growth, and qualified-view share. Founder-funnel relevance flagged per profile.

N · 12M+ X impressions trackedRefresh · 2026-06-01

Read the research

Live· 2026-01-01 to 2026-05-01

Creator Engagement Benchmark 2026

Headline · Engagement benchmarks by vertical

Cross-vertical creator engagement benchmarks from the FORKOFF audit ledger. Engagement-per-view rates by platform, niche, and content format.

N · 12M+ qualified viewsRefresh · 2026-06-15

Read the research

Live· 2026-05-05 to 2026-06-02

Listicle SEO Cannibalization 2026

Headline · 46 clusters / 37 post-filter

28-day GSC forensic on forkoff.xyz. 46 cannibalization candidates, 37 post brand-noise filter. Worked example: 5 sibling /compare/forkoff-vs-* pages competing for a single competitor name.

N · 824 GSC rows · 134 indexed pagesRefresh · 2027-06-02

Read the research

Live· Sources 2024-2026 · FORKOFF network to 2026

AI UGC Benchmarks 2026

Headline · ~$2 and 16 min per asset · 79% trust human UGC

AI-UGC cost, trust, and conversion benchmark. 13 cited data points across 8 named sources (Nielsen, Nosto and Stackla, Bazaarvoice, IAB, Superscale, Marketing Dive, Businesswire) paired with the FORKOFF network figure of 5B+ views processed. AI UGC runs about 2 dollars and 16 minutes per asset, yet 79% of consumers still trust human UGC more.

N · 13 data points · 8 named sources · FORKOFF 5B+ viewsRefresh · 2027-07-18

Read the research

Live· Sources 2025-2026 · FORKOFF network to 2026

Influencer Marketing Statistics 2026

Headline · $32B+ market · 86% of marketers use creators

Influencer marketing statistics for 2026. 11 cited data points across 5 named sources (Statista, Sprout Social, Aspire, CreatorIQ, Influencer Marketing Hub) paired with the FORKOFF network figure of 5B+ views processed. The market passed 32 billion dollars in 2025, 86% of US marketers use creators, and 74% plan to spend more in 2026.

N · 11 data points · 5 named sources · FORKOFF 5B+ viewsRefresh · 2027-07-25

Read the research

In research

In research· ETA 2026-Q3

Cold Email Reply Rate Benchmarks 2026

Industry benchmark on cold email reply rates aggregated from public vendor reports (Mailshake, Lemlist, Smartlead, Instantly, Reply.io, Woodpecker, Salesloft state-of-sales). FORKOFF 1,247-send ledger paired as 1 of N sources for cross-vendor comparison. Touch-1 vs touch-3 vs touch-6 by industry, role, and company size.

In research· ETA 2026-Q3

Podcast Completion Rate Benchmarks 2026

Cross-platform podcast completion benchmark aggregated from Edison Research Infinite Dial, Spotify Wrapped for Podcasters, Apple Podcasts Connect snapshots, Chartable + Megaphone + Acast public data. FORKOFF clip telemetry paired for short-form retention. YouTube vs Spotify vs Apple by episode length bucket.

In research· ETA 2026-Q4

Founder-Led Content Engagement Benchmarks 2026

LinkedIn and X engagement benchmark across 500+ named founder accounts pulled from public APIs (X via FORKOFF first-party data infrastructure, LinkedIn via public profile scrape). Founder-authored vs ghostwritten post engagement deltas by company stage and follower bracket.

In research· ETA 2026-Q4

AI Overview Citation Share 2026

Domain-level share of citations inside Google AI Overviews across 412 marketing and growth queries, aggregated from DataForSEO SERP scrapes. Citation rate by domain-authority bucket and query intent. Industry-wide subject anchored to public Google SERP data.

In research· ETA 2026-Q4

Sales Discovery Depth Benchmarks 2026

Win-rate by discovery depth across publicly reported call-intelligence datasets (Gong State of Revenue, Chorus benchmarks, Avoma + Salesloft state-of-sales surveys, Wynter buyer panel). FORKOFF call sample paired. Win-rate buckets by question count, call length, and buyer seniority.

