Greg Portnoy works on B2B partner revenue, writing and speaking about how companies can build partner programs, measure their financial impact, and use AI agents to manage the work.
Greg Portnoy is most useful for practical B2B partner program design, financial measurement, and AI agent operations.
Best for
B2B SaaS companies selling partner management, partner analytics, or agentic operations to partner leaders.
Not for
Consumer lifestyle, family, or broad awareness brands seeking standard creator sponsorship packages.
Key takeaways
Partner programs get too complicated because companies copy bigger competitors.
Partner teams lose budget because they cannot produce a P&L.
Partner Market Fit is the gate before spending on process, tooling, or people.
Check first: Confirm whether they have a media kit, rate card, or sponsorship policy before contacting them.
Main ideas
Partner programs get too complicated because companies copy bigger competitors · Partner teams lose budget because they cannot produce a P&L · Partner Market Fit is the gate before spending on process, tooling, or people
Greg Portnoy writes and speaks about building B2B partner programs that produce revenue companies can measure and fund.
His posts connect practical program choices—such as when to add partners, how to simplify program rules, and what to measure—to a broader case for treating partnerships as a serious go-to-market channel.
He also shares updates about EULER and its AI tools for partner teams.
Follow his work for concrete advice on partner-program design, financial reporting, and the role of AI agents in making partner operations more manageable.
The supplied material does not establish whether he has signature books, shows, or earlier work beyond these posts and EULER; targeted research into those areas would help complete a name-search profile.
Portnoy turns broad claims about partnerships into choices a team can examine.
In one post, he uses SpaceX’s partner-network launch to illustrate recruiting before launch, preparing certification in advance, and keeping the program to two clear tracks.
In another, he gives a specific audit for complexity: keep a requirement, benefit, or tier only if it adds value, encourages useful behavior, or makes the program easier to understand.
His financial posts make the case measurable, listing partner revenue and program costs before naming cost per dollar of partner-sourced revenue as a metric to compare with blended CAC.
A recurring thread is that teams should prove partner-market fit and build reliable data before scaling.
Not every post is a how-to: company milestones, event travel, and a family story show a more personal and promotional side of the feed.
The strongest reason to follow is the combination of operational checklists and an executive-facing argument for why partnerships deserve investment.
Greg Portnoy's posts circle one argument: partner revenue is a financial channel that has to be modeled, simplified, and measured like sales or marketing, and AI agents are now the way to produce the operating data that makes it forecastable.
Read more
He is blunt about where partner teams fail — over-complicated programs copied from larger competitors, and an inability to show a cost per dollar of partner-sourced revenue — and he builds each argument from a named example: a specific company launch, a conversation with an executive, or numbers from his own company, EULER. His stated priority is giving partner leaders the vocabulary and evidence to win budget in a board meeting, and he sources most of his material from conference rooms and small operator dinners rather than reading.
Partner programs get too complicated because companies copy bigger competitors
Portnoy argues that partner leaders add tiers, benefits, and partner types because a competitor has them, not because their own volume or mix of partner motions requires the structure.
Read more
Complexity should be earned: bigger companies layered it on only after scale or genuinely different partner motions forced them to.
His test is an audit of every requirement, benefit, and tier against four questions — does it add value, does it drive the behavior you want, does it make you easier to partner with, and does it make the program easier to understand?
If not, cut it.
He also points out that every benefit promised inside a tier is a delivery obligation, and unkept promises become a repair job roughly a year later, because partners remember what was offered.
His repeated closing line is that complexity is something a program should grow into, not something you install and hope to grow toward.
He recounts a conversation with a Global VP of Partnerships whose CEO wanted tiers and complexity added because a competitor had them — in Portnoy's framing, solving for challenges the company did not have, for partners who had not asked. A related post on EULER's own audience contrasts that with SpaceX Super Intelligence's partner network, which he describes as recruiting 130+ partners through an early-access phase before the public launch, running a Forward Deployed Engineer accreditation program across 30+ organizations on day one, and keeping just two tracks — Transformation Partners for enterprise-wide deployments and Marketplace Partners for integrations.
Partner teams lose budget because they cannot produce a P&L
Portnoy's central budget argument is that partnership teams are weak at financial reporting and that this, not performance, is why the channel gets starved.
