StarZero All shows Try the podcast clipper →

Mar 20, 2019 · 18m · top-founders

1334 This $600k+ ARR SaaS Helps Oil and Gas Companies Predict Oil Well Production

Luther Birdzell · 11m 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 episode of The Top Entrepreneurs, Nathan Latka interviews Luther Birdzell, founder of Oil and Gas Analytics, exploring how his cloud-based AI platform optimizes upstream well planning, generates over $50,000 in monthly recurring revenue, and scales within the capital-intensive energy sector.

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 30.6% of the talking time here. How this is scored →

Nathan as informed peer 4.3 Guest teaching 3.3 Guest disagreement 1.5 Nathan pushing back 2.7
05100:0010:001:45–5:31 · Nathan as informed peer 5/10 AI-Powered Well Planning and Capital Optimization Value Proposition Luther explains the upstream oil economics (capital spent pre/post drill), and Nathan asks clarifying technical questions to confirm whether they deploy proprietary hardware or pure cloud analytics.5:32–8:30 · Nathan as informed peer 6/10 SaaS Pricing Structure, Customer Profile, and Retention Dynamics Nathan presses on customer retention and potential churn if a customer finishes drilling a well. Luther schools Nathan on oil and gas land leasing economics, explaining that operators must keep drilling to maintain lease validity.8:30–12:26 · Nathan as informed peer 4/10 Go-to-Market Timeline, Peer-to-Peer Consulting Model, and Team Breakdown Nathan probes customer counts and delivery model, cutting off Luther's extended monologue to nail down specific team counts and engineering breakdown across remote vs Houston locations.12:26–15:56 · Nathan as informed peer 5/10 Fundraising Strategy, Series A Plans, and Customer Acquisition Cost Luther shares angel funding numbers and Series A expansion plans. Nathan digs into unit economics, querying customer acquisition cost (CAC) and sales quota testing.15:57–18:20 · Nathan as informed peer 6/10 Revenue Growth Projections and Monthly Recurring Revenue Benchmark Nathan quickly runs the math on Luther's minimum customer and price points to deduce they are doing north of $50k MRR, followed by the standard Famous Five lightning round.18:20–18:57 · Nathan as informed peer 0/10 Episode Conclusion and Host Executive Summary Host outro summary monologue wrapping up company metrics, CAC, payback period, and team details.1:45–5:31 · Guest teaching 5/10 AI-Powered Well Planning and Capital Optimization Value Proposition Luther explains the upstream oil economics (capital spent pre/post drill), and Nathan asks clarifying technical questions to confirm whether they deploy proprietary hardware or pure cloud analytics.5:32–8:30 · Guest teaching 6/10 SaaS Pricing Structure, Customer Profile, and Retention Dynamics Nathan presses on customer retention and potential churn if a customer finishes drilling a well. Luther schools Nathan on oil and gas land leasing economics, explaining that operators must keep drilling to maintain lease validity.8:30–12:26 · Guest teaching 4/10 Go-to-Market Timeline, Peer-to-Peer Consulting Model, and Team Breakdown Nathan probes customer counts and delivery model, cutting off Luther's extended monologue to nail down specific team counts and engineering breakdown across remote vs Houston locations.12:26–15:56 · Guest teaching 3/10 Fundraising Strategy, Series A Plans, and Customer Acquisition Cost Luther shares angel funding numbers and Series A expansion plans. Nathan digs into unit economics, querying customer acquisition cost (CAC) and sales quota testing.15:57–18:20 · Guest teaching 2/10 Revenue Growth Projections and Monthly Recurring Revenue Benchmark Nathan quickly runs the math on Luther's minimum customer and price points to deduce they are doing north of $50k MRR, followed by the standard Famous Five lightning round.18:20–18:57 · Guest teaching 0/10 Episode Conclusion and Host Executive Summary Host outro summary monologue wrapping up company metrics, CAC, payback period, and team details.1:45–5:31 · Guest disagreement 1/10 AI-Powered Well Planning and Capital Optimization Value Proposition Luther explains the upstream oil economics (capital spent pre/post drill), and Nathan asks clarifying technical questions to confirm whether they deploy proprietary hardware or pure cloud analytics.5:32–8:30 · Guest disagreement 3/10 SaaS Pricing Structure, Customer Profile, and Retention Dynamics Nathan presses on customer retention and potential churn if a customer finishes drilling a well. Luther schools Nathan on oil and gas land leasing economics, explaining that operators must keep drilling to maintain lease validity.8:30–12:26 · Guest disagreement 2/10 Go-to-Market Timeline, Peer-to-Peer Consulting Model, and Team Breakdown Nathan probes customer counts and delivery model, cutting off Luther's extended monologue to nail down specific team counts and engineering breakdown across remote vs Houston locations.12:26–15:56 · Guest disagreement 2/10 Fundraising Strategy, Series A Plans, and Customer Acquisition Cost Luther shares angel funding numbers and Series A expansion plans. Nathan digs into unit economics, querying customer acquisition cost (CAC) and sales quota testing.15:57–18:20 · Guest disagreement 1/10 Revenue Growth Projections and Monthly Recurring Revenue Benchmark Nathan quickly runs the math on Luther's minimum customer and price points to deduce they are doing north of $50k MRR, followed by the standard Famous Five lightning round.18:20–18:57 · Guest disagreement 0/10 Episode Conclusion and Host Executive Summary Host outro summary monologue wrapping up company metrics, CAC, payback period, and team details.1:45–5:31 · Nathan pushing back 2/10 AI-Powered Well Planning and Capital Optimization Value Proposition Luther explains the upstream oil economics (capital spent pre/post drill), and Nathan asks clarifying technical questions to confirm whether they deploy proprietary hardware or pure cloud analytics.5:32–8:30 · Nathan pushing back 5/10 SaaS Pricing Structure, Customer Profile, and Retention Dynamics Nathan presses on customer retention and potential churn if a customer finishes drilling a well. Luther schools Nathan on oil and gas land leasing economics, explaining that operators must keep drilling to maintain lease validity.8:30–12:26 · Nathan pushing back 4/10 Go-to-Market Timeline, Peer-to-Peer Consulting Model, and Team Breakdown Nathan probes customer counts and delivery model, cutting off Luther's extended monologue to nail down specific team counts and engineering breakdown across remote vs Houston locations.12:26–15:56 · Nathan pushing back 3/10 Fundraising Strategy, Series A Plans, and Customer Acquisition Cost Luther shares angel funding numbers and Series A expansion plans. Nathan digs into unit economics, querying customer acquisition cost (CAC) and sales quota testing.15:57–18:20 · Nathan pushing back 2/10 Revenue Growth Projections and Monthly Recurring Revenue Benchmark Nathan quickly runs the math on Luther's minimum customer and price points to deduce they are doing north of $50k MRR, followed by the standard Famous Five lightning round.18:20–18:57 · Nathan pushing back 0/10 Episode Conclusion and Host Executive Summary Host outro summary monologue wrapping up company metrics, CAC, payback period, and team details.

