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In This Together Series
“The Science of Re-establishing Growth”
Mark Roberge
Managing Director @ Stage 2 Capital
Prof @Harvard Business School
hello@salesimpactacademy.co.uk
Sales & Marketing Leaders
Webinar will be live at
4pm BST/8am PST
presents
The Science of Re-establishing
Growth
Where, When, and How?
Mark Roberge @markroberge
Managing Director @Stage2Capital
Senior Lecturer, Harvard Business School
Former CRO @HubSpot
3 @markroberge
When should we
begin scaling again?
The Science of Re-establishing Growth
What is product-market-fit?
#1 Product-Market Fit
Goal of Phase
#1 Product-Market Fit
Customer Retention
Annual Revenue Retention > 100%
Annual Customer Retention > 90%
Annual Revenue Retention = [ARR (start of year) – Churn + Upgrades] / ARR (start of year)
Annual Customer Retention = [#Customers (start of year) – Customer Churn] / # Customers (start of year)
The Science of Re-establishing Growth
Customer retention is the best quantifiable measure of product-market-fit
Pothole Alert!
But customer retention is a lagging
indicator. We need to identify a
leading indicator to customer
retention to identify when product-
market-fit is achieved.
A Scientific, Data-Driven Approach to Product-Market-Fit
Define a leading indicator to customer retention
[Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days
A Scientific, Data-Driven Approach to Product-Market-Fit
Industry examples of customer retention leading indicators
[Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days
70% of customers send 2,000+ team messages in the first 30
days
85% of customers upload 1 file in 1 folder on 1 device within 1
hour
80% of customers use 5 features out of the 25 features in
the platform within 60 days
% of customers that achieve customer retention leading indicator by month of tenure
A Scientific, Data-Driven Approach to Product-Market-Fit
Instrument customer acquisition cohorts to identify when product-market-fit is achieved
A Scientific, Data-Driven Approach to Product-Market-Fit
Over time, verify the leading indicator correlates with customer retention
Strong correlation of leading indicator to customer retention
Weak correlation of leading indicator to customer retention
Evaluation of customers acquired between 12 and 18 months ago
Goal of Phase
#1 Product-Market Fit
Customer Retention
The Science of Re-establishing Growth
A scientific, data-driven approach to product-market-fit
[Product-Market-Fit] = “Yes”
if ([Customer Retention Leading Indicator] correlates with [Long Term Customer Retention]) AND
([Customer Retention Leading Indicator] is “True”)
Where [Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days
Goal of Phase
#1 Product-Market Fit
Customer Retention
The Science of Re-establishing Growth
What is “Go-to-Market-Fit”?
#2 Go-to-Market Fit
Goal of Phase
#1 Product-Market Fit
Customer Retention
The Science of Re-establishing Growth
“Go-to-Market-Fit” is acquiring and retaining customers consistently and scalably
#2 Go-to-Market Fit
Scalable Unit Economics
“Unit Economics” are also lagging indicators.
We need to understand the leading indicators to unit economics.
The Science of Re-establishing Growth
Defining the leading indicators to Unit Economics
LTV = Lifetime Value of a Customer
CAC = Customer Acquisition Cost
ACV = Annual Contract Value per customer
GM% = Gross Margin Percentage
SQL = Sales Qualified Lead
LTV/CAC > 3
LTV = ACV*GM% / [Annual Churn %]
CAC = [Demand Generation CAC] + [Salesperson CAC]
[Demand Generation CAC] = [Cost per SQL] / [SQL-to-Customer%]
[Salesperson CAC] = [Salesperson Monthly Cost] / [Customers Acquired per Month per Salesperson]
[Customers Acquired per Month per Salesperson] = [SQLs per Salesperson per Month] * [SQL-to-Customer%]
The Science of Re-establishing Growth
Defining the leading indicators to Unit Economics
(ACV*GM%/ [Annual Churn %]) / ([Cost per SQL] / [SQL-to-Customer%] + [Salesperson
Monthly Cost] / [SQLs per Salesperson per Month] * [SQL-to-Customer%]) > 3
Therefore, through relatively simple algebra, we have “go-to-market-fit” if the below equation is “True”
ACV = $20,000
GM% = 70%
Annual Churn % = 15%
Cost per SQL = $1,000
SQL-to-Customer % = 5%
Salesperson Monthly Cost = $15,000
SQLs per Salesperson per Month = 2
LTV = $93,333
Sales CAC = $7,500
Marketing CAC = $20,000
LTV/CAC = 3.4
For example…
The Science of Re-establishing Growth
Instrumenting the leading indicators to Unit Economics
Goal of Phase
#1 Product-Market Fit
Customer Retention
The Science of Re-establishing Growth
When should we scale?
When we have “product-market” and “go-to-market” fit.
