The SaaS Podcast - Real Lessons on Growing Profitable SaaS

He never bought a keyword, never ran content marketing, and the big outbound sales force he tried did not work. Rodney Robinson still grew TabaPay to $100 million in revenue, almost entirely through inbound, on a single $2.5 million seed round that stayed the company's only outside money for nine years.

Rodney explains how he found a problem Mastercard could not solve, why he chased small fintechs instead of big logos, how his inbound marketing came from banks and the card networks rather than ads, and why he believes outbound sales no longer works in B2B.

Plus: the six-month lawsuit that cost TabaPay its sponsor bank, and what Rodney had personally put on the line to get that bank in the first place.

TabaPay is payment processing infrastructure that gives fintechs one API to move money instantly in both directions, and processes payments for companies like Dave. The company runs at $100 million in revenue with about 150 people, profitable, growing 35 to 40 percent a year. On the day this interview was recorded, Rodney announced a $155 million raise and the acquisition of a bank.

🔑 Key Lessons

Build what the incumbent is forbidden to build: Mastercard would not add pull payments because it would compete with its biggest processors. That structural refusal, not a missed feature, was the opening TabaPay walked through.

Make the trusted party your sales channel: Fintechs do not know a new processor, but they trust their bank and Visa. TabaPay processes for about 20 banks and lets those relationships generate its inbound pipeline.

Solve revenue before expense: Rodney paid vendors above market to reach the market in a year, charged what it would bear, then displaced the vendors later. Getting to revenue outranked protecting early margin.

Chase minnows, not whales: The first ten customers were small fintechs where the founders already knew each other. Those minnows grew into whales, and the relationship carried through the growth.

Reliability is the product for infrastructure: Three vendors at 99 percent availability leaves you down about 3 percent of the time. Customers bet their business on payments working, so TabaPay took the stack in house.

Expect arrows in year one: Six months in, another company claimed TabaPay stole its software and the sponsor bank dropped them. They won, but only because there was nothing to find.

Chapters

What TabaPay does

$100M in revenue with 150 people

The $2.5M round that lasted nine years

Raising $155M and buying a bank

The problem Mastercard would not solve

Finding the wedge by listening

How the money actually moves

A year to build the first version

Solving revenue before expense

Pledging his house for a sponsor bank

Landing the first ten customers

Chasing minnows instead of whales

When vendors go down

Owning the stack end to end

Channels that wasted time

Why outbound sales is dead in B2B

Building the inbound engine

Pricing against commoditization

Fraud data as a value-add

The lawsuit that cost them their bank

Making every customer feel like the biggest

Why buy a bank

Lightning round

Resources

Full show notes: https://saasclub.io/495

Join 5,000+ SaaS founders: https://saasclub.io/email

He needed a big retailer's data to build the product. No big retailer gives data to a company with no product. Felix Hoffmann solved it sideways: 7Learnings sold a paid consulting project, kept the right to use the data, and built its predictive pricing product on top of it. Ten customers later it was at $1M ARR, and he had closed every one himself.
Felix explains why a demand forecasting product cannot start with a small customer, how he structured the first pilot as an A/B test so a retailer could hand over half its prices without betting the business, and what happened when the first run came back far too expensive.
Plus: how a pricing optimization company prices itself, and why he refuses success-based fees even though he can prove the uplift.
7Learnings is a Berlin company whose software forecasts demand for each product at each price, then sets the price that hits a retailer's goal. It is now at multiple seven figures in ARR with around 40 customers. Felix spent six years as a pricing consultant at Kearney and two years running price optimization at Zalando before founding it.
This episode is brought to you by:
🤖 Hobbes → Don't book a demo. Take one.
🔑 Key Lessons
🎯 Solve the data cold start by selling something else first: 7Learnings could not train a forecasting model without a large retailer's sales history, so it sold a paid consulting project and kept the right to use that dataset.
🤝 Shrink a scary ask into a reversible test: Retailers would not hand pricing to an algorithm outright, so 7Learnings ran an A/B test on half the assortment while the retailer's own team priced the rest.
📉 Pick an early customer who can survive a failure: The first live pricing run was badly wrong on high-priced products. It survived because the buyer had a big enough problem, no alternative, and understood they were working with a startup.
💰 Price high enough to lose some deals: His test is blunt. If nobody is walking away because you are too expensive, you are too cheap, especially for a complex product carrying real delivery cost.
🚀 Founder-led sales lasts longer than founders expect: Felix closed all ten customers behind the first $1M ARR himself, and stayed closely involved through the next forty, because handing off enterprise sales is genuinely hard.
⚡ Pick the technology after the problem, not before: Felix argues founders are all digging in the same technical space, and that decisions needing determinism, low cost and explainability should not be handed to an LLM.
Chapters
Where the idea came from: Kearney, then Zalando
The hardest part was finding co-founders
The consulting project that funded the product
Finding the first paying customer
Structuring the first deal as an A/B test
The first upload was a disaster
How a pricing company prices itself
Ten customers to $1M ARR
The price matching objection
Why LLMs don't belong in the pricing decision
Resources
Full show notes: https://saasclub.io/494
Join 5,000+ SaaS founders: https://saasclub.io/email