Read more
He lays out a concrete model: revenue lines for partner-sourced revenue, partner-influenced revenue, and resale revenue net of rebates; cost lines for events and travel, partner team headcount, commissions and rebates, MDF and co-marketing spend, and tooling; and then the number he says ends the argument, cost per dollar of partner-sourced revenue, put next to the company's blended CAC.
His claim is that asking most partner leaders what a dollar of partner-sourced revenue costs to generate produces a blank stare, and that no CFO funds a channel they cannot model.
He frames the wider problem as a data gap: executives told him they believe partnerships can work but hesitate because they do not know what good looks like, which he attributes to missing ROI, framework, performance, and benchmarking data across the function.
After asking dozens of CEOs, CROs, and CMOs at the GTM2026 conference in New York what would get them to invest more in partnerships, Portnoy reports a consistent answer — that partnerships can work, but leadership does not know what good looks like. His recommended metrics for partner leaders are win rate, sales cycle, ACV, and cost per dollar sourced, the same numbers he says other go-to-market leaders already bring to board meetings.
Partner Market Fit is the gate before spending on process, tooling, or people
Portnoy sets a readiness test rather than a growth target.
Read more
Partner Market Fit, in his account, is the condition that makes investment in process, tooling, and eventually people sensible, and it shows up as evidence rather than intention: complementary capabilities, partner-sourced deals arriving without heavy pushing, shorter sales cycles and higher win rates together, inbound high-value partners, existing mutual customers, ROI-positive partnerships, and leadership asking how to get many more of the same partners. The counter-argument is deliberately unflattering — if most of the signals are missing, the company does not need more partners, it needs a harder look at the ones it already has.
His 13-sign checklist includes items such as the partnership increasing customer engagement and retention, partners' competitors showing interest in partnering with you, and the better-together story rolling off the tongue organically. He describes those signals as the sign to start investing rather than a reason to keep recruiting.
AI agents are the current answer to predictable partner revenue
Portnoy's most recent framing connects the financial-modeling argument to AI: partner-led deals already carry better unit economics — higher win rates, lower CAC, better retention — but companies never build the channel seriously because no CFO funds something they cannot model, and agents change that by taking over work that used to consume a partner team's week while producing the operational data that makes the channel forecastable.
Read more
He uses EULER's own product metrics as the illustration, which are company-reported figures rather than independently verified numbers: the PAM AI Agent handling over 48,000 conversations with more than 6,500 partners and saving over 1,300 hours of team time, POPS Sub-Agents that run a described routine on a schedule, and shipping work that brings AWS Marketplace private offers and ACE deals into the same system as the rest of a partner program.
At Pavilion's GTM conference he notes that a year earlier AI was just entering the conversation and that this year's talk is an agentic playbook for making partner revenue predictable — a visible shift in emphasis across his own speaking slots rather than a one-off post.
The emphasis moved from diagnosing the data gap and building the P&L to arguing that agents generate the forecast data as a byproduct of running daily partner operations.
He gathers his evidence in rooms with operators, not from reading
A stated working priority is that the useful information sits with people changing the industry rather than with people publishing about it.
Read more
Portnoy says he learns more in two days of conference and dinner rooms than in two months of reading online, and his posts consistently convert those conversations into arguments — the executive hesitation about partnerships, the copycat tier story, and the CFO-funding premise all come from direct questioning of CEOs, CROs, CMOs, and partner leaders. He runs a recurring small-group format, the EULER Partner Revenue Executive Dinners, described as a small table of senior operators in a private space comparing notes on the same problems.
Posts mention hosting an AI roundtable at the Partnership Leaders Catalyst Summit in Seattle, speaking at Pavilion's GTM conference in New York, and hosting Zapier's Executive AI Workshop, with an open invitation to message him about a seat at a dinner.
He builds EULER in public, mixing the operating story with the same arguments
A distinct part of the record is first-person company updates that read as operating milestones: taking a year to reach the first $1M in revenue and then posting a first $1M quarter, closing a $4.3M round led by Channel Equity Partners, describing bootstrapping to profitability before raising, and publishing numbered hiring lists with a careers link.
Read more
These posts reuse the partner-revenue arguments and end with a product call to action, so reading him means reading a vendor founder whose public voice and company promotion are entangled. The figures are his own claims and posted headcount numbers vary between updates.