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

0:00 · Nathan 58.2% · guest 41.8%0:00 · Nathan 58.2% · guest 41.8%3:00 · Nathan 15.9% · guest 84.1%3:00 · Nathan 15.9% · guest 84.1%6:00 · Nathan 25.4% · guest 74.6%6:00 · Nathan 25.4% · guest 74.6%9:00 · Nathan 16.3% · guest 83.7%9:00 · Nathan 16.3% · guest 83.7%12:00 · Nathan 20.1% · guest 79.9%12:00 · Nathan 20.1% · guest 79.9%15:00 · Nathan 34% · guest 66%15:00 · Nathan 34% · guest 66%18:00 · Nathan 74.6% · guest 25.4%18:00 · Nathan 74.6% · guest 25.4%
Sharpest disagreement ▶ 7:04 Pushing back against churn hypothetical

Luther firmly rejects Nathan's hypothetical about customers stopping drilling after one well, stating flatly that operators would go out of business.

 Hardest push from Nathan ▶ 6:35 Pressing on SaaS churn risk

Nathan refuses to let go of the churn question, insisting on knowing what happens when a client finishes an initial 30-day drill window.

 Biggest teaching moment ▶ 7:12 Explaining oil leasehold economics

Luther educates Nathan on industry mechanics, explaining that oil leases legally require continuous drilling to remain valid.