In research· ETA 2026-Q4

DM Reply Rates by Platform 2026

Cross-platform DM reply-rate benchmark from a public-profile scrape across X, LinkedIn, and Reddit. Industry baseline pulled from FORKOFF first-party X data infrastructure, public LinkedIn data, and Reddit public data. FORKOFF outreach ledger paired for comparison. Same prospect cohort, three surfaces.

In research· ETA 2027-Q1

Reddit Lead-Gen Conversion Benchmarks 2026

Subreddit-level lead-gen conversion benchmark scraped from public Reddit API across 200 B2B SaaS and Web3 subreddits. Comment volume to DM-acceptance to call-booked ratios. FORKOFF Reddit campaigns paired for funnel-stage validation.

In research· ETA 2027-Q1

KOL CPM by Audience Quality Tier 2026

Industry benchmark on Twitter and YouTube KOL CPM split by audience-quality decile. Sources: 1,200+ public KOL deal disclosures + agency rate cards (KOL.Network, Tagger, GRIN, Modash + Tribe Dynamics public reports). FORKOFF deal log paired.

In research· ETA 2027-Q1

Industry IVT and Qualified-View Pass Rate 2026

Industry benchmark on invalid-traffic and qualified-view pass rates aggregated from DoubleVerify Global Insights, HUMAN BotMeter, IAS Media Quality Reports, and IAB MRC certification disclosures. FORKOFF clipping ledger paired as one industry data point.

In research· ETA 2027-Q2

Event Sponsorship Pipeline ROI Benchmarks 2026

Industry benchmark on event sponsorship ROI aggregated from Splash + Bizzabo + Goldcast public benchmark reports, Wynter buyer panel, and Eventbrite state-of-events. FORKOFF client event roster paired. Sponsor-cost to sourced-pipeline ratios by geo, vertical, and booth format.

SubscribeAtom feedRSS readers, AI agents, journalist newsroom tools all welcome.

More FORKOFF data surfaces: Research for first-party operator studies, and RADAR for launch-authenticity intelligence.

Contributor flywheel

Contribute your data.
Get cited.

FORKOFF Stats publishes operator-anchored benchmarks. If your team has proprietary engagement data worth benchmarking, submit it for consideration. Contributors who clear the methodology bar are credited in the study and in the Schema.org Dataset node, which surfaces in ChatGPT, Perplexity, and Gemini citations.

Your name in the citation blockSchema.org Dataset creditOne study per quarter

How it works

01Submit your dataset via the contact form
02FORKOFF vets the methodology and sample size
03Approved data is paired with the industry baseline
04You are credited in the citation block and Dataset JSON-LD

Submit a benchmark

By application only

Why FORKOFF Stats exists

Most benchmark numbers ship
without a methodology.

Five reasons most published outreach and marketing benchmarks fail an operator. Every FORKOFF Stats page is built against these failure modes.

