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Oct 30, 2019 · 15m · top-founders

1558 Why This Event Management CEO Believes 25% Of Her $2.5m In Revenue Should Be Professional Services

Ali Magyar · 8m spoken Nathan Latka · 5m spoken
0:00 / 0:00

gold bands on the timeline = statements, start to end. Hover to read, click to jump. CC turns on captions

In this interview with Nathan Latka, Hub founder and CEO Ali Magyar explains how she transformed an internal agency workflow tool into a $2.2 million ARR event intelligence SaaS platform backed by $13 million in capital. She breaks down Hub's customer acquisition economics, 110% net revenue retention, and why maintaining a 25% professional services revenue mix supports enterprise scale.

How this conversation actually went

Every chapter scored 0–10 on four independent dynamics. Hover any point for the reasoning behind the score. Nathan holds 40.7% of the talking time here. How this is scored →

Nathan as informed peer 5.8 Guest teaching 3.3 Guest disagreement 1.0 Nathan pushing back 2.8
05100:0010:001:16–4:37 · Nathan as informed peer 5/10 Understanding Hub's Core Software and Business Model Latka explores Hub's business model, probing whether the platform is pure SaaS or service-heavy. Magyar explains the industry's historical reliance on antiquated tech and details why enterprise clients require a 25% professional services mix.4:38–7:16 · Nathan as informed peer 6/10 Hub's Origins, Agency Spinout, and Bootstrapping Phase Latka pushes into the mechanics of spinning out software from an existing agency, specifically interrogating how the cap table was structured and whether the $3M invested was real cash or internal agency labor. Magyar clarifies that it was funded via cash flow into outsourced software development.7:16–11:41 · Nathan as informed peer 7/10 Customer Breakdown, ARR Scale, and Venture Fundraising Latka digs into the SaaS metrics, calculating MRR, total funding amounts, and solving the net retention equation in real time. Magyar elaborates on how Hub combats high event churn by positioning the product as a cross-event CMO data platform.11:41–14:33 · Nathan as informed peer 5/10 Pacific Northwest Talent, CAC Payback, and Content Marketing Engine Latka quickly converts Magyar's CAC and ACV into a 4-5 month payback metric while discussing local Pacific Northwest talent dynamics before transitioning into the Famous Five closing questions.1:16–4:37 · Guest teaching 4/10 Understanding Hub's Core Software and Business Model Latka explores Hub's business model, probing whether the platform is pure SaaS or service-heavy. Magyar explains the industry's historical reliance on antiquated tech and details why enterprise clients require a 25% professional services mix.4:38–7:16 · Guest teaching 3/10 Hub's Origins, Agency Spinout, and Bootstrapping Phase Latka pushes into the mechanics of spinning out software from an existing agency, specifically interrogating how the cap table was structured and whether the $3M invested was real cash or internal agency labor. Magyar clarifies that it was funded via cash flow into outsourced software development.7:16–11:41 · Guest teaching 4/10 Customer Breakdown, ARR Scale, and Venture Fundraising Latka digs into the SaaS metrics, calculating MRR, total funding amounts, and solving the net retention equation in real time. Magyar elaborates on how Hub combats high event churn by positioning the product as a cross-event CMO data platform.11:41–14:33 · Guest teaching 2/10 Pacific Northwest Talent, CAC Payback, and Content Marketing Engine Latka quickly converts Magyar's CAC and ACV into a 4-5 month payback metric while discussing local Pacific Northwest talent dynamics before transitioning into the Famous Five closing questions.1:16–4:37 · Guest disagreement 1/10 Understanding Hub's Core Software and Business Model Latka explores Hub's business model, probing whether the platform is pure SaaS or service-heavy. Magyar explains the industry's historical reliance on antiquated tech and details why enterprise clients require a 25% professional services mix.4:38–7:16 · Guest disagreement 2/10 Hub's Origins, Agency Spinout, and Bootstrapping Phase Latka pushes into the mechanics of spinning out software from an existing agency, specifically interrogating how the cap table was structured and whether the $3M invested was real cash or internal agency labor. Magyar clarifies that it was funded via cash flow into outsourced software development.7:16–11:41 · Guest disagreement 1/10 Customer Breakdown, ARR Scale, and Venture Fundraising Latka digs into the SaaS metrics, calculating MRR, total funding amounts, and solving the net retention equation in real time. Magyar elaborates on how Hub combats high event churn by positioning the product as a cross-event CMO data platform.11:41–14:33 · Guest disagreement 0/10 Pacific Northwest Talent, CAC Payback, and Content Marketing Engine Latka quickly converts Magyar's CAC and ACV into a 4-5 month payback metric while discussing local Pacific Northwest talent dynamics before transitioning into the Famous Five closing questions.1:16–4:37 · Nathan pushing back 2/10 Understanding Hub's Core Software and Business Model Latka explores Hub's business model, probing whether the platform is pure SaaS or service-heavy. Magyar explains the industry's historical reliance on antiquated tech and details why enterprise clients require a 25% professional services mix.4:38–7:16 · Nathan pushing back 5/10 Hub's Origins, Agency Spinout, and Bootstrapping Phase Latka pushes into the mechanics of spinning out software from an existing agency, specifically interrogating how the cap table was structured and whether the $3M invested was real cash or internal agency labor. Magyar clarifies that it was funded via cash flow into outsourced software development.7:16–11:41 · Nathan pushing back 3/10 Customer Breakdown, ARR Scale, and Venture Fundraising Latka digs into the SaaS metrics, calculating MRR, total funding amounts, and solving the net retention equation in real time. Magyar elaborates on how Hub combats high event churn by positioning the product as a cross-event CMO data platform.11:41–14:33 · Nathan pushing back 1/10 Pacific Northwest Talent, CAC Payback, and Content Marketing Engine Latka quickly converts Magyar's CAC and ACV into a 4-5 month payback metric while discussing local Pacific Northwest talent dynamics before transitioning into the Famous Five closing questions.

