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(Lean) Startup Metrics & Analytics

      Nicola Junior Vitto - @njvitto @blomming
  September 26, 2012 - Better Software - Firenze, Italy
Entrepreneurship



...Entrepreneurs recognize they are going to have
 to follow their own internal compass and embrace
      the uncertainty as part of the journey.

                              - Steve Blank -
 more on: http://steveblank.com/2009/06/29/agile-opportunism-entrepreneurial-dna/
Get out of the building (by Steve Blank)




    Your business assumptions can be wrong
     Go out and speak with your customers
Vanity Metrics
Vanity Metrics - Timelines




There will always be something up and to the right
Vanity Metrics - Google Analytics




                  Forget it!
Vanity Metrics - Google Analytics




 ...and this could become like a drug...killing you!
Vanity Metrics - TechCrunch & Co


           “mDialog raises 5 Million
          from Blackberry partners”

          “GroupMe is now sending
          one Million texts every day”

         “Google Plus hits 10 Million
             users in 2 weeks”
Lean Metrics
What’s a startup?


A startup is first of all an experiment, it is a human
institution designed to deliver a new product or
service under conditions of extreme uncertainty

At its heart, a startup is a catalyst that transforms
ideas into product.

       (From Lessons Learned blog By Eric Ries)
What’s a Lean Startup?



     Lean startup is a rigorous process
           for iterating from Plan A
            to a plan that works.

               (by Ash Maurya)
What Metrics Matter?


    Example: Facebook on early days

           150k users, little revenue

          Many superior competitors


   What would indicate their future success?
What Metrics Matter?


    Example: Facebook on early days

 75% of users visit one or more times per day

   Within one month of launching on a new
  campus, can acquire 90% of the students
What Metrics Matter?

        Good Metrics (Three A’s)

              Are Actionable

              Can be Audited

              Are Accessible
Actionable Metric



     An actionable metric is one that ties
      specific and repeatable actions
             to observed results

                (by Ash Maurya)
A/B Testing
A/B Testing - New Blomming home




                  VS




            Define your Goals
A/B Testing - Define your goals


              A/B Testing Goals

          One single important Goal:
% Users that sign-up for the service (as a seller)

                 Secondary Goal:
         % Buyers that buy something
         after landing on the homepage
Multivariate Testing
Multivariate Testing at Google


   “Yes, it’s true that a team at Google couldn’t
 decide between two blues, so they’re testing 41
    shades between each blue to see whic one
performs better. I has a recent debate over wheter
a border should be 3, 4 or 5 pixels wide, and was
               asked to prove my case.
 I can’t operate in an environment like that.”

       (by Doug Bowman on Design at Google)
Multivariate Testing at Google
Multivariate Testing at Google
Multivariate Testing at Google




      Google                     Bing
Multivariate Testing at Google




      “That blue was worth at least $80M”

       (by Paul Ray - Product Manager at Bing)
Funnels
David Cancel’s Funnel




                 The Problem:
         98% of people who visit your site,
              leave never to return
David Cancel’s Funnel



                        2%
  “The average conversion rate in the United States of
   America wheter you’re selling elephants or iPods”

   (by Avinash Kaushik - Analytics Evangelist, Google)
David Cancel’s Funnel
David Cancel’s Funnel




                    The Solution:
          To find, engage and convert more
       of your website visitors into customers
Online Marketing
   is shifting
Online Marketing Paradigm Shift




                                  by David Cancel
Online Marketing Paradigm Shift




                                  by David Cancel
Online Marketing Paradigm Shift




                                  by David Cancel
Online Marketing Paradigm Shift




  Internet Marketing 3.0 (different goal)
                                    by David Cancel
Lifecycle Marketing




                      by David Cancel
Optimize
Optimize for learning




                 Optimize for learning
     by creating a data-driven marketing framework
Optimize for learning




          Analytics & A/B Testing are also
             not exactly the answer
Optimize for learning




         Use quantitative & qualitative data
           to test *your* assumptions
Optimize for learning




      The point of testing is to prove or disprove
                assumptions quickly
Optimize for learning




 Pay attention to “overtesting” using Multivariate testing
           because it generally takes too long
The Local Maxima Problem
Frameworks
AARRR
AARRR

 Dave McClure’s Startup Metrics for Pirates is a good
     framework for thinking about macro metrics
AARRR - Model
AARRR - Conversions Example
AARRR - Different orders (example)


      1. Activation, Retention (happiness)

            2. Revenue (sustainability)

         3. Acquisition, Referral (virality)

      (this is the Ash Maurya or 37signals order:
                 “Charge from day one”)
Acquisition
Tracking Marketing Channels


                 Google Adwords
                    Banners
                  Social Media
                  Partnerships
                       PR
                    Blogging

        ...anything that links to your site!
Tracking Marketing Channels


        Use unique urls (tracking parameters)
       on every url you create/give-out/pay for

                     Use bit.ly

         Use HTTP referrers to group PR
Measuring Cost of Visits



               Cost per click (site visits)