#2 Go-to-Market Fit
Scalable Unit Economics
18 @markroberge
How fast should
we scale?
Goal of Phase
The Science of Re-establishing Growth
Establish a pace. Watch the speedometer.
Growth Speedometer
#1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat
Experiment Scale
Customer Retention Scalable Unit Economics Revenue Growth Rate
The Science of Re-establishing Growth
Where should we scale?
The Science of Re-establishing Growth
Where should we scale?
The Science of Re-establishing Growth
Separate “Scale” teams from “Experiment” teams
Goal of Phase
#1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat
Learn Scale
Customer Retention Scalable Unit Economics Revenue Growth Rate
The Science of Re-establishing Growth
How to re-establish and execute growth?
Goal of Phase
Target Market
GTM Playbook
Compensation
Demand Gen.
Pricing
Sales Hire
Early Adopter
Personal Network + Referrals
#1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat
Learn Scale
Customer Retention
Win At All Cost
Solve for Customer Commitment
PM + AE
Based on Customer Retention
Scalable Unit Economics Revenue Growth Rate
The Science of Re-establishing Growth
Aligning GTM with the pursuit of Product-Market-Fit
Goal of Phase
Target Market
GTM Playbook
Compensation
Demand Gen.
Pricing
Sales Hire
Early Adopter
Personal Network + Referrals
Early Majority
1 Scalable, Measurable Medium
#1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat
Learn Scale
Customer Retention Scalable Unit Economics
Win At All Cost Codified, Scalable
Customer Retention + Unit
Economics
Solve for Customer Commitment Solve for Unit Economics
PM + AE Process Builder
Based on Customer Retention
The Science of Re-establishing Growth
Aligning GTM with the pursuit of Go-To-Market-Fit
Revenue Growth Rate
Goal of Phase
Target Market
GTM Playbook
Compensation
Demand Gen.
Pricing
Sales Hire
Early Adopter
Personal Network + Referrals
Early Majority
1 Scalable, Measurable Medium
#1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat
Learn Scale
Customer Retention Scalable Unit Economics Revenue Growth Rate
Win At All Cost Codified, Scalable
Solve for Customer Commitment Solve for Unit Economics
PM + AE Process Builder Process Executor
Add Promotion Path
Scale vs. Experiment vs. Ignore
Multiple Mediums.
Tightly Aligned with Sales.
Reinforced
Assess Disruption Risk
Customer Retention + Unit
Economics
Based on Customer Retention
The Science of Re-establishing Growth
Aligning GTM with Growth and Moat
Resources
https://blog.stage2.capital/science-of-scaling https://blog.stage2.capital/bottoms-up-sm-model
https://blog.stage2.capital/hiring-sales-leader
https://blog.stage2.capital/
• Jay Simons – President, VP S&M @ Atlassian
• Lesley Young – Global Sales @ Facebook Workplace, Box
• Jed Nachman – COO, CRO @ Yelp
• Jon McNeill – Former President @Tesla, COO @Lyft
• Leela Srinivasan, CMO @ SurveyMonkey, LinkedIn, Upwork
• Emmanuelle Skala – SVP Customer Success @ Toast, Digital Ocean
• Oliver Jay – Head of Sales @ Asana, DropBox
• Sydney Sloan – CMO @ Salesloft, Jive, Adobe
• Brian Halligan – CEO @ HubSpot
• Hilary Headlee – Head of Sales Ops @ Zoom, MindBody
• Josh Allen – CRO @ Drift, CarGurus
• Carol Meyers – CMO @ Rapid7
• John Boucher – SVP @ Oracle, ServiceSource
• Kara Gilbert – Chief People Officer @ Turbonomic
• Andrew Rains – CRO @ Automotive Mastermind, VTS
• David Meerman Scott – Speaker & Best Selling Author
• Jeetu Mahtani – SVP International Sales @ HubSpot
• Lou Shipley – CEO @ Blackduck Software
• Tom Chavez – CEO @ Superset, Krux
• Bill Vellante – GM @Infor, Workday, Oracle
• Jim Norton – CRO@ Dosh, Conde Nast, AOL, Google
• Larry D’Angelo – Chief Sales Officer @ LogMeIn
• Mike Volpe – CEO @ Lola, CMO @ HubSpot
• Michael Manne – CRO @ Reonomy, Namely
• Mike McGuinness – Chief Customer Officer @ Veracode
• Mike Arntz – SVP Sales @ SmartSheet, NetSuite
VC Backed and Run by 120+ Sales, Marketing,
and Customer Success Executives
https://www.hbs.edu/faculty/Pages/profile.aspx?facId=869446&facInfo=pub
30 @markroberge
All proceeds go to
Ayele Shakur
Build.org CEO
Thanks!!