speaking balance: gold is Nathan, purple is the guest (3 minute bins)

0:00 · Nathan 55.2% · guest 44.8%0:00 · Nathan 55.2% · guest 44.8%3:00 · Nathan 18.7% · guest 81.3%3:00 · Nathan 18.7% · guest 81.3%6:00 · Nathan 46% · guest 54%6:00 · Nathan 46% · guest 54%9:00 · Nathan 30.2% · guest 69.8%9:00 · Nathan 30.2% · guest 69.8%12:00 · Nathan 47.1% · guest 52.9%12:00 · Nathan 47.1% · guest 52.9%15:00 · Nathan 91.9% · guest 8.1%15:00 · Nathan 91.9% · guest 8.1%
Sharpest disagreement ▶ 6:56 Clarifying cash allocation versus agency services

Magyar firmly refines Latka's assumption about agency expenses, clarifying that the $3M was direct outsourced development cash rather than credited agency services.

 Hardest push from Nathan ▶ 6:46 Pressing on agency cash flow accounting

Latka interrupts to clarify whether the founder used actual agency cash flow or simply amortized agency staff salaries into the $3M initial capital calculation.

 Biggest teaching moment ▶ 9:30 Reframing event software from logistics to CMO data play

Magyar explains how event SaaS avoids fatal churn by moving above transactional event management to become an enterprise-level content and speaker intelligence engine.

