May 30, 2017 · 27m · top-founders

675: Would you acquire Mattermark? Artesian $700k MRR, $40M Raised w/ CEO Andrew Yates

Andrew Yates · 14m spoken Nathan Latka · 10m spoken
0:00 / 0:00

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In this episode of The Top Podcast, host Nathan Latka interviews Andrew Yates, CEO of Artesian, exploring how the contextual sales intelligence platform scaled to $700k in MRR across 120 enterprise customers while transitioning from high venture burn to cash-flow profitability. Yates shares detailed unit economics, machine learning differentiation strategies, and insights on SaaS industry consolidation and governance.

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 42.7% of the talking time here. How this is scored →

Nathan as informed peer 4.9 Guest teaching 2.3 Guest disagreement 0.4 Nathan pushing back 2.2
05100:0010:0020:000:54–3:31 · Nathan as informed peer 3/10 Preview of Upcoming Episode with Mike Wynn Latka introduces the company and prompts Yates to explain Artesian's core value proposition and product architecture. Yates explains their combination of firmographic data and real-time contextual triggers using NLP in an informative, cooperative manner.3:32–6:24 · Nathan as informed peer 6/10 Customer Base, Seat Metrics, and Enterprise Pricing Latka performs live math on ARPU and catches a discrepancy in the 30,000 subscriber count. He directly pushes Yates to clarify whether they have 30k unique enterprise customers or 30k seats across 120 accounts.6:24–9:18 · Nathan as informed peer 6/10 Revenue Performance, Burn Reduction, and Retention Metrics Latka investigates historical cash burn and pinpoints the monthly recurring revenue at approximately $700k. He also drills into retention definitions, making sure Yates distinguishes between logo retention and net revenue retention.9:18–11:28 · Nathan as informed peer 5/10 Machine Learning Differentiation vs. Human Research Models Latka challenges Yates on how Artesian differentiates from DiscoverOrg, FullContact, and Clearbit given shared data sourcing. Yates explains his machine-learning differentiation versus human researcher models using a Savile Row tailored suit analogy.11:28–14:28 · Nathan as informed peer 5/10 Industry Consolidation Trends and M&A Strategy Latka probes strategic M&A possibilities by asking whether Artesian would acquire Mattermark. Yates discusses macro consolidation trends in sales intelligence and details their capital runway and bridge history.14:29–16:42 · Nathan as informed peer 4/10 User Engagement, CAC Dynamics, and Platform Gamification Latka questions Yates on CAC and daily active engagement across the 30k seat base. Yates explains their gamified Social Seller Score and high daily engagement benchmarks.16:42–20:13 · Nathan as informed peer 6/10 Customer Lifetime Value and Multi-Year Enterprise Contracts Latka rapidly calculates customer lifetime value at $370k based on Yates's 5.2-year retention metric, prompting Yates to joke that Latka should join his finance team. Latka then drills into cap table ownership splits.20:14–24:17 · Nathan as informed peer 3/10 Mid-Roll Sponsor Break: Superfood Travel Packets Latka reads a mid-roll sponsor segment before transitioning into the Famous Five rapid-fire questions. Latka presses on operational tools when Yates initially answers with his own product.24:17–25:10 · Nathan as informed peer 6/10 Interview Synthesis and Artesian Metrics Summary Latka delivers an exhaustive, rapid summary synthesizing all of Artesian's core metrics, funding numbers, and unit economics without interruption before wrapping the episode.0:54–3:31 · Guest teaching 2/10 Preview of Upcoming Episode with Mike Wynn Latka introduces the company and prompts Yates to explain Artesian's core value proposition and product architecture. Yates explains their combination of firmographic data and real-time contextual triggers using NLP in an informative, cooperative manner.3:32–6:24 · Guest teaching 3/10 Customer Base, Seat Metrics, and Enterprise Pricing Latka performs live math on ARPU and catches a discrepancy in the 30,000 subscriber count. He directly pushes Yates to clarify whether they have 30k unique enterprise customers or 30k seats across 120 accounts.6:24–9:18 · Guest teaching 2/10 Revenue Performance, Burn Reduction, and Retention Metrics Latka investigates historical cash burn and pinpoints the monthly recurring revenue at approximately $700k. He also drills into retention definitions, making sure Yates distinguishes between logo retention and net revenue retention.9:18–11:28 · Guest teaching 5/10 Machine Learning Differentiation vs. Human Research Models Latka challenges Yates on how Artesian differentiates from DiscoverOrg, FullContact, and Clearbit given shared data sourcing. Yates explains his machine-learning differentiation versus human researcher models using a Savile Row tailored suit analogy.11:28–14:28 · Guest teaching 2/10 Industry Consolidation Trends and M&A Strategy Latka probes strategic M&A possibilities by asking whether Artesian would acquire Mattermark. Yates discusses macro consolidation trends in sales intelligence and details their capital runway and bridge history.14:29–16:42 · Guest teaching 3/10 User Engagement, CAC Dynamics, and Platform Gamification Latka questions Yates on CAC and daily active engagement across the 30k seat base. Yates explains their gamified Social Seller Score and high daily engagement benchmarks.16:42–20:13 · Guest teaching 2/10 Customer Lifetime Value and Multi-Year Enterprise Contracts Latka rapidly calculates customer lifetime value at $370k based on Yates's 5.2-year retention metric, prompting Yates to joke that Latka should join his finance team. Latka then drills into cap table ownership splits.20:14–24:17 · Guest teaching 2/10 Mid-Roll Sponsor Break: Superfood Travel Packets Latka