StarZero All shows Try the podcast clipper →

Sep 30, 2016 · 27m · top-founders

EP 433: $19M Raised, 0 to 1M Active Users for Copmetitive Intelligence Platform Owler with CEO Jim Fowler

Jim Fowler · 14m spoken Nathan Latka · 9m 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, host Nathan Latka interviews Owler founder and CEO Jim Fowler about scaling a crowdsourced competitive intelligence platform to over 700,000 active users, defending private data legality, and driving enterprise revenue via API licensing.

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 38.3% of the talking time here. How this is scored →

Nathan as informed peer 4.8 Guest teaching 4.0 Guest disagreement 1.5 Nathan pushing back 3.5
05100:0010:0020:001:42–5:17 · Nathan as informed peer 5/10 Introducing Jim Fowler and Owler's Competitive Intelligence Platform Nathan pulls up his own acquired company (Heyo) on Owler to test the platform in real time, validating Owler's competitor detection while questioning data sources in a supportive tone.5:19–8:32 · Nathan as informed peer 7/10 Crowdsourcing Methodology, Data Accuracy, and the Owler Challenge Nathan pushes hard after finding Hootsuite's revenue listed as an absurd $5.4B, demanding to know how the algorithm arrives at such numbers. Jim concedes the error openly and explains how crowd inputs correct algorithmic baselines.8:33–14:26 · Nathan as informed peer 5/10 Owler's Monetization Strategy and Enterprise Data Licensing Deals Nathan presses Jim to define active users and explain enterprise data buyers, prompting Jim to elaborate on the 'Tom Sawyer' crowdsourcing model and large enterprise licensing deals.14:26–20:51 · Nathan as informed peer 6/10 Scaling Milestones, Revenue Forecasts, and Private Data Legality Nathan challenges Jim on SLA guarantees and why obtaining private revenue figures would be considered illegal. Jim schools Nathan on corporate NDAs and differences between European disclosure mandates and US estimate-based models.20:51–23:04 · Nathan as informed peer 4/10 Handling Legal Objections and Scaling the Global Company Database Nathan poses a hypothetical cease-and-desist scenario from an angry CEO. Jim firmly explains his legal standing and database policies regarding public data and trademarked logos.23:07–27:27 · Nathan as informed peer 2/10 Mid-Roll Sponsor Break: Building Software with Toptal The segment consists of an ad read for Toptal, a brief check on Owler's India operations, and the standard Famous Five rapid-fire questions.1:42–5:17 · Guest teaching 3/10 Introducing Jim Fowler and Owler's Competitive Intelligence Platform Nathan pulls up his own acquired company (Heyo) on Owler to test the platform in real time, validating Owler's competitor detection while questioning data sources in a supportive tone.5:19–8:32 · Guest teaching 4/10 Crowdsourcing Methodology, Data Accuracy, and the Owler Challenge Nathan pushes hard after finding Hootsuite's revenue listed as an absurd $5.4B, demanding to know how the algorithm arrives at such numbers. Jim concedes the error openly and explains how crowd inputs correct algorithmic baselines.8:33–14:26 · Guest teaching 5/10 Owler's Monetization Strategy and Enterprise Data Licensing Deals Nathan presses Jim to define active users and explain enterprise data buyers, prompting Jim to elaborate on the 'Tom Sawyer' crowdsourcing model and large enterprise licensing deals.14:26–20:51 · Guest teaching 6/10 Scaling Milestones, Revenue Forecasts, and Private Data Legality Nathan challenges Jim on SLA guarantees and why obtaining private revenue figures would be considered illegal. Jim schools Nathan on corporate NDAs and differences between European disclosure mandates and US estimate-based models.20:51–23:04 · Guest teaching 5/10 Handling Legal Objections and Scaling the Global Company Database Nathan poses a hypothetical cease-and-desist scenario from an angry CEO. Jim firmly explains his legal standing and database policies regarding public data and trademarked logos.23:07–27:27 · Guest teaching 1/10 Mid-Roll Sponsor Break: Building Software with Toptal The segment consists of an ad read for Toptal, a brief check on Owler's India operations, and the standard Famous Five rapid-fire questions.1:42–5:17 · Guest disagreement 0/10 Introducing Jim Fowler and Owler's Competitive Intelligence Platform Nathan pulls up his own acquired company (Heyo) on Owler to test the platform in real time, validating Owler's competitor detection while questioning data sources in a supportive tone.5:19–8:32 · Guest disagreement 2/10 Crowdsourcing Methodology, Data Accuracy, and the Owler Challenge Nathan pushes hard after finding Hootsuite's revenue listed as an absurd $5.4B, demanding to know how the algorithm arrives at such numbers. Jim concedes the error openly and explains how crowd inputs correct algorithmic baselines.8:33–14:26 · Guest disagreement 1/10 Owler's Monetization Strategy and Enterprise Data Licensing Deals Nathan presses Jim to define active users and explain enterprise data buyers, prompting Jim to elaborate on the 'Tom Sawyer' crowdsourcing model and large enterprise licensing deals.14:26–20:51 · Guest disagreement 3/10 Scaling Milestones, Revenue Forecasts, and Private Data Legality Nathan challenges Jim on SLA guarantees and why obtaining private revenue figures would be considered illegal. Jim schools Nathan on corporate NDAs and differences between European disclosure mandates and US estimate-based models.20:51–23:04 · Guest disagreement 3/10 Handling Legal Objections and Scaling the Global Company Database Nathan poses a hypothetical cease-and-desist scenario from an angry CEO. Jim firmly explains his legal standing and database policies regarding public data and trademarked logos.23:07–27:27 · Guest disagreement 0/10 Mid-Roll Sponsor Break: Building Software with Toptal The segment consists of an ad read for Toptal, a brief check on Owler's India operations, and the standard Famous Five rapid-fire questions.1:42–5:17 · Nathan pushing back 1/10 Introducing Jim Fowler and Owler's Competitive Intelligence Platform Nathan pulls up his own acquired company (Heyo) on Owler to test the platform in real time, validating Owler's competitor detection while questioning data sources in a supportive tone.5:19–8:32 · Nathan pushing back 7/10 Crowdsourcing Methodology, Data Accuracy, and the Owler Challenge Nathan pushes hard after finding Hootsuite's revenue listed as an absurd $5.4B, demanding to know how the algorithm arrives at such numbers. Jim concedes the error openly and explains how crowd inputs correct algorithmic baselines.8:33–14:26 · Nathan pushing back 3/10 Owler's Monetization Strategy and Enterprise Data Licensing Deals Nathan presses Jim to define active users and explain enterprise data buyers, prompting Jim to elaborate on the 'Tom Sawyer' crowdsourcing model and large enterprise licensing deals.14:26–20:51 · Nathan pushing back 5/10 Scaling Milestones, Revenue Forecasts, and Private Data Legality Nathan challenges Jim on SLA guarantees and why obtaining private revenue figures would be considered illegal. Jim schools Nathan on corporate NDAs and differences between European disclosure mandates and US estimate-based models.20:51–23:04 · Nathan pushing back 4/10 Handling Legal Objections and Scaling the Global Company Database Nathan poses a hypothetical cease-and-desist scenario from an angry CEO. Jim firmly explains his legal standing and database policies regarding public data and trademarked logos.23:07–27:27 · Nathan pushing back 1/10 Mid-Roll Sponsor Break: Building Software with Toptal The segment consists of an ad read for Toptal, a brief check on Owler's India operations, and the standard Famous Five rapid-fire questions.