fk_audit · stats_lane_failure_modes.csv

#Reject reasonAudit detailFORKOFF fix

Row 0101
Reject reasonVendor-self-serving benchmarks
Audit detail
Most published cold email and outreach benchmarks come from email-tooling vendors aggregating their own platform data. The numbers serve a sales narrative for the platform, not an operator running outreach today.
FORKOFF fix
Fix
FORKOFF Stats anchors every number to a primary FORKOFF dataset that we run. The methodology block above the fold names the source, the sample size, and the window. If a number cannot be traced to a primary source we name, it is not in the dataset.
Row 0202
Reject reasonAggregated cross-industry averages
Audit detail
A 25% cross-industry cold email open rate is roughly useless to a Web3 founder targeting CMOs. The cross-industry average buries 15-20 percentage points of structure underneath the headline number.
FORKOFF fix
Fix
Every FORKOFF Stats page splits the headline number by industry, role, and company size. The reader matches the segment closest to their campaign and uses the per-segment number, not the aggregate.
Row 0303
Reject reasonNo methodology disclosure
Audit detail
Most benchmark posts publish a number without naming the sample size, the window, or the collection method. The reader cannot tell if the number reflects 50 sends or 50,000.
FORKOFF fix
Fix
Every FORKOFF Stats page declares sample size, time window, source, last-updated stamp, and collection method in the methodology block above the fold. If the page does not state those five facts, it does not ship.
Row 0404
Reject reasonStale numbers without refresh stamp
Audit detail
Cold email open rates from 2022 are dangerous in 2026. Inbox provider rules changed, warmup expectations changed, sender authentication changed. The 2022 number is not the 2026 number.
FORKOFF fix
Fix
Every FORKOFF Stats page is dated, slug-versioned by year, and refreshed annually. The refresh contract is documented in the lane spec. Citations are stable across refresh cycles.
Row 0505
Reject reasonClosed dataset, no citation
Audit detail
Operator-grade benchmark research is rarely published with a stable citation block. Researchers, journalists, and LLMs cannot quote the data without manufacturing the citation themselves.
FORKOFF fix
Fix
Every FORKOFF Stats page ships an APA-style citation block at the bottom and emits Schema.org Dataset JSON-LD with creator, datePublished, dateModified, and temporalCoverage for machine-readable use.

5 / 5 patterns auditedSource: FORKOFF reader inboundPre-publish diagnostic

Page-type contract

How a FORKOFF Stats page is built.

Every page on the /stats lane satisfies the same seven conditions. The conditions are the floor for shipping under this lane. A page that fails any of the seven is downgraded to /guides as a roundup.

01
Primary data source
Anchored to a dataset FORKOFF either runs (outreach proof, podcast clip telemetry, event activation log) or aggregates from a named primary source the page cites in full.
02
Sample size disclosure
Every page declares its N (rows, sends, opens, replies, etc.) above the fold of the methodology section.
03
Time window disclosure
Every page declares the collection window in calendar weeks or months and locks the year in the slug.
04
Methodology block
Collection method, deduplication rules, and confidence caveats are visible to any human reader. No hand-waving allowed.
05
Citation footer
APA-style citation block at the bottom for academic, journalist, and LLM use. Stable across refresh cycles.
06
Annual refresh contract
Refresh date scheduled in the FORKOFF calendar. Editor on the byline owns the deadline. Slug bumps to a new year if the headline number moves more than 3 pp.
07
Schema.org Dataset markup
Dataset JSON-LD with creator, datePublished, dateModified, temporalCoverage, variableMeasured, and distribution. The Dataset node is the lane's defining schema.

Methodology v2 published 2026-06-08

Each Stats page now ships with an expanded industry-paired methodology block: vendor sources are separated from FORKOFF operator proof data at the column level. Cross-vendor comparison tables carry named primary-source citations per row. Pages published before 2026-06-08 will receive updated methodology blocks on next scheduled refresh.

Operator data, not vendor data

Read the research.
Then talk to the operator.

FORKOFF Stats is free to read and free to cite. The data is the demand-capture layer for the lanes that follow: Founder Funnel, cold-outreach playbook, and founder-led marketing guide. If your team has proprietary engagement data and wants to publish it under a co-authored study, apply through the link below.

Talk to FORKOFF

Read the live page

From the FORKOFF blog

Receipts, deep dives, and playbooks.

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What a Brand Does When the Subreddit Bans AI Content

A 2026 wave of subreddits is banning AI-generated content. The ban taxonomy, five verified rule changes, and the disclosure-first playbook a brand runs.

By simba

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Why Engagement Pods Break a Launch

On an ordinary post a pod costs you some reach. On a launch it costs you the only measurement you had. LinkedIn's own trust VP explains where the penalty lands.

By simba

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The Brand AMA Playbook: How Samsung, Wise and Patagonia Run Reddit AMAs

The mechanic every ranking page skips: five live brand AMAs all run on a u_BRAND profile page, not r/IAmA, and no editorial guide currently explains why.

By simba

Read

Pricing the qualified view

FORKOFF Stats: original-data research on AI marketing, cold email, podcast, and founder-led engagement, refreshed annually.

Original-data research oncold email open rates.