reads a mid-roll sponsor segment before transitioning into the Famous Five rapid-fire questions. Latka presses on operational tools when Yates initially answers with his own product.24:17–25:10 · Guest teaching 0/10 Interview Synthesis and Artesian Metrics Summary Latka delivers an exhaustive, rapid summary synthesizing all of Artesian's core metrics, funding numbers, and unit economics without interruption before wrapping the episode.0:54–3:31 · Guest disagreement 0/10 Preview of Upcoming Episode with Mike Wynn Latka introduces the company and prompts Yates to explain Artesian's core value proposition and product architecture. Yates explains their combination of firmographic data and real-time contextual triggers using NLP in an informative, cooperative manner.3:32–6:24 · Guest disagreement 1/10 Customer Base, Seat Metrics, and Enterprise Pricing Latka performs live math on ARPU and catches a discrepancy in the 30,000 subscriber count. He directly pushes Yates to clarify whether they have 30k unique enterprise customers or 30k seats across 120 accounts.6:24–9:18 · Guest disagreement 1/10 Revenue Performance, Burn Reduction, and Retention Metrics Latka investigates historical cash burn and pinpoints the monthly recurring revenue at approximately $700k. He also drills into retention definitions, making sure Yates distinguishes between logo retention and net revenue retention.9:18–11:28 · Guest disagreement 1/10 Machine Learning Differentiation vs. Human Research Models Latka challenges Yates on how Artesian differentiates from DiscoverOrg, FullContact, and Clearbit given shared data sourcing. Yates explains his machine-learning differentiation versus human researcher models using a Savile Row tailored suit analogy.11:28–14:28 · Guest disagreement 1/10 Industry Consolidation Trends and M&A Strategy Latka probes strategic M&A possibilities by asking whether Artesian would acquire Mattermark. Yates discusses macro consolidation trends in sales intelligence and details their capital runway and bridge history.14:29–16:42 · Guest disagreement 0/10 User Engagement, CAC Dynamics, and Platform Gamification Latka questions Yates on CAC and daily active engagement across the 30k seat base. Yates explains their gamified Social Seller Score and high daily engagement benchmarks.16:42–20:13 · Guest disagreement 0/10 Customer Lifetime Value and Multi-Year Enterprise Contracts Latka rapidly calculates customer lifetime value at $370k based on Yates's 5.2-year retention metric, prompting Yates to joke that Latka should join his finance team. Latka then drills into cap table ownership splits.20:14–24:17 · Guest disagreement 0/10 Mid-Roll Sponsor Break: Superfood Travel Packets Latka reads a mid-roll sponsor segment before transitioning into the Famous Five rapid-fire questions. Latka presses on operational tools when Yates initially answers with his own product.24:17–25:10 · Guest disagreement 0/10 Interview Synthesis and Artesian Metrics Summary Latka delivers an exhaustive, rapid summary synthesizing all of Artesian's core metrics, funding numbers, and unit economics without interruption before wrapping the episode.0:54–3:31 · Nathan pushing back 1/10 Preview of Upcoming Episode with Mike Wynn Latka introduces the company and prompts Yates to explain Artesian's core value proposition and product architecture. Yates explains their combination of firmographic data and real-time contextual triggers using NLP in an informative, cooperative manner.3:32–6:24 · Nathan pushing back 4/10 Customer Base, Seat Metrics, and Enterprise Pricing Latka performs live math on ARPU and catches a discrepancy in the 30,000 subscriber count. He directly pushes Yates to clarify whether they have 30k unique enterprise customers or 30k seats across 120 accounts.6:24–9:18 · Nathan pushing back 3/10 Revenue Performance, Burn Reduction, and Retention Metrics Latka investigates historical cash burn and pinpoints the monthly recurring revenue at approximately $700k. He also drills into retention definitions, making sure Yates distinguishes between logo retention and net revenue retention.9:18–11:28 · Nathan pushing back 3/10 Machine Learning Differentiation vs. Human Research Models Latka challenges Yates on how Artesian differentiates from DiscoverOrg, FullContact, and Clearbit given shared data sourcing. Yates explains his machine-learning differentiation versus human researcher models using a Savile Row tailored suit analogy.11:28–14:28 · Nathan pushing back 3/10 Industry Consolidation Trends and M&A Strategy Latka probes strategic M&A possibilities by asking whether Artesian would acquire Mattermark. Yates discusses macro consolidation trends in sales intelligence and details their capital runway and bridge history.14:29–16:42 · Nathan pushing back 2/10 User Engagement, CAC Dynamics, and Platform Gamification Latka questions Yates on CAC and daily active engagement across the 30k seat base. Yates explains their gamified Social Seller Score and high daily engagement benchmarks.16:42–20:13 · Nathan pushing back 2/10 Customer Lifetime Value and Multi-Year Enterprise Contracts Latka rapidly calculates customer lifetime value at $370k based on Yates's 5.2-year retention metric, prompting Yates to joke that Latka should join his finance team. Latka then drills into cap table ownership splits.20:14–24:17 · Nathan pushing back 2/10 Mid-Roll Sponsor Break: Superfood Travel Packets Latka reads a mid-roll sponsor segment before transitioning into the Famous Five rapid-fire questions. Latka presses on operational tools when Yates initially answers with his own product.24:17–25:10 · Nathan pushing back 0/10 Interview Synthesis and Artesian Metrics Summary Latka delivers an exhaustive, rapid summary synthesizing all of Artesian's core metrics, funding numbers, and unit economics without interruption before wrapping the episode.