Nine months in. Close to zero customers. He was ready to hand the money back to investors. Rick Knudtson had already sold one company, so Workshop started with the idea he found interesting: an intranet. Customers kept telling him to fix email instead. The rebuild took 30 days and brought in 10 customers.
Rick explains why big enterprises cannot run internal comms on a cheap marketing tool, how a year of newsletters and ungated resources filled the pipeline before Workshop had anything to sell, and what changed when the founding team stopped defending its own idea and started listening to customers.
Plus: why Workshop dropped per-user fees for audience-based pricing, and how that changed the way customers expand into new departments.
Workshop is an internal communications software platform based in Omaha with around 140 employees and just under 1,000 customers, including Capgemini. It is five years old and past $10M ARR. Rick previously co-founded Flywheel, a WordPress hosting platform sold to WP Engine in 2019.
This episode is brought to you by:
🤖 Hobbes → Don't book a demo. Take one.
🔑 Key Lessons
👂 The signal was in the sales calls all along: Prospects named email as their biggest internal comms pain for nine months while Workshop kept building an intranet. Listening to customers only started once the ego from a previous exit got out of the way.
🎯 Finding product-market fit was obvious when it finally arrived: Nine months of selling the intranet earned about three customers. Thirty days on the email product brought ten. That gap told the team exactly where to go all in.
🧱 Pick a first problem you can ship fast: An intranet cannot be built iteratively, so feedback loops stall for months. Email analytics was small enough to ship in 30 days and grow into a wider platform.
🔒 Enterprise email is not a MailChimp problem: Security layers, IT governance, and getting a message into 100,000 inboxes in minutes are why large companies cannot run internal comms on an off-the-shelf marketing tool.
📣 Market for a year before you sell anything: Workshop launched a weekly newsletter on day one, now at 50,000 subscribers, alongside ungated resources and monthly webinars that grew from five attendees to five hundred.
💰 Audience-based pricing removes expansion friction: Workshop charges by employee audience size and by channel rather than per seat, so adding another department never triggers a procurement review or a new negotiation.
🧭 Write the mission first and the values later: A broad mission gave the team direction before the product existed. Values waited twelve months so they described what had actually kept the company alive.
Chapters
How selling Flywheel led to the internal comms idea
Writing the mission statement before the product
The intranet bet and why it never found a through line
Why enterprise email is harder than founders assume
Building a newsletter and resource library before selling
Nine months, near-zero customers, and the plan to return the money
The bar conversation that led to the 30-day email rebuild
Ten customers in 30 days and what product-market fit felt like
Audience-based pricing and dropping per-seat fees
Lightning round
Resources
Full show notes: https://saasclub.io/493
Join 5,000+ SaaS founders: https://saasclub.io/email