Mark Roberge @markroberge
Managing Director @Stage2Capital
Senior Lecturer, Harvard Business School
Former CRO @HubSpot

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Mark Roberge's The Science of Re-Establishing Growth - Where, When, and How

  • 1. & In This Together Series “The Science of Re-establishing Growth” Mark Roberge Managing Director @ Stage 2 Capital Prof @Harvard Business School hello@salesimpactacademy.co.uk Sales & Marketing Leaders Webinar will be live at 4pm BST/8am PST presents
  • 2. The Science of Re-establishing Growth Where, When, and How? Mark Roberge @markroberge Managing Director @Stage2Capital Senior Lecturer, Harvard Business School Former CRO @HubSpot
  • 3. 3 @markroberge When should we begin scaling again?
  • 4. The Science of Re-establishing Growth What is product-market-fit? #1 Product-Market Fit
  • 5. Goal of Phase #1 Product-Market Fit Customer Retention Annual Revenue Retention > 100% Annual Customer Retention > 90% Annual Revenue Retention = [ARR (start of year) – Churn + Upgrades] / ARR (start of year) Annual Customer Retention = [#Customers (start of year) – Customer Churn] / # Customers (start of year) The Science of Re-establishing Growth Customer retention is the best quantifiable measure of product-market-fit
  • 6. Pothole Alert! But customer retention is a lagging indicator. We need to identify a leading indicator to customer retention to identify when product- market-fit is achieved.
  • 7. A Scientific, Data-Driven Approach to Product-Market-Fit Define a leading indicator to customer retention [Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days
  • 8. A Scientific, Data-Driven Approach to Product-Market-Fit Industry examples of customer retention leading indicators [Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days 70% of customers send 2,000+ team messages in the first 30 days 85% of customers upload 1 file in 1 folder on 1 device within 1 hour 80% of customers use 5 features out of the 25 features in the platform within 60 days
  • 9. % of customers that achieve customer retention leading indicator by month of tenure A Scientific, Data-Driven Approach to Product-Market-Fit Instrument customer acquisition cohorts to identify when product-market-fit is achieved
  • 10. A Scientific, Data-Driven Approach to Product-Market-Fit Over time, verify the leading indicator correlates with customer retention Strong correlation of leading indicator to customer retention Weak correlation of leading indicator to customer retention Evaluation of customers acquired between 12 and 18 months ago
  • 11. Goal of Phase #1 Product-Market Fit Customer Retention The Science of Re-establishing Growth A scientific, data-driven approach to product-market-fit [Product-Market-Fit] = “Yes” if ([Customer Retention Leading Indicator] correlates with [Long Term Customer Retention]) AND ([Customer Retention Leading Indicator] is “True”) Where [Customer Retention Leading Indicator] is “True” if P% of customers achieve E event(s) within T days
  • 12. Goal of Phase #1 Product-Market Fit Customer Retention The Science of Re-establishing Growth What is “Go-to-Market-Fit”? #2 Go-to-Market Fit
  • 13. Goal of Phase #1 Product-Market Fit Customer Retention The Science of Re-establishing Growth “Go-to-Market-Fit” is acquiring and retaining customers consistently and scalably #2 Go-to-Market Fit Scalable Unit Economics “Unit Economics” are also lagging indicators. We need to understand the leading indicators to unit economics.
  • 14. The Science of Re-establishing Growth Defining the leading indicators to Unit Economics LTV = Lifetime Value of a Customer CAC = Customer Acquisition Cost ACV = Annual Contract Value per customer GM% = Gross Margin Percentage SQL = Sales Qualified Lead LTV/CAC > 3 LTV = ACV*GM% / [Annual Churn %] CAC = [Demand Generation CAC] + [Salesperson CAC] [Demand Generation CAC] = [Cost per SQL] / [SQL-to-Customer%] [Salesperson CAC] = [Salesperson Monthly Cost] / [Customers Acquired per Month per Salesperson] [Customers Acquired per Month per Salesperson] = [SQLs per Salesperson per Month] * [SQL-to-Customer%]
  • 15. The Science of Re-establishing Growth Defining the leading indicators to Unit Economics (ACV*GM%/ [Annual Churn %]) / ([Cost per SQL] / [SQL-to-Customer%] + [Salesperson Monthly Cost] / [SQLs per Salesperson per Month] * [SQL-to-Customer%]) > 3 Therefore, through relatively simple algebra, we have “go-to-market-fit” if the below equation is “True” ACV = $20,000 GM% = 70% Annual Churn % = 15% Cost per SQL = $1,000 SQL-to-Customer % = 5% Salesperson Monthly Cost = $15,000 SQLs per Salesperson per Month = 2 LTV = $93,333 Sales CAC = $7,500 Marketing CAC = $20,000 LTV/CAC = 3.4 For example…
  • 16. The Science of Re-establishing Growth Instrumenting the leading indicators to Unit Economics
  • 17. Goal of Phase #1 Product-Market Fit Customer Retention The Science of Re-establishing Growth When should we scale? When we have “product-market” and “go-to-market” fit. #2 Go-to-Market Fit Scalable Unit Economics
  • 18. 18 @markroberge How fast should we scale?