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

0:00 · Nathan 65.4% · guest 34.6%0:00 · Nathan 65.4% · guest 34.6%3:00 · Nathan 27.2% · guest 72.8%3:00 · Nathan 27.2% · guest 72.8%6:00 · Nathan 34.8% · guest 65.2%6:00 · Nathan 34.8% · guest 65.2%9:00 · Nathan 37.8% · guest 62.2%9:00 · Nathan 37.8% · guest 62.2%12:00 · Nathan 25.4% · guest 74.6%12:00 · Nathan 25.4% · guest 74.6%15:00 · Nathan 15.4% · guest 84.6%15:00 · Nathan 15.4% · guest 84.6%18:00 · Nathan 58.4% · guest 41.6%18:00 · Nathan 58.4% · guest 41.6%21:00 · Nathan 36.4% · guest 63.6%21:00 · Nathan 36.4% · guest 63.6%24:00 · Nathan 91.5% · guest 8.5%24:00 · Nathan 91.5% · guest 8.5%27:00 · Nathan 0% · guest 0%27:00 · Nathan 0% · guest 0%
Sharpest disagreement ▶ 11:15 Friendly deflection regarding Hugo Boss and off-the-shelf tools

In a very collegial interview, Yates playfully walks back a comment comparing off-the-shelf tools to Hugo Boss after Latka jokes about lost sponsorships.