One update reports hiring nine people to reach 49 team members, while another posted around the same period says the company went from 12 people a year ago to 54 today — figures that do not match and are not reconciled in the posts.
Milestone and hiring posts are a minority format alongside the partner-advice posts, and they are plainly promotional in a way the advice posts are not.
Answers: What does a mature partner program design look like at launch?
Read more
Start here because it gives a named example and three concrete decisions a reader can compare against their own program.
Greg Portnoy breaks down SpaceX's partner network launch into three choices: recruiting 130+ partners before the public launch, having a Forward Deployed Engineer accreditation program with 30+ organizations already training engineers on day one, and keeping only two tracks — Transformation Partners for enterprise-wide deployments and Marketplace Partners for integrations — instead of bronze, silver, and gold tiers.
The post contrasts this with programs that announce first and recruit later, treat certification as a second-year problem, or copy complex tier structures.
The summary line is 'Scale down to scale up.'
For brands planning a campaign
A campaign about partner program launch readiness or simplification can use this as the anchor example. The three choices map to content angles: pre-launch recruitment, certification as a prerequisite, and simple partner tracks.
Answers: Why do partner programs become overcomplicated, and how do you audit one?
Read more
Start here for the diagnostic question and a practical audit rule.
Greg Portnoy argues companies copy tiered programs from much larger competitors and install complexity before they have the volume or motion differences that justified it.
The post includes a conversation with a Global VP of Partnerships whose CEO wanted tiers because a competitor had them.
The audit test is direct: every requirement, benefit, and tier must add value, incentivize key behavior, make the company easier to partner with, or make the program easier to understand.
If not, throw it out.
The post ends with 'Complexity is something your program should grow into.
Not something you install and hope to grow toward.'
For brands planning a campaign
Use for a campaign around partner program simplification or program audits. The post supplies a concrete audit checklist and a copycat-competitor failure story.
Answers: How do you make partner revenue CFO-fundable?
Read more
Start here because it gives the exact model and metric to build.
Greg Portnoy says the reason partner programs do not get more budget is that partnership teams are weak at financial reporting.
The post lists revenue lines — partner-sourced revenue, partner-influenced revenue, and resale revenue net of rebates — and cost lines — events and travel, partner team headcount, commissions and rebates, MDF and co-marketing spend, and tooling.
It then names the decisive metric: cost per dollar of partner-sourced revenue compared with the company's blended CAC.
The argument is that no CFO funds a channel they cannot model.
For brands planning a campaign
A brief about making partner revenue predictable should lead with this financial model. The campaign can use the P&L structure as a practical resource and position Greg Portnoy around the line that the language of business is finance.
Answers: What data do executives want before funding partnerships?
Read more
Start here for the demand-side view from buyers of partner programs.
After asking dozens of CEOs, CROs, and CMOs at GTM2026 what would make them invest more in partnerships, Greg Portnoy reports a consistent answer: they believe partnerships can work but lack ROI data, framework data, performance data, and benchmarking data.
The post calls this the biggest gap and asks partnership leaders to track win rate, sales cycle, ACV, and cost per dollar sourced — the same numbers other GTM leaders bring to board meetings.
It frames the issue as a collective data problem, not an individual performance problem.
For brands planning a campaign
Use as audience research for a data and benchmarking campaign. The post gives the exact executive objection and the metrics that address it.
Answers: When should a company scale its partner program?
Read more
Start here for a diagnostic checklist a reader can apply immediately.
Greg Portnoy lists 13 signals that a company is ready to scale partner investments, including complementary capabilities, inbound partner-sourced deals, higher customer engagement and retention, shorter sales cycles, mutual customers, ROI-positive partnerships, and leadership asking how to get 10x more partners.
The post names the condition 'Partner Market Fit' and says it is the prerequisite for investing in process, tooling, and people.
If most boxes are unchecked, the advice is to look harder at existing partners rather than add more.
For brands planning a campaign
Campaign angle: partner program readiness assessment. The 13 signs can become a self-assessment resource, webinar framework, or lead magnet.
Answers: How do AI agents connect to partner revenue predictability?
Read more
Start here for the shortest statement of the agentic thesis.
Speaking at Pavilion's GTM Conference, Greg Portnoy argues that partner-led deals have the best unit economics in B2B — higher win rates, lower CAC, and better retention — but most companies never build the channel seriously because no CFO funds something they cannot model.
