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May 10, 2018 · 21m · top-founders

1020 Urban Outfitters Inventory Management Tool Breaks $6m in ARR

John Andrews · 12m spoken Nathan Latka · 6m 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, host Nathan Latka interviews Celect executive John Andrews on how the MIT-born predictive analytics platform optimizes retail inventory, scaling enterprise SaaS revenues to nearly $6 million in ARR.

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 35.6% of the talking time here. How this is scored →

Nathan as informed peer 5.0 Guest teaching 3.8 Guest disagreement 1.5 Nathan pushing back 3.0
05100:0010:0020:004:54–9:36 · Nathan as informed peer 4/10 Understanding Customer Preference via the Choice Engine Nathan probes how the choice engine is trained compared to giant data collectors like Amazon, wondering if physical store tracking requires RFID. John educates Nathan on why granular in-store tracking isn't necessary and explains how choice modeling derives strong signals from sparse retail transaction data.9:36–12:38 · Nathan as informed peer 5/10 SaaS Subscription Model and Enterprise Contract Economics Nathan interrupts John's feature walkthrough to pin down exact customer price points and contract sizes. John shares typical ACVs of $400k-$500k and enterprise LTVs in the $3M-$4M range, with both agreeing that fashion retail bankruptcies present the primary churn risk.12:38–15:29 · Nathan as informed peer 5/10 Company Founding, Venture Funding, and Team Scaling Nathan explores the company origin, VC funding history, and team headcount, inquiring whether John was an EIR. John explains how standard SaaS cohort metrics break down when dealing with a high-touch enterprise model with fewer than twenty total accounts.15:32–18:50 · Nathan as informed peer 6/10 Sponsor Break: Mobile Document Signing with SignEasy After an ad read, Nathan quickly runs mental math on ARR and growth metrics, estimating past run-rates and pushing John on whether he is secretly raising or selling the company. John clarifies ARR figures and dismisses the fundraising assumption, asserting they are well-capitalized.4:54–9:36 · Guest teaching 6/10 Understanding Customer Preference via the Choice Engine Nathan probes how the choice engine is trained compared to giant data collectors like Amazon, wondering if physical store tracking requires RFID. John educates Nathan on why granular in-store tracking isn't necessary and explains how choice modeling derives strong signals from sparse retail transaction data.9:36–12:38 · Guest teaching 2/10 SaaS Subscription Model and Enterprise Contract Economics Nathan interrupts John's feature walkthrough to pin down exact customer price points and contract sizes. John shares typical ACVs of $400k-$500k and enterprise LTVs in the $3M-$4M range, with both agreeing that fashion retail bankruptcies present the primary churn risk.12:38–15:29 · Guest teaching 4/10 Company Founding, Venture Funding, and Team Scaling Nathan explores the company origin, VC funding history, and team headcount, inquiring whether John was an EIR. John explains how standard SaaS cohort metrics break down when dealing with a high-touch enterprise model with fewer than twenty total accounts.15:32–18:50 · Guest teaching 3/10 Sponsor Break: Mobile Document Signing with SignEasy After an ad read, Nathan quickly runs mental math on ARR and growth metrics, estimating past run-rates and pushing John on whether he is secretly raising or selling the company. John clarifies ARR figures and dismisses the fundraising assumption, asserting they are well-capitalized.4:54–9:36 · Guest disagreement 2/10 Understanding Customer Preference via the Choice Engine Nathan probes how the choice engine is trained compared to giant data collectors like Amazon, wondering if physical store tracking requires RFID. John educates Nathan on why granular in-store tracking isn't necessary and explains how choice modeling derives strong signals from sparse retail transaction data.9:36–12:38 · Guest disagreement 1/10 SaaS Subscription Model and Enterprise Contract Economics Nathan interrupts John's feature walkthrough to pin down exact customer price points and contract sizes. John shares typical ACVs of $400k-$500k and enterprise LTVs in the $3M-$4M range, with both agreeing that fashion retail bankruptcies present the primary churn risk.12:38–15:29 · Guest disagreement 1/10 Company Founding, Venture Funding, and Team Scaling Nathan explores the company origin, VC funding history, and team headcount, inquiring whether John was an EIR. John explains how standard SaaS cohort metrics break down when dealing with a high-touch enterprise model with fewer than twenty total accounts.15:32–18:50 · Guest disagreement 2/10 Sponsor Break: Mobile Document Signing with SignEasy After an ad read, Nathan quickly runs mental math on ARR and growth metrics, estimating past run-rates and pushing John on whether he is secretly raising or selling the company. John clarifies ARR figures and dismisses the fundraising assumption, asserting they are well-capitalized.4:54–9:36 · Nathan pushing back 3/10 Understanding Customer Preference via the Choice Engine Nathan probes how the choice engine is trained compared to giant data collectors like Amazon, wondering if physical store tracking requires RFID. John educates Nathan on why granular in-store tracking isn't necessary and explains how choice modeling derives strong signals from sparse retail transaction data.9:36–12:38 · Nathan pushing back 3/10 SaaS Subscription Model and Enterprise Contract Economics Nathan interrupts John's feature walkthrough to pin down exact customer price points and contract sizes. John shares typical ACVs of $400k-$500k and enterprise LTVs in the $3M-$4M range, with both agreeing that fashion retail bankruptcies present the primary churn risk.12:38–15:29 · Nathan pushing back 2/10 Company Founding, Venture Funding, and Team Scaling Nathan explores the company origin, VC funding history, and team headcount, inquiring whether John was an EIR. John explains how standard SaaS cohort metrics break down when dealing with a high-touch enterprise model with fewer than twenty total accounts.15:32–18:50 · Nathan pushing back 4/10 Sponsor Break: Mobile Document Signing with SignEasy After an ad read, Nathan quickly runs mental math on ARR and growth metrics, estimating past run-rates and pushing John on whether he is secretly raising or selling the company. John clarifies ARR figures and dismisses the fundraising assumption, asserting they are well-capitalized.