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

0:00 · Nathan 84.9% · guest 15.1%0:00 · Nathan 84.9% · guest 15.1%3:00 · Nathan 24.7% · guest 75.3%3:00 · Nathan 24.7% · guest 75.3%6:00 · Nathan 32.8% · guest 67.2%6:00 · Nathan 32.8% · guest 67.2%9:00 · Nathan 12.4% · guest 87.6%9:00 · Nathan 12.4% · guest 87.6%12:00 · Nathan 24.6% · guest 75.4%12:00 · Nathan 24.6% · guest 75.4%15:00 · Nathan 31.4% · guest 68.6%15:00 · Nathan 31.4% · guest 68.6%18:00 · Nathan 24.4% · guest 75.6%18:00 · Nathan 24.4% · guest 75.6%21:00 · Nathan 40.8% · guest 59.2%21:00 · Nathan 40.8% · guest 59.2%24:00 · Nathan 61.2% · guest 38.8%24:00 · Nathan 61.2% · guest 38.8%27:00 · Nathan 99.5% · guest 0.5%27:00 · Nathan 99.5% · guest 0.5%
Sharpest disagreement ▶ 21:09 Firm dismissal of cease-and-desist threats

Jim firmly rejects the premise that companies can force Owler to take down public profile data, stating that only trademarked logos will be removed on request.

 Hardest push from Nathan ▶ 6:22 Nathan presses on the flawed 5.4B Hootsuite figure

Nathan refuses to let Jim brush off a bad data point, asking specifically what formula generated an inaccurate $5.4 billion revenue figure for Hootsuite.

 Biggest teaching moment ▶ 16:22 Jim breaks down private company disclosure laws and NDAs

Jim educates Nathan on international corporate disclosure regulations and explains why soliciting non-public financial information breaches employee NDAs.