Agents change that, in this account, by handling work that used to consume a partner team's week and by producing the operational data that makes the channel forecastable.
The post promises a walkthrough of what it takes to make that real and what it returns.
For brands planning a campaign
Use as the bridge between partner data and AI agents. A campaign can pair this with the P&L post to show the full argument: model the channel, then use agents to generate the operating data.
Answers: What is the operating company behind the posts, and what does its AI agent actually do?
Read more
Start here for concrete product and traction context.
Greg Portnoy reports that EULER hit its first $1M quarter, closed a $4.3M funding round led by Channel Equity Partners, and grew to 49 team members.
The post also gives specific product numbers: the PAM AI Agent had over 48,000 conversations with over 6,500 partners, saving over 1,300 hours of team time; POPS Sub-Agents run described routines on a schedule; and Hyperscaler brings AWS Marketplace private offers and ACE deals into the same system as the rest of a partner program.
The post is a company milestone update, so the figures are company-reported.
For brands planning a campaign
An agentic partner management campaign can use the PAM AI Agent conversation and time-savings figures as supporting proof points, with the caveat that they are company-reported. The quarterly update also shows the product shipped features that connect to the predictability argument.
Financial modeling as the argument for partner budget3
Repeated post architecture3
Partner programs are over-built by copying bigger competitors2
Building EULER in public2
Partner Market Fit as a readiness gate before scaling1
Occasional personal and family posts1
Partner programs are over-built by copying bigger competitors
A recurring argument: partner programs accumulate tiers, benefits, and partner types because leaders copy programs that earned that complexity at a much larger scale.
Read more
Portnoy describes a Global VP of Partnerships whose CEO wanted tiers and complexity because a competitor had them, and calls it solving for challenges they did not have.
The claim is that every benefit promised in a tier creates a delivery obligation and a repair job twelve months later, so programs should audit each requirement, benefit, and tier against whether it adds value or makes the company easier to partner with.
The SpaceX Super Intelligence launch is used as the counter-example: two tracks, Transformation Partners for enterprise-wide deployments and Marketplace Partners for integrations, no bronze, silver, or gold layers, and 130+ partners recruited through an early-access phase before the public launch, with a Forward Deployed Engineer accreditation program running on day one across 30+ organizations.
Contrast framing: states the common industry behavior, then the specific example that did the opposite, then the takeaway.
For brands planning a campaign
A strong angle for partner-program tooling, PRM, and channel services vendors is an audit campaign rather than a more-partners campaign. The concrete hooks are tier audits, promise-delivery checks, and simple two-track structures, which read as practical advice instead of generic partner marketing.
Financial modeling as the argument for partner budget
Portnoy argues partner teams lose budget because they cannot produce a P&L.
Read more
The pitch is specific: list partner-sourced revenue, partner-influenced revenue, and resale revenue net of rebates; list costs including events and travel, partner team headcount, commissions and rebates, MDF and co-marketing spend, and tooling; then report cost per dollar of partner-sourced revenue next to the company's blended CAC.
Portnoy says asking most partner leaders what a dollar of partner-sourced revenue costs produces a blank stare, and that no CFO funds a channel they cannot model.
A related post reports the same answer across dozens of CEO, CRO, and CMO conversations at GTM2026 in New York: executives believe partnerships can work but hesitate because they do not know what good looks like, which Portnoy frames as a data gap covering ROI, frameworks, performance, and benchmarks, and a call to track win rate, sales cycle, ACV, and cost per dollar sourced.
For brands planning a campaign
Finance-adjacent messaging lands here: CFO language, cost-per-dollar metrics, and benchmarking data are the terms Portnoy already uses. Analytics, attribution, PRM, and partner-revenue platforms have a natural fit in jointly produced benchmark or ROI research, and in content aimed at partner leaders who need to defend the channel in a board meeting.
Partner Market Fit as a readiness gate before scaling
Portnoy lays out thirteen signs that a company is ready to invest in partner process, tooling, and people, including complementary capabilities, partner-sourced deals arriving without heavy pushing, shorter sales cycles and higher win rates together, inbound high-value partners, existing mutual customers, ROI-positive partnerships, and leadership asking how to get ten times more of these partners.
