# Greg Portnoy

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.

- Profile: https://b2binfluencer.marketing/creators/greg-portnoy/
- LinkedIn: https://www.linkedin.com/in/gregportnoy
- LinkedIn followers: 26,858
- Median of last 9 posts: 88 reactions, 24 comments (checked 2026-11-02)
- Topics: artificial-intelligence, leadership, startup, ai-agents, unit-economics, b2b-saas
- Based on 9 dated posts, latest 2026-10-06

## Summary

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.
- Check first: Confirm whether they have a media kit, rate card, or sponsorship policy before contacting them.

### 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.

## Main ideas

- **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. 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.
- **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. 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.
- **Partner Market Fit is the gate before spending on process, tooling, or people**: Portnoy sets a readiness test rather than a growth target. 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.
- **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. 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.
- **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. 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.
- **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. 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.

## Work to read

- [SpaceX Super Intelligence's partner network: three launch choices most companies miss](https://www.linkedin.com/posts/gregportnoy_spacex-super-intelligence-launched-its-partner-activity-7523093260257517568-BGRE)
- [Your partner program is too complicated](https://www.linkedin.com/posts/gregportnoy_your-partner-program-is-too-complicated-activity-7518019512617668608-Nzgh)
- [Partner programs lose budget because they lack a P&L](https://www.linkedin.com/posts/gregportnoy_lets-get-really-honest-this-is-hard-to-activity-7516181056652447745-6EP3)
- [Executives hesitate to invest in partnerships because they don't know what good looks like](https://www.linkedin.com/posts/gregportnoy_last-week-i-spoke-with-dozens-of-ceos-cros-activity-7513294373900464129-L9GD)
- [13 signs you've reached Partner Market Fit](https://www.linkedin.com/posts/gregportnoy_most-partner-programs-try-to-scale-too-early-activity-7515822681087283201-fTAU)
- [The agentic playbook for predictable partner revenue](https://www.linkedin.com/posts/gregportnoy_on-the-way-to-new-york-to-speak-at-pavilion-activity-7510368314808803328-8GXe)
- [EULER's first $1M quarter and the PAM AI Agent numbers](https://www.linkedin.com/posts/gregportnoy_it-took-euler-a-year-to-hit-our-first-1m-activity-7516556710472495104-myhL)

## Brand relationships

- **EULER** (disclosed_partnership)
- **Channel Equity Partners** (investment)
- **Partnership Leaders** (mention)
- **Pavilion** (mention)
- **Zapier** (mention)

## Partnerships

Greg Portnoy's reviewed posts document no sponsorship or brand-partnership offer. 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.

## Alternatives

- John Ashe: Choose John Ashe when the same buyer task is really a channel-marketing and segmentation problem rather than a partner-revenue problem. 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.
- Dev Basu: 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. 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.
- Marcos Rivera: 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. 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.

---
AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/