 Nathan holds their own ▶ 10:55 Real-time expansion math deduction

Latka instantly deduces and states the required 30% expansion rate after Magyar shares an 80% gross retention and 110% net retention figure.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Understanding Hub's Core Software and Business Model 5412 Latka explores Hub's business model, probing whether the platform is pure SaaS or service-heavy. Magyar explains the industry's historical reliance on antiquated tech and details why enterprise clients require a 25% professional services mix.
Hub's Origins, Agency Spinout, and Bootstrapping Phase 6325 Latka pushes into the mechanics of spinning out software from an existing agency, specifically interrogating how the cap table was structured and whether the $3M invested was real cash or internal agency labor. Magyar clarifies that it was funded via cash flow into outsourced software development.
Customer Breakdown, ARR Scale, and Venture Fundraising 7413 Latka digs into the SaaS metrics, calculating MRR, total funding amounts, and solving the net retention equation in real time. Magyar elaborates on how Hub combats high event churn by positioning the product as a cross-event CMO data platform.
Pacific Northwest Talent, CAC Payback, and Content Marketing Engine 5201 Latka quickly converts Magyar's CAC and ACV into a 4-5 month payback metric while discussing local Pacific Northwest talent dynamics before transitioning into the Famous Five closing questions.

Statements from this episode (13)

Assertion Not checkable as stated
Magyar: Hub's ACV Is Roughly $20,000
“Our ACV is roughly around 20,000 right now.”
Ali Magyar Oct 30, 2019 ▶ 3:03
Insight
Magyar: Events Need 50+ Speakers or Sponsors to Justify Automation Software
“Hub is a good fit for anyone that has 50 or more speakers, sessions, sponsors. So if you have less than that, you really can handle the automation yourself. It's not that complex.”
Ali Magyar Oct 30, 2019 ▶ 3:30
Assertion Not checkable as stated
Magyar: 25% of Hub's Business Is Services and 75% Is Pure SaaS
“25% of our business is in In professional services, and the 75% is in pure SaaS, so.”
Ali Magyar Oct 30, 2019 ▶ 4:29
Assertion Not checkable as stated
Hub generated $650,000 across 21 paying customers in its first year
“So in 2015, we did our proof of concept, and so we went to market, and in the first year, we ended with 21 paying customers, about 650,000 in revenue, and I realized there definitely was market traction and market adoption.”
Ali Magyar Oct 30, 2019 ▶ 5:43
Disclosure
Magyar: Bootstrapped Hub using $3M of agency cashflow
“So I did use agency cash to be able to fund that three million dollars, but there wasn't any expenses for the agency that I would have been receiving professional services for as a part of that three million.”
Ali Magyar Oct 30, 2019 ▶ 6:56
Assertion Not checkable as stated
Magyar: Hub has about 125 total customers
“We're about a 125 customers today.”
Ali Magyar Oct 30, 2019 ▶ 7:19
Assertion Not checkable as stated
Magyar: About 90% of Hub's customers are on pure ARR
“The majority of them are on more of our ARR plan versus the one-time event. So about 90% of our customers are on pure ARR.”
Ali Magyar Oct 30, 2019 ▶ 7:28
Assertion Supported
Hub raised $13M across Series A, Series B, and founder capital
“So no, we've done our series A and our series B plus the original investment that I did. So total would be thirteen million between all of those.”
Ali Magyar Oct 30, 2019 ▶ 8:29
Opinion
Latka: SaaS Models Struggle in Events Space Due to Episodic Churn
“SaaS is hard to make work in an event space because they start and they stop. So unless someone consistently does events, SaaS models really don't work. It throws your churn all out of whack.”
Nathan Latka Oct 30, 2019 ▶ 9:02
Disclosure
Ali Magyar: Hub Sees 80% Gross Retention on SaaS Platform
“On the SaaS platform, we're about 80% retention. So about 20% churn.”
Ali Magyar Oct 30, 2019 ▶ 10:24
Disclosure
Ali Magyar: Hub Reaches Approximately 110% Net Revenue Retention
“Yeah, net revenue retention, we're about a 110% right now.”
Ali Magyar Oct 30, 2019 ▶ 10:56
Assertion Not checkable as stated
Hub has doubled revenue every year since launching in 2015
“We've doubled every year in revenue that since we've been in market in 2015.”
Ali Magyar Oct 30, 2019 ▶ 11:55
Disclosure
Hub acquires SaaS customers for $5,000 to $6,000 in CAC
“Our customer acquisition costs are they vary between five and six grand this year based on the different campaigns that we're doing, but we have a pretty low cap.”
Ali Magyar Oct 30, 2019 ▶ 12:46
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