 Nathan holds their own ▶ 16:42 Calculating minimum MRR run rate

Nathan combines customer count minimums and contract floor rates to successfully pin down the company's real baseline revenue.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
AI-Powered Well Planning and Capital Optimization Value Proposition 5512 Luther explains the upstream oil economics (capital spent pre/post drill), and Nathan asks clarifying technical questions to confirm whether they deploy proprietary hardware or pure cloud analytics.
SaaS Pricing Structure, Customer Profile, and Retention Dynamics 6635 Nathan presses on customer retention and potential churn if a customer finishes drilling a well. Luther schools Nathan on oil and gas land leasing economics, explaining that operators must keep drilling to maintain lease validity.
Go-to-Market Timeline, Peer-to-Peer Consulting Model, and Team Breakdown 4424 Nathan probes customer counts and delivery model, cutting off Luther's extended monologue to nail down specific team counts and engineering breakdown across remote vs Houston locations.
Fundraising Strategy, Series A Plans, and Customer Acquisition Cost 5323 Luther shares angel funding numbers and Series A expansion plans. Nathan digs into unit economics, querying customer acquisition cost (CAC) and sales quota testing.
Revenue Growth Projections and Monthly Recurring Revenue Benchmark 6212 Nathan quickly runs the math on Luther's minimum customer and price points to deduce they are doing north of $50k MRR, followed by the standard Famous Five lightning round.
Episode Conclusion and Host Executive Summary 0000 Host outro summary monologue wrapping up company metrics, CAC, payback period, and team details.

Statements from this episode (12)

Assertion Supported
Birdzell: $500B spent annually in upstream oil and gas
“And if we look at the oil and gas industry, Nathan, about five hundred billion dollars of cash is spent every year in the upstream, you know, part of the oil and gas.”
Luther Birdzell Mar 20, 2019 ▶ 2:56
Assertion Contradicted
Birdzell: 90% of upstream spend is within 60 days of drilling
“Right, and 90% of that five hundred billion is spent 30 days pre-drilled to 30 days post-drilled.”
Luther Birdzell Mar 20, 2019 ▶ 3:11
Assertion Not checkable as stated
Oil and Gas Analytics' software saves $400K to $1M per well
“And we're identifying insights to save a five to 10% of cost per well. Which is, you know, 400 to 800,000 dollars, 400,000 to a million dollars per well.”
Luther Birdzell Mar 20, 2019 ▶ 3:57
Disclosure
Birdzell: Oil and Gas Analytics monthly fees range from $10k to $50k
“Across that, you know, really almost the whole spectrum of the market you know, those monthly fees range, you know, the monthly licensing costs, It ranges from about 10 to 50 K a month.”
Luther Birdzell Mar 20, 2019 ▶ 6:20
Disclosure
Birdzell: Oil and Gas Analytics has between 5 and 10 customers
“It's we're between five and 10.”
Luther Birdzell Mar 20, 2019 ▶ 9:07
Insight
Birdzell: Industrial AI adoption requires peer-to-peer delivery with subject experts
“The more AI and machine learning are rolled out in the industrial sector. So this is using these enabling technologies to affect relatively few, very high cost or high consequence decisions requires kind of delivering, enabling the capabilities on a peer to pe…”
Luther Birdzell Mar 20, 2019 ▶ 10:30
Insight
Birdzell: Startups should hire first 5–10 engineers globally before co-locating
“What I saw work really, really well for the first five to 10 software engineering hires in my last company was the founders focused on getting the absolute best talent they could anywhere in the world. And only as we got bigger did we start hiring for the home…”
Luther Birdzell Mar 20, 2019 ▶ 11:45
Disclosure
Birdzell: Oil and Gas Analytics plans Q4 Series A fundraise
“We are planning to go to the market in Q-IV to do a series A.”
Luther Birdzell Mar 20, 2019 ▶ 12:37
Assertion Supported
Birdzell: Oil and Gas Analytics raised under $3M over five years
“The money we've raised over the past five years is less than three million.”
Luther Birdzell Mar 20, 2019 ▶ 12:48
Assertion Not checkable as stated
Oil and Gas Analytics' customer acquisition cost is $5K to $50K
“Our lowest cost of bringing in a customer so far has probably been in like the five K range total. It's happened, you know, very quickly local customer. On the outside we haven't invested more than 50 yet in bringing a customer on board.”
Luther Birdzell Mar 20, 2019 ▶ 15:07
Prediction Not checkable as stated
Birdzell: Oil and Gas Analytics on track for over 300% growth
“We're on track to do over 300% growth this in 2018. And believe we can continue that growth rate through 19 as well.”
Luther Birdzell Mar 20, 2019 ▶ 16:17
Assertion Not checkable as stated
Birdzell: Oil and Gas Analytics generates over $50K monthly revenue
“We have more than 50 K a month in revenue.”
Luther Birdzell Mar 20, 2019 ▶ 17:00
Made with StarZero

Turn any episode into a week of clips.

This entire site, over 2,600 episodes transcribed, diarized, checked and made playable, runs on the StarZero media pipeline. Drop in your own episode and the podcast clipper finds the moments worth sharing, cuts them, captions them, and reframes them for every feed.

Try the podcast clipper Learn more