Hardest push from Nathan ▶ 5:09 Latka confronts math conflict on customer counts

Latka stops Yates when the 30k customer number yields an impossibly high $30M MRR calculation, pushing Yates to clarify that 30,000 represents individual user seats rather than enterprise logos.

Biggest teaching moment ▶ 9:53 Yates delineates human research versus automated machine learning models

Yates provides a deep conceptual breakdown of why Artesian does not compete with DiscoverOrg, educating the host on how machine learning triggers scale differently than human research teams.

Nathan holds their own ▶ 18:07 Latka models exact contract LTV on the fly

Latka instantly computes 62 months at $6k/month to reach a $370k enterprise customer lifetime value, demonstrating immediate financial modeling mastery.

the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Preview of Upcoming Episode with Mike Wynn 3201 Latka introduces the company and prompts Yates to explain Artesian's core value proposition and product architecture. Yates explains their combination of firmographic data and real-time contextual triggers using NLP in an informative, cooperative manner.
Customer Base, Seat Metrics, and Enterprise Pricing 6314 Latka performs live math on ARPU and catches a discrepancy in the 30,000 subscriber count. He directly pushes Yates to clarify whether they have 30k unique enterprise customers or 30k seats across 120 accounts.
Revenue Performance, Burn Reduction, and Retention Metrics 6213 Latka investigates historical cash burn and pinpoints the monthly recurring revenue at approximately $700k. He also drills into retention definitions, making sure Yates distinguishes between logo retention and net revenue retention.
Machine Learning Differentiation vs. Human Research Models 5513 Latka challenges Yates on how Artesian differentiates from DiscoverOrg, FullContact, and Clearbit given shared data sourcing. Yates explains his machine-learning differentiation versus human researcher models using a Savile Row tailored suit analogy.
Industry Consolidation Trends and M&A Strategy 5213 Latka probes strategic M&A possibilities by asking whether Artesian would acquire Mattermark. Yates discusses macro consolidation trends in sales intelligence and details their capital runway and bridge history.
User Engagement, CAC Dynamics, and Platform Gamification 4302 Latka questions Yates on CAC and daily active engagement across the 30k seat base. Yates explains their gamified Social Seller Score and high daily engagement benchmarks.
Customer Lifetime Value and Multi-Year Enterprise Contracts 6202 Latka rapidly calculates customer lifetime value at $370k based on Yates's 5.2-year retention metric, prompting Yates to joke that Latka should join his finance team. Latka then drills into cap table ownership splits.
Mid-Roll Sponsor Break: Superfood Travel Packets 3202 Latka reads a mid-roll sponsor segment before transitioning into the Famous Five rapid-fire questions. Latka presses on operational tools when Yates initially answers with his own product.
Interview Synthesis and Artesian Metrics Summary 6000 Latka delivers an exhaustive, rapid summary synthesizing all of Artesian's core metrics, funding numbers, and unit economics without interruption before wrapping the episode.

Statements from this episode (21)