Read more
The term used is Partner Market Fit, described as the prerequisite for a successful partner program and the sign to start investing. The counter-argument is direct: if most of the boxes are unchecked, the company does not need more partners, it needs a harder look at the ones it has.
For brands planning a campaign
Readiness assessment is a usable campaign format with this audience: self-scoring checklists, diagnostic workshops, and lead magnets built around a fit test. The message to avoid is recruiting volume, which runs against the stated position.
The most recent framing is that AI agents make partner revenue predictable by handling the work that used to consume a partner team's week and producing the operational data that makes the channel forecastable.
Read more
Portnoy's own numbers for the EULER PAM AI Agent are 48,000 conversations with over 6,500 partners, saving more than 1,300 hours of team time, alongside POPS Sub-Agents that run described routines on a schedule, and shipped features including Hyperscaler, Service Partners, Customer and Partner Surveys, AI Co-marketing Studio, and Crossbeam co-sell skills. A conference post shows the shift in emphasis: at Pavilion's GTM Conference a year earlier AI was just entering the conversation, and the current talk is about the agentic playbook for predictable partner revenue, built on the claim that partner-led deals already carry better unit economics through higher win rates, lower CAC, and better retention.
For brands planning a campaign
Generic AI content will not differentiate here.
The specific, defensible angle is agents producing forecastable partner data and taking over repetitive partner operations.
AI and agent vendors, and event organizers building partner-ops tracks, can co-present this playbook; the metric claims in these posts are Portnoy's own and should be attributed rather than repeated as verified fact.
Portnoy sources arguments from events and small-group conversation: dozens of CEO, CRO, and CMO interviews at GTM2026 in New York, an AI roundtable at the Partnership Leaders Catalyst Summit, Zapier's Executive AI Workshop, and the EULER Partner Revenue Executive Dinners described as small tables of top operators in private spaces comparing notes.
Read more
The stated reason for the travel is direct: more is learned in two days of these rooms than in two months of reading online, because the people changing the industry are at the tables rather than publishing about it.
For brands planning a campaign
Field research and dinner-series sponsorship fit the format Portnoy already runs.
A brand can attach to a benchmark survey, a roundtable series, or a private dinner where the output is a named research artifact rather than logo placement.
The value to the brand comes from the operator access, so sponsorship should be framed around the conversations and the resulting data.
A recurring post type covers company milestones as first-person updates: a first $1M quarter after taking a year to reach the first $1M total, a $4.3M funding round led by Channel Equity Partners, headcount moving from 12 to 54 people in a year with a stated intent to keep hiring, revenue up threefold, bootstrapping to profitability before raising, and a numbered list of ten open roles with a link to the careers page.
Read more
These posts mix the operating story with the same partner-revenue arguments found elsewhere, ending with a product call to action.
Company milestone posts are a minority format in this corpus and are plainly self-promotional in a way the partner-advice posts are not.
For brands planning a campaign
A brand working with Portnoy is working with a vendor founder whose content carries EULER recruiting and product links.
Co-marketing needs a genuine education or research component to fit; pure brand-awareness placement would sit oddly beside milestone and hiring posts.
This is also the clearest signal that Portnoy's public voice is bound up with the company being promoted.
The posts follow a consistent structure: a blunt claim, a numbered list or short labelled sections, a contrast between what most companies do and what a specific example did, a plain-language takeaway, the repeated closing line scale down to scale up, and often a call-to-action link.
Read more
Sentences are short and declarative, and the vocabulary stays operational rather than abstract.
For brands planning a campaign
Sponsored content that mirrors this structure, meaning numbered points, a concrete company example, and a practical takeaway, will read as native. Long narrative or high-concept creative formats will stand out against the surrounding work.
One supplied post steps entirely out of the partner-revenue subject: a first-person account of getting a reluctant four-year-old to school, describing how a stressful drop-off routine changed once the child's actual worry, a fear of being excused again for not listening and waiting, was addressed, and closing with the view that work wins and family wins deserve equal airtime.
Read more
This is not a commercial or partner-revenue topic; it appears once in the reviewed set.
For brands planning a campaign
The register here is personal and parenting-oriented, and it is a small part of the reviewed corpus, so it should not be treated as a content pillar for campaign planning. It does indicate that personal-story sponsorship angles are not off-brand, provided they are occasional rather than the main line.