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

0:00 · Nathan 56% · guest 44%0:00 · Nathan 56% · guest 44%3:00 · Nathan 10.5% · guest 89.5%3:00 · Nathan 10.5% · guest 89.5%6:00 · Nathan 13.7% · guest 86.3%6:00 · Nathan 13.7% · guest 86.3%9:00 · Nathan 20.1% · guest 79.9%9:00 · Nathan 20.1% · guest 79.9%12:00 · Nathan 38.9% · guest 61.1%12:00 · Nathan 38.9% · guest 61.1%15:00 · Nathan 61.8% · guest 38.2%15:00 · Nathan 61.8% · guest 38.2%18:00 · Nathan 51.9% · guest 48.1%18:00 · Nathan 51.9% · guest 48.1%21:00 · Nathan 11% · guest 89%21:00 · Nathan 11% · guest 89%
Sharpest disagreement ▶ 18:35 John denies acquisition or fundraising rumors

When Nathan insists that being a year out from a round means Select is either raising or in M&A talks, John firmly dismisses both premises and states they have plenty of cash in the bank.

 Hardest push from Nathan ▶ 10:07 Nathan cuts off product description for ACV metrics

Nathan interrupts John's descriptive explanation of the software interface to forcefully redirect the discussion toward specific annual customer contract values.

 Biggest teaching moment ▶ 8:17 John clarifies signal extraction from sparse retail data

John corrects Nathan's assumption that effective modeling requires invasive physical trackers, explaining the mechanics of choice engine algorithms on sparse datasets.