Ten thousand ads, all built by hand. Julius Körfgen left that grind to build Uplane, software that automates it, then sold to his first customers before writing a line of code. Uplane reached a million dollars in ARR in about six months.
Julius makes the case for selling before building: the cold outreach that got strangers on calls, the one-week sprint from discovery call to working demo, and why he refuses to run a free pilot. Without a dollar attached, he argues, you cannot tell a real business case from a polite conversation.
Plus: why Julius threw out per-seat pricing and now charges a share of ad spend, so Uplane only earns more when the customer's campaigns do better.
Uplane runs around twenty people across San Francisco and Berlin. Julius and his two co-founders raised their first funding round close to a year before the product existed, AG1 is a customer, and a project with Deutsche Bahn is underway.
This episode is brought to you by:
🤖 Hobbes → Don't book a demo. Take one.
🔑 Key Lessons
🤝 Sell before you build: Julius closed customers before writing a line of code. His discovery calls ended with a promise to return in a week with a solution, which forced both a real deadline and a real answer about demand.
🎯 Frame outreach as learning, not selling: His cold LinkedIn messages said he had just left his job and was exploring an idea, and asked for a few questions. People opened up about problems they would never have shared with a pitch.
💰 Never run a free pilot: Without a dollar attached you cannot tell a business case from a polite conversation. Julius has watched founders stay attached to an idea for months because nobody ever asked them to pay for it.
⚡ A week is long enough to build the thing you promised: Three founders and one week produced demos that won real customers. Scrappy was fine; fake was not, and he argues AI removes the excuse for a mock-up that does nothing.
💰 Align pricing with the outcome you claim: Uplane charges a fixed fee covering costs plus a variable share of ad spend. Julius says it makes the pitch easier, because he only earns more when the customer's campaigns do better.
🏢 Be reachable faster than an agency can be: Uplane answers customers within 120 seconds. Julius treats speed of response as the main structural advantage an early-stage company has over an incumbent agency.
🧠 Volume is not the constraint anymore: AI made producing ads nearly free, so the bottleneck moved to picking the roughly ten percent that perform. Companies pushing more output without connecting it to analytics are solving the wrong half.
Chapters
Introduction
What Uplane does and the problem it solves
Ten thousand ads by hand
Deciding to leave and build it
The cold LinkedIn outreach that worked
Standing out when everyone uses AI to personalise
The first customer
Why free pilots are a trap
The one-week sprint from call to demo
The 120-second response rule
Throwing out per-seat pricing
Attribution and charging on ad spend
Guardrails and atomic content
Lightning round
Resources
Full show notes: https://saasclub.io/492
Join 5,000+ SaaS founders: https://saasclub.io/email

Two founders. Two engineers. No product. Christian Lund closed one of the Big Four accounting firms as Templafy's first customer before the software existed, by selling a point of view instead of a demo. When that customer asked to start with ten people, he didn't say no. He said "yes, if."
Christian breaks down his approach to selling to enterprise without a product, why he answered every ten-person pilot request with "yes, if," and how fixing the proof criteria upfront turned trials into company-wide deals. He also explains why disqualifying prospects beats trying to convince them.
Templafy now runs at eight figures in revenue with a couple of hundred employees. Christian and his co-founder spun it out of an on-premise document business, raised their first funding round close to twelve months before the product existed, and are now rebuilding the company again for the AI shift.
This episode is brought to you by:
🤖 Hobbes → Don't book a demo. Take one.
🔑 Key Lessons
🏢 Sell your point of view before you sell product: During a technology shift, large enterprises buy people who understand the transition. Templafy won a Big Four firm on domain expertise alone, then co-created the product with them.
🤝 Answer pilot requests with "yes, if" rather than no: Christian never refused a proof of concept. He attached conditions on proof criteria, budget, timeline, and the rollout that follows, and walked away when they were missing.
🎯 Define what you are proving before any trial starts: A POC to see whether someone likes the product proves nothing. Agreeing the exact pass conditions upfront turns a trial into a decision rather than an experiment.
⚡ Setting the criteria shapes the competition: Because Templafy defined the proof points first, prospects who later ran competitive evaluations often used Templafy's criteria to score every vendor in the process.
🧠 Disqualify rather than convince: Christian's team filters for buyers who already accept the market is changing. He argues sales has nothing to do with convincing people, and that defending buyers cost too much time to pursue.
🚀 Land wide, then go deep: Enterprise security and procurement cost the same for ten users or a hundred thousand, so Templafy pushed for company-wide rollouts first and expanded into specific team use cases afterwards.
📉 Being too far ahead is a real cost: Templafy's AI messaging ran ahead of what buyers wanted. Christian's rule is that you can be fifteen percent ahead of the market but not eighty, or you lose the conversation entirely.
Chapters
Introduction
What Templafy does and the size of the business
Seeing the cloud shift and spinning out of the on-premise business
Two founders, two engineers, and a year of unlearning
Selling thought leadership instead of product
Targeting 800 people with specific messaging
Raising funding twelve months before the product
Why every enterprise customer is its own market
The ten-person pilot problem
"We didn't say no, we said yes if"
Writing the criteria your competitors get scored on
Disqualification as a sales strategy
Resetting the company again for AI: fifteen percent ahead, not eighty
Uphill skiers, downhill skiers, and the lightning round
Resources
Full show notes: https://saasclub.io/491
Join 5,000+ SaaS founders: https://saasclub.io/email