Assertion Not checkable as stated
Artesian serves 30,000 paying seats across 100 enterprise customers
“We're at about 30,000 paying subscribers, got over a hundred large enterprise customers companies like Cisco, Hewlett Packard Enterprise, NetApp, American Express, Lloyds, Barclays, HSBC, Ernst & Young, KPMG.”
Andrew Yates May 30, 2017 ▶ 3:48
Prediction Didn’t hold up
Artesian targets $10M to $15M run rate with 60 employees
“So it's 60 people. Our run rate this year will be in around about the 10 to fifteen million dollar range.”
Andrew Yates May 30, 2017 ▶ 4:30
Assertion Not checkable as stated
Artesian contract sizes range from $10,000 to over $2 million annually
“Our subscribers are paying anything from 10,000 dollars a year to over two million dollars annually is our largest contract.”
Andrew Yates May 30, 2017 ▶ 4:48
Assertion Not checkable as stated
Artesian has 68% of its annual ARR goal already under contract
“And about 68% of our ARR goal for next year or this year that we're in is currently already contracted.”
Andrew Yates May 30, 2017 ▶ 5:03
Prediction Not checkable as stated
Artesian expects to reach cash flow positivity by May 2017
“So we're actually striving towards Profitability and cash flow positivity, which we should hit around about May this year.”
Andrew Yates May 30, 2017 ▶ 6:52
Disclosure
Artesian regularly burned $300k-$400k monthly in its early stages
“We were regularly, you know, seeing off between three and 400,000 dollars a month in the early days.”
Andrew Yates May 30, 2017 ▶ 7:04
Disclosure
Artesian raised $40M in equity and debt to fuel growth
“We, you know, we raised about forty million of equity and debt to fund that, and that helped us, you know, drive growth in the 50 to 70% range.”
Andrew Yates May 30, 2017 ▶ 7:13
Disclosure
Artesian's largest customer has deployed 4,500 enterprise seats
“Our largest customer with, you know, at the higher end of the tariff scale would be one of the banks in the UK that has about four and a half thousand seats deployed.”
Andrew Yates May 30, 2017 ▶ 8:06
Disclosure
Artesian maintains 93% gross and 120% net revenue retention
“Our customer retention is running at around about 93% gross and a 120 percent net.”
Andrew Yates May 30, 2017 ▶ 8:24
Disclosure
Artesian averaged a +43 Net Promoter Score over 12 months
“We also run a net promoter score program to check in on how satisfied our customers are. And that's running at an average over the last 12 months of plus 43.”
Andrew Yates May 30, 2017 ▶ 8:54
Assertion Contradicted
Artesian ranks second on G2 Crowd behind DiscoverOrg
“We're now number two in the G two crowd ranking in terms of the most popular sales intelligence platform, just behind the guys at discover org.”
Andrew Yates May 30, 2017 ▶ 9:06
Assertion Supported
Latka: DiscoverOrg Generates Roughly $5M Monthly Revenue
“He, you know, he shared with me Henry in that episode that they're doing about five million ish per month in revenue”
Nathan Latka May 30, 2017 ▶ 9:19
Prediction Not checkable as stated
Yates: Sales intelligence consolidation is inevitable after D&B Avention deal
“I think that a market consolidation exercises is, is, is inevitable. If you look at the, you know, recent acquisition of invention by Dun & Bradstreet, I think that's going to create a little bit of a ripple effect.”
Andrew Yates May 30, 2017 ▶ 11:52
Disclosure
Yates: Only Artesian's CEO manages potential M&A deal sourcing
“The only person that focuses on that or dedicates any percentage of their time is, is myself.”
Andrew Yates May 30, 2017 ▶ 12:45
Disclosure
Yates: Artesian Has Two Years of Cash Runway Without More Funding
“So we are in a position where we've got adequate cash resources to keep going without any more investment for the next two years.”
Andrew Yates May 30, 2017 ▶ 13:47
Assertion Not checkable as stated
Artesian tracks a one-year CAC payback period on annual contracts
“We're tracking on, on around about one X in year one, which I, you know, I believe is, is, is world-class”
Andrew Yates May 30, 2017 ▶ 14:39
Assertion Not checkable as stated
Yates: Artesian maintains around 89% average daily user engagement
“We're running at around about 89% average daily user engagement, which for a tool set or platform in our space is, is, is really, really high.”
Andrew Yates May 30, 2017 ▶ 15:42
Assertion Not checkable as stated
Artesian CEO: 80% of revenue comes from large enterprise customers
“We've got some small, medium business customers but it's a classic kind of, you know, 80% of the revenue comes from the, you know, larger enterprise customers”
Andrew Yates May 30, 2017 ▶ 16:56
Assertion Not checkable as stated
Artesian CEO: Enterprise customer retention averages 5.2 years
“So I'm measuring it in years, at the moment it's tracking at 5.2 years.”
Andrew Yates May 30, 2017 ▶ 17:18
Assertion Not checkable as stated
Artesian CEO: HSBC signed a 3-year renewal, reaching 7 years with Artesian
“I mean, HSBC, I just signed another three-year deal. That'll be seven years of continual service.”
Andrew Yates May 30, 2017 ▶ 17:39
Disclosure
Yates: 50% of Artesian's equity is institutionally owned
“50% of our of our equity is owned by an institution that's invested with an expectation they're going to see a return.”
Andrew Yates May 30, 2017 ▶ 19:33
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