 Nathan holds their own ▶ 17:11 Nathan calculates past run-rate from growth multipliers

Nathan demonstrates financial acumen by instantaneously calculating historical MRR and ARR figures based on John's 2.5x annual growth rate.
the scores for every segment, with the reasoning behind each
ChapterTopicNathan as informed peerGuest teachingGuest disagreementNathan pushing backWhy
Understanding Customer Preference via the Choice Engine 4623 Nathan probes how the choice engine is trained compared to giant data collectors like Amazon, wondering if physical store tracking requires RFID. John educates Nathan on why granular in-store tracking isn't necessary and explains how choice modeling derives strong signals from sparse retail transaction data.
SaaS Subscription Model and Enterprise Contract Economics 5213 Nathan interrupts John's feature walkthrough to pin down exact customer price points and contract sizes. John shares typical ACVs of $400k-$500k and enterprise LTVs in the $3M-$4M range, with both agreeing that fashion retail bankruptcies present the primary churn risk.
Company Founding, Venture Funding, and Team Scaling 5412 Nathan explores the company origin, VC funding history, and team headcount, inquiring whether John was an EIR. John explains how standard SaaS cohort metrics break down when dealing with a high-touch enterprise model with fewer than twenty total accounts.
Sponsor Break: Mobile Document Signing with SignEasy 6324 After an ad read, Nathan quickly runs mental math on ARR and growth metrics, estimating past run-rates and pushing John on whether he is secretly raising or selling the company. John clarifies ARR figures and dismisses the fundraising assumption, asserting they are well-capitalized.

Statements from this episode (12)

Disclosure
Andrews: Celect counts Urban Outfitters and Saks Fifth Avenue as customers
“Our customers include folks like Urban Outfitters, Anthropologie, Free People, Aldo, Montreal, up in Montreal, the shoe manufacturer, designer, and retailer, Saks Fifth Avenue, etc.”
John Andrews May 10, 2018 ▶ 3:28
Opinion
Andrews: Retail inventory planning is mostly gut instinct and Excel
“The way that these decisions are made today is generally based on gut instinct and Excel spreadsheets, right?”
John Andrews May 10, 2018 ▶ 4:35
Assertion Not checkable as stated
Andrews: Celect delivers 5-7% revenue growth and up to 14% margin lift
“When you do that right, we've seen customers with anywhere from You know, at points, five to seven percent increase in revenue to, you know, upwards of, you know, 13 to 14% increase in gross margin.”
John Andrews May 10, 2018 ▶ 7:39
Insight
Andrews: Retail choice modeling doesn't require granular in-store sensor tracking
“The reality is, Nathan, is that you don't actually need that level of granularity to get the signal out of understanding customer preference, right? Part of the technology, you need to identify what the selection set is that people are likely looking at just b…”
John Andrews May 10, 2018 ▶ 8:28
Insight
Andrews: Traditional retailers have sparse customer-product interaction data
“The challenge that other retailers have, even though they feel as though they have a lot of data, the issue is, is that they actually have very sparse data about an individual customer that And individual products and specifically with those customers interact…”
John Andrews May 10, 2018 ▶ 9:03
Disclosure
Andrews: Celect's starting contracts range from $400k to $500k per year
“The starting point is going to be somewhere between, you know, 400 to, call it 400 to 500 K. Okay. Per year.”
John Andrews May 10, 2018 ▶ 10:39
Disclosure
Andrews: Celect customer lifetime value is typically $3M to $4M
“Millions of dollars. It's generally in the three to four million dollar range.”
John Andrews May 10, 2018 ▶ 11:22
Disclosure
Andrews: Celect has about 15 enterprise customers
“So we're in the middle teens at this point.”
John Andrews May 10, 2018 ▶ 14:05
Disclosure
Andrews: Celect had two customer churns in four years
“So we've had two customers who've churned over the past four years.”
John Andrews May 10, 2018 ▶ 14:24
Insight
Andrews: Low-volume enterprise SaaS makes standard churn dashboards difficult
“It's a really hard thing to, it's a really hard thing to measure, right? If our model was, you know, Hey, download something from you know, from our website, put your credit card in, we've got thousands of customers. You can measure based on cohorts much, much…”
John Andrews May 10, 2018 ▶ 14:38
Assertion Not checkable as stated
Andrews: Celect grew revenue roughly 2.5x year-over-year in 2017
“So last year was it's about two and a half X.”
John Andrews May 10, 2018 ▶ 16:48
Assertion Not checkable as stated
Andrews: Celect achieves a roughly six-month CAC payback period
“So our payback period, it's been, you know, it can be in the six month range.”
John Andrews May 10, 2018 ▶ 18:02
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