Greg Portnoy's supplied posts most clearly connect him to EULER, a partner-management software business he describes in first-person plural and promotes through product pages, events, and hiring posts.
Read more
The posts also disclose EULER's $4.3M funding round led by Channel Equity Partners and several conference/event relationships, including Partnership Leaders Catalyst, Pavilion's GTM Conference, and Zapier's Executive AI Workshop. The posts do not state his ownership or employment title, so EULER is recorded as a disclosed business relationship with that unstated detail.
EULER
Disclosed partnership
EULER is the partner-management software business behind the PAM AI Agent, POPS Sub-Agents, Hyperscaler, and Partner Revenue Dinners that Portnoy writes about as 'we' and 'our team.' The posts link to EULER careers and product pages, but do not state whether Portnoy owns or is employed by the company.
Portnoy led a roundtable on Agentic Partner Management and hosted an EULER Partner Revenue Executive Dinner at Partnership Leaders' Catalyst events, including Seattle and the PL Catalyst Summit.
Greg Portnoy's posts read as a short course in treating partner revenue as a financial channel.
Read more
Start with the argument that partner teams lose budget because they cannot produce a P&L, then the readiness checklist for what he calls Partner Market Fit, then the program-design posts on why tiers and partner types should be earned rather than copied from larger competitors.
The most recent material turns to AI agents producing the operating data that makes partner revenue forecastable.
Read him as a vendor founder: he writes as EULER's chief executive, so milestone, hiring, and product posts sit alongside the advice, and the figures inside them are his own.
The conference, roundtable, and dinner posts are where he says the raw material comes from.
For adjacent reading, the similar creators below write in the same B2B go-to-market register from marketing, pricing, and channel-marketing angles.
Both publish short B2B go-to-market frameworks built on numbered steps and checklists for senior operators.
Read more
Basu's 100-day plan for new CMOs and his breakdown of how the six stakeholders in a complex B2B deal think before buying share Portnoy's diagnose-then-plan structure and his habit of turning a messy pipeline or revenue problem into an ordered list a reader can act on.
Basu writes from the marketing side of the house, covering CMO onboarding, lead definition, attribution, and content for buying committees. Portnoy writes from the partnerships side, about program design, partner-sourced revenue, and agents for partner operations, so the two are adjacent rather than overlapping reading.
Both write for B2B software operators selling AI products and both make their case through CFO-defensibility.
Read more
Rivera's posts on predictable total cost and on justifying AI spend to finance track Portnoy's cost-per-dollar and no-CFO-funds-a-channel-they-cannot-model argument. Both favour short frameworks, direct questions to the reader, and buyer-research figures over opinion.
Rivera's subject is pricing and packaging for AI vendors, grounded in survey data across company sizes. Portnoy's is partner programs and channel revenue, with his numbers coming from his own company and from executive conversations rather than published research.
Both write for go-to-market leaders and both tie partner or channel activity back to the customer journey and revenue rather than treating it as a separate function.
Read more
Ashe's channel-marketing and segment-marketing posts place partner channels alongside paid and owned channels, and his practical, operator-facing register matches how Portnoy frames partner work.
Ashe's material is marketing-side, built on segmentation, first-party data, and omnichannel journeys, and it rarely reaches partner-program design or partner economics. Portnoy's is partnerships-side, centred on program structure, partner P&L, and agentic partner management.
Greg Portnoy's content is aimed at B2B partner and go-to-market leaders: partner-program design, partner-sourced revenue measurement, CFO-ready financial reporting, and agentic partner management.
Read more
The posts repeatedly address partner executives, CxOs, and conference audiences, and he uses events such as Pavilion's GTM Conference, Partnership Leaders Catalyst, and EULER Partner Revenue Dinners to reach that professional world.
The supplied measured audience evidence is limited to a LinkedIn follower count of 26,858 as of October 8, 2026.
That figure establishes reach on one professional platform, but it does not show job titles, seniority, company size, geography, or engagement.
For a buyer assessing fit with a partnership-revenue brief, the content appeal is clear; the measured composition is not.
A practical next step is to request recent results for comparable partner-revenue topics and formats, such as reach, comment quality from partner leaders, or sponsored-post performance, or an audience survey if the brief depends on employer, occupation, or seniority.
Treat the follower count as professional-interest reach, not as a verified buyer composition.