  • 19. Goal of Phase The Science of Re-establishing Growth Establish a pace. Watch the speedometer. Growth Speedometer #1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat Experiment Scale Customer Retention Scalable Unit Economics Revenue Growth Rate
  • 20. The Science of Re-establishing Growth Where should we scale?
  • 21. The Science of Re-establishing Growth Where should we scale?
  • 22. The Science of Re-establishing Growth Separate “Scale” teams from “Experiment” teams
  • 23. Goal of Phase #1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat Learn Scale Customer Retention Scalable Unit Economics Revenue Growth Rate The Science of Re-establishing Growth How to re-establish and execute growth?
  • 24. Goal of Phase Target Market GTM Playbook Compensation Demand Gen. Pricing Sales Hire Early Adopter Personal Network + Referrals #1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat Learn Scale Customer Retention Win At All Cost Solve for Customer Commitment PM + AE Based on Customer Retention Scalable Unit Economics Revenue Growth Rate The Science of Re-establishing Growth Aligning GTM with the pursuit of Product-Market-Fit
  • 25. Goal of Phase Target Market GTM Playbook Compensation Demand Gen. Pricing Sales Hire Early Adopter Personal Network + Referrals Early Majority 1 Scalable, Measurable Medium #1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat Learn Scale Customer Retention Scalable Unit Economics Win At All Cost Codified, Scalable Customer Retention + Unit Economics Solve for Customer Commitment Solve for Unit Economics PM + AE Process Builder Based on Customer Retention The Science of Re-establishing Growth Aligning GTM with the pursuit of Go-To-Market-Fit Revenue Growth Rate
  • 26. Goal of Phase Target Market GTM Playbook Compensation Demand Gen. Pricing Sales Hire Early Adopter Personal Network + Referrals Early Majority 1 Scalable, Measurable Medium #1 Product-Market Fit #2 Go-to-Market Fit #3 Growth and Moat Learn Scale Customer Retention Scalable Unit Economics Revenue Growth Rate Win At All Cost Codified, Scalable Solve for Customer Commitment Solve for Unit Economics PM + AE Process Builder Process Executor Add Promotion Path Scale vs. Experiment vs. Ignore Multiple Mediums. Tightly Aligned with Sales. Reinforced Assess Disruption Risk Customer Retention + Unit Economics Based on Customer Retention The Science of Re-establishing Growth Aligning GTM with Growth and Moat
  • 28. • Jay Simons – President, VP S&M @ Atlassian • Lesley Young – Global Sales @ Facebook Workplace, Box • Jed Nachman – COO, CRO @ Yelp • Jon McNeill – Former President @Tesla, COO @Lyft • Leela Srinivasan, CMO @ SurveyMonkey, LinkedIn, Upwork • Emmanuelle Skala – SVP Customer Success @ Toast, Digital Ocean • Oliver Jay – Head of Sales @ Asana, DropBox • Sydney Sloan – CMO @ Salesloft, Jive, Adobe • Brian Halligan – CEO @ HubSpot • Hilary Headlee – Head of Sales Ops @ Zoom, MindBody • Josh Allen – CRO @ Drift, CarGurus • Carol Meyers – CMO @ Rapid7 • John Boucher – SVP @ Oracle, ServiceSource • Kara Gilbert – Chief People Officer @ Turbonomic • Andrew Rains – CRO @ Automotive Mastermind, VTS • David Meerman Scott – Speaker & Best Selling Author • Jeetu Mahtani – SVP International Sales @ HubSpot • Lou Shipley – CEO @ Blackduck Software • Tom Chavez – CEO @ Superset, Krux • Bill Vellante – GM @Infor, Workday, Oracle • Jim Norton – CRO@ Dosh, Conde Nast, AOL, Google • Larry D’Angelo – Chief Sales Officer @ LogMeIn • Mike Volpe – CEO @ Lola, CMO @ HubSpot • Michael Manne – CRO @ Reonomy, Namely • Mike McGuinness – Chief Customer Officer @ Veracode • Mike Arntz – SVP Sales @ SmartSheet, NetSuite VC Backed and Run by 120+ Sales, Marketing, and Customer Success Executives
  • 30. 30 @markroberge All proceeds go to Ayele Shakur Build.org CEO
  • 31. Thanks!! Mark Roberge @markroberge Managing Director @Stage2Capital Senior Lecturer, Harvard Business School Former CRO @HubSpot

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