 Nathan holds their own ▶ 20:19 Nathan decodes Jim's revenue-per-employee mental model

Nathan immediately identifies and explains the back-of-the-envelope cost structure calculation Jim is using to estimate private company revenue based on headcount.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Introducing Jim Fowler and Owler's Competitive Intelligence Platform 5301 Nathan pulls up his own acquired company (Heyo) on Owler to test the platform in real time, validating Owler's competitor detection while questioning data sources in a supportive tone.
Crowdsourcing Methodology, Data Accuracy, and the Owler Challenge 7427 Nathan pushes hard after finding Hootsuite's revenue listed as an absurd $5.4B, demanding to know how the algorithm arrives at such numbers. Jim concedes the error openly and explains how crowd inputs correct algorithmic baselines.
Owler's Monetization Strategy and Enterprise Data Licensing Deals 5513 Nathan presses Jim to define active users and explain enterprise data buyers, prompting Jim to elaborate on the 'Tom Sawyer' crowdsourcing model and large enterprise licensing deals.
Scaling Milestones, Revenue Forecasts, and Private Data Legality 6635 Nathan challenges Jim on SLA guarantees and why obtaining private revenue figures would be considered illegal. Jim schools Nathan on corporate NDAs and differences between European disclosure mandates and US estimate-based models.
Handling Legal Objections and Scaling the Global Company Database 4534 Nathan poses a hypothetical cease-and-desist scenario from an angry CEO. Jim firmly explains his legal standing and database policies regarding public data and trademarked logos.
Mid-Roll Sponsor Break: Building Software with Toptal 2101 The segment consists of an ad read for Toptal, a brief check on Owler's India operations, and the standard Famous Five rapid-fire questions.

Statements from this episode (14)

Assertion Not checkable as stated
Owler has nearly 700,000 active business users on its platform
“We've got almost 700,000 active business professionals using the platform as you mentioned that, you know, help outsmart their competition.”
Jim Fowler Sep 30, 2016 ▶ 2:42
Assertion Not checkable as stated
Most Owler data is user-generated rather than scraped
“Most of the data is input by users. We do do some crawling and scraping, but mostly it's around the user input.”
Jim Fowler Sep 30, 2016 ▶ 4:36
Opinion
Owler's crowdsourced data is more accurate than Hoover's and Dun & Bradstreet
“Pick five private companies that, you know, go pull the data off of Hoover's, which has done a Bradstreet data and pull the data off of our. And see who wins. We're kicking their butts. our crowd is, is just far more powerful than the few employees they can, …”
Jim Fowler Sep 30, 2016 ▶ 6:01
Disclosure
Owler doubled its user base over the preceding 90 days
“You know, we've doubled our user base over the last 90 days.”
Jim Fowler Sep 30, 2016 ▶ 8:19
Disclosure
Owler remained completely pre-revenue throughout 2015
“We're, we were pre-rev in 2015. We hadn't even started even pushing revenue.”
Jim Fowler Sep 30, 2016 ▶ 9:23
Disclosure
Owler has raised a total of $19M in venture funding
“You know, nineteen million dollars.”
Jim Fowler Sep 30, 2016 ▶ 9:39
Prediction Not checkable as stated
Owler expects to surpass 1M active users by year-end 2016
“You know, we're, we will end this year with over a million active, not registered active users on our system.”
Jim Fowler Sep 30, 2016 ▶ 10:10
Disclosure
Owler recently signed a data licensing contract over $100K
“We just signed a deal for, you know, a 100,000 dollar plus.”
Jim Fowler Sep 30, 2016 ▶ 11:01
Prediction Not publicly verifiable
Owler projects generating $3M to $5M in revenue in 2017
“I'm imagining we're going to do, you know, anywhere between three and five million in revenue and in 26, in 2017.”
Jim Fowler Sep 30, 2016 ▶ 15:19
Disclosure
Owler refuses to provide data accuracy SLAs to enterprise customers
“So no, there's no such thing as an SLA. We're very, very clear to our buyers that this data is an estimate.”
Jim Fowler Sep 30, 2016 ▶ 16:55
Insight
$100K to $120K revenue per employee is a solid baseline heuristic
“Basically a good back of the envelope guesstimate on revenue is a 100,000 dollars in, in revenue per employee, maybe a 120,000”
Jim Fowler Sep 30, 2016 ▶ 20:29
Assertion Not checkable as stated
Owler leverages public data rights, only removing trademarked logos upon request
“And if you're a registered business, we have every legal right to do it. There is one field that we will take off if someone requests and that's their logo. And then we just put in a, you know, a generic one that says this company, you know, will not authorize…”
Jim Fowler Sep 30, 2016 ▶ 21:37
Assertion Partly supported
Owler lists nearly 12M companies, targeting 20M by year-end 2016
“We have almost twelve million companies on and, you know, on, on plan to have about twenty million by the end of the year.”
Jim Fowler Sep 30, 2016 ▶ 22:13
Disclosure
Owler's entire engineering team is based in India
“Our entire engineering team is in India as well.”
Jim Fowler Sep 30, 2016 ▶ 24:51
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