Greg Portnoy's reviewed posts document no sponsorship or brand-partnership offer.
Read more
The commercial thread running through them is EULER, the partner-management platform he writes about as his own company: postscripts link to how EULER helps partner teams, and the events he publicises — Partnership Leaders Catalyst roundtables, EULER Partner Revenue Executive Dinners, and talks at Pavilion's GTM conference — are EULER's own programming.
His partner-program analysis (SpaceX's pre-launch partner network, overbuilt program tiers, partner-market fit, partner revenue and cost reporting) is written for partner leaders rather than for brands buying creator placements.
A B2B SaaS buyer should plan on reaching Greg Portnoy through EULER's product and partner community, not through a creator sponsorship package; no rate card, sponsorship policy, or partnership inquiry page appears in the reviewed material.
A B2B SaaS company that sells partner-management software, partner analytics, or agentic operations to partner leaders is a strong fit.
Read more
The review of Greg Portnoy's LinkedIn posts shows a consistent, specific body of work about making partner revenue CFO-fundable: build a partner P&L with partner-sourced, partner-influenced, and resale revenue, set costs against it, and report cost per dollar of partner-sourced revenue next to blended CAC.
The same material links that financial argument to AI agents that handle repetitive partner-team work and produce forecastable operating data.
A campaign built around operator education, benchmark research, a readiness assessment, or a private dinner series would sit naturally beside this work.
The best formats are practical templates, diagnostic checklists, and co-produced research that partner leaders can use in a board conversation.
This is not a standard creator sponsorship opportunity: the reviewed posts document no media kit, rate card, or sponsorship policy, and the public call to action points to EULER, the company Greg Portnoy writes about.
Plan on reaching them through EULER's product, partner community, conference roundtables, or executive dinners.
Claims about EULER's product usage, funding, headcount, and revenue are company-reported and should be attributed rather than repeated as independent fact.
When to choose a specialist
A consumer lifestyle, family, or broad-awareness brand looking for a creator sponsorship package is a poor fit.
Read more
The reviewed posts are overwhelmingly aimed at B2B partner executives, CxOs, and conference audiences, with one occasional family post that is not a content pillar.
There is no documented sponsorship offer, pricing, or partnership inquiry page, so a campaign that depends on a standard creator rate card or consumer-reach audience data would be starting from missing commercial evidence.
A B2B company that mainly wants rapid partner recruitment is also misaligned with the stated position: the content argues that most partner programs try to scale too early, that complexity should be earned rather than installed, and that companies without partner market fit should study their existing partners instead of adding more.
A brief that expects neutral third-party comparison of partner-management tools would also be a poor fit, because the posts promote EULER and its product directly.
The measured audience evidence supplied is a LinkedIn follower count of 26,858 as of 8 October 2026; it does not show job titles, seniority, company size, geography, or engagement.
Treat the account as professional-interest reach, not as a verified buyer composition.
A worked campaign example
Brief: a B2B SaaS company wants to make partner revenue more predictable and CFO-fundable, and asks whether Greg Portnoy fits.
Decision: yes, with a co-marketing and research structure rather than an influencer placement.
Worked angle: 'The partner P&L and the agentic reporting loop.' Build a practical campaign that first gives partner leaders a financial model and then shows how agents keep that model fed with operating data.
Step one, co-produce a benchmark report or workshop around the exact line items Greg Portnoy already publishes: partner-sourced revenue, partner-influenced revenue, resale revenue net of rebates, events and travel, partner team headcount, commissions and rebates, MDF and co-marketing spend, tooling, and the decisive metric of cost per dollar of partner-sourced revenue compared with blended CAC.
Step two, package the Partner Market Fit checklist from the posts as a self-assessment that helps a company decide whether it is ready to invest in process, tooling, and people.
Step three, attach the agentic argument: agents handle the repetitive work that consumes a partner team's week and generate the operational data that makes the channel forecastable.
The campaign can use an executive dinner or roundtable as the live format, because the posts describe EULER Partner Revenue Dinners and conference sessions as the settings where these operators compare notes.
The reason this fits is that it matches the two strongest themes in the reviewed material: partner financial reporting as the route to budget, and agentic partner management as the current thesis.
The main tradeoff is commercial proximity.
Greg Portnoy is a vendor founder whose content carries recruiting and product links, so the campaign should disclose the relationship and avoid presenting EULER product metrics as independently verified.
The next step for a brand is to test interest through EULER's partner community, an event roundtable, or a co-produced research concept, not through a standard creator sponsorship request.
Choose John Ashe when the same buyer task is really a channel-marketing and segmentation problem rather than a partner-revenue problem.
Read more
Ashe's posts work through bringing paid, owned, and partner channels into one message, teaming with segmentation, product, and partnerships to activate channels with relevance, and shifting measurement from impression counts to whether the customer was guided across channels and devices.
They also argue that generation labels should be inputs, not destinations, and that first-party behavior and intent data should drive segments.
For a B2B SaaS company whose question is how partner marketing fits into an omnichannel plan, or how to rebuild segmentation before spending on activation, this is closer to the working material than Greg Portnoy's finance-first partner P&L framing.
The tradeoff is that neither reviewed John Ashe post addresses partner revenue reporting, partner program structure, or partner-sourced pipeline economics.
There is no cost-per-dollar model, no partner market fit test, and no agentic operations angle.
A campaign that needs a CFO-ready partner P&L, a readiness checklist, or benchmark data on partner-sourced revenue would have to be built or sourced elsewhere.
The evidence is two posts with no audience composition, engagement, or commercial-availability data, so brand-fit conclusions beyond those posts are unsupported.
Choose Dev Basu when the brief is about repairing a broken marketing system or aligning marketing and sales around a shared lead definition, rather than about partner revenue.
Read more
The reviewed posts give a concrete 100-day sequence for a new CMO: audit closed-won deals, map channels against pipeline produced, check the real MQL-to-SQL rate, audit attribution, talk to the last five sales losses, then align ICP, agree what a good lead looks like, and pick one North Star pipeline metric before launching bottom-of-funnel content and paid search.
A second post maps the six-plus stakeholders in a complex B2B deal — champion, executive, finance, IT and security, operations, legal — and argues that each needs its own content or the deal stalls.
If the campaign goal is demand-generation repair or multi-stakeholder content, Dev Basu's material is the more directly usable base.
The tradeoff is that the reviewed posts stop at marketing and sales alignment.
They do not cover partner program design, partner-sourced or partner-influenced revenue, rebates and MDF cost lines, or partner market fit.
A brief that requires a partner P&L, partner revenue predictability, or an agentic partner-management story would lose its central argument.
The same evidence limits apply: two posts, no audience composition or engagement data, and no documented commercial offer.
Choose Marcos Rivera when the brief needs buyer-side pricing research and a predictability argument, especially for an AI product sold on usage-based pricing.
Read more
The reviewed posts report that 68% of AI buyers rank predictable total cost as a top pricing priority and only 19% care about a lower entry price, and that predictability matters most to companies under $50M while the larger-company problem shifts toward justifying spend to finance.
They turn that into three questions a vendor should answer before shipping usage-based pricing: can a buyer estimate the bill before signing, what happens when usage spikes, and does the metric track customer value rather than infrastructure cost.
A survey of 292 B2B software buyers and 480+ pricing engagements is the closest alternative evidence to a CFO-fundability conversation, but it is about pricing a vendor's own product, not forecasting partner-channel revenue.
The tradeoff is that the unit of analysis is a vendor's pricing model, not a partner program.
There is no partner P&L, no partner-sourced revenue metric, no partner market fit checklist, and no partner-team operating model.
A campaign aimed at partner leaders would need to carry pricing-predictability research into a channel context, and the reviewed posts do not make that translation.
Evidence is two posts with no audience composition, engagement, or commercial-availability data.
Based on eleven LinkedIn posts reviewed in full and the LinkedIn account record observed on 8 October 2026.
The posts cover partner-program design, partner financial reporting, readiness diagnostics, AI agents for partner operations, conference and dinner activity, EULER company milestones, and one personal family post.
Comparator evidence is limited to two posts each from three other creators.
Most posts carry no individual publication date; the talks, roundtables, and dinners named in the posts are not represented by transcripts; and EULER's revenue, headcount, funding, and product-usage figures are company-reported rather than independently verified.
The supplied material contains no books, shows, or earlier career work, so those remain an open research gap for a name-search profile.
Recent engagement
Across their last 9 LinkedIn posts, the median post got 88 reactions and 24 comments. Checked 2026-11-02.