        Cost of campaign / Traffic generated

    (Social media) Cost of effort / Traffic generated
Measuring Cost of Acquisition

         Cost of one visit / conversion rate =
              Cost of an Acquisition

      Acquisition could be paid for acquisition
                 of free sign-up


          ...unfortunately is not so simple
Marketing Channels

                Per channel track:

                    Scale
                    Cost
                  Conversion


           Optimise and scale channels
       with best Cost of Acquisition (CoA)
             and potential to Scale
Acquisition



    Cost of Acquisition < Customer Lifetime Profit

    Then scale acquisition at a similar or lower rate

       A/B test acquisition channels to optimise
Acquisition including Referral


 If it costs €3 to acquire a customer through advertising

                 But a customer brought
         in 2 other customers through referral

             The COA of that channel is €1
Activation
Activation



             Sure, they signed-up!!!
Activation



             Sure, they signed-up!!!


             BUT did the like it???
Activation at Facebook



 (i) which data points predict whether a user will stay?


(ii) if they stay, which data points predict how active they’ll
                    be after three months?
Activation at Facebook

 (i) which data points predict whether a user will stay?
        having more than one session as a new user
           and entering basic profile information.


(ii) if they stay, which data points predict how active they’ll
                    be after three months?
how often a user was reached out by others, frequency of
  third party application use, and how available a user was
                           on the site.
Activation at Facebook

        “At the time, I heard many people criticize
 Facebook’s early investors, claiming that Facebook had
   ‘no business model’ and only modest revenues
    relative to the valuation offered by its investors...”

“...Facebook was different, because it employed a different
     Engine of Growth. It paid nothing for customer
     acquisition, and its high engagement meant that
    it was accumulating massive amount of customer
                   attention every day.”

              (Eric Ries - The Lean Startup)
Activation Metrics




    Activation metrics often drive other metrics
            in Referral, Retention, Revenue
Retention
Returning Users



                Tracking unregistered users
 that return often (useful for content sites with advertising)

                Tracking registered users
         that return and take some sort of action.
Cohort Analysis
Twitter Cohorts (example)




                      by Fred Wilson’s blog
   (more on: http://www.avc.com/a_vc/2009/10/the-cohort-analysis.html)
Twitter Cohorts (example)




                      by Fred Wilson’s blog
   (more on: http://www.avc.com/a_vc/2009/10/the-cohort-analysis.html)
Referral
Referral Mechanism


             Social Media Sharing

         Invite a friend type mechanism

                 App Reviews

                Word of Mouth
Viral Coefficient




         The average number of customers
            that each customer refers
Viral Coefficient - Example


              Each company customer
         invites 5 other customers via email

            20% click on that email link

     50% of those users convert into customers
Viral Coefficient - Example




Viral Coefficient = Referrals x click through x conversion

                   5 x 0.2 x 0.5 = 0.5
Viral Coefficient


          A viral co-efficient greater than 1
            means that every customer
   gets more than one other customer on average
Viral Coefficient


          A viral co-efficient greater than 1
            means that every customer
   gets more than one other customer on average



       Therefore your product will grow virally
Viral Coefficient


           Measure automatically for all
           your built in referral mechanism



         Give customers unique invite URLs
                and track conversions
Viral Cycle Time



     Viral Cycle Time = the average time taken for
           a referral to turn into a customer


              With the viral coefficient
                and viral cycle time
         you can determine your viral growth
Net Promoter Score



  Net Promoter Score: Number of people who would
         recommend your product to a friend



              A single question survey
Net Promoter Score


 “How likely is it you would recommend my product to a
                     friend or colleague?”


 0    1     2   3     4    5    6    7    8     9   10




          NPS = % Promoters - % Detractors
Net Promoter Score


            Survey a small percentage
       of your customers by email weekly


           Record who you sent to so
       you don’t repeat the same people
                   every week
Net Promoter Score



          NPS is not a direct measurement
           that translates to key metrics



   Can act as a leading indicator of other metrics
Revenue
Making Money




  Key for any business is to find out how much profit
             they make for every customer
         and scaling the number of customers
Lifetime Customer Value


             How much money you make
          for every customer you acquire

          For some this a single transaction

 For subscription businesses it depends on retention
Cancellation Rate


    Cancellation rate = is the percentage number of
 customers who cancel in any given month compared to
                total (paying) customers


                     [Cancellation rate] =
   [product utility] + [service quality] + [acceptable price]
Lifetime Customer Value (LTV)



     LTV = monthly revenue x n° months in lifetime

          N° months = 1 / cancellation rate

       LTV = monthly revenue / cancellation rate
Lifetime Customer Value (LTV)



                     For example:

  If €20 a month and cancellation rate is 10% a month

                     LTV = €200
Lifetime Customer Value (LTV)


              Often not that simple.
         Short term cancellation rates are
           much higher than long term



        Use Cohort Analysis to determine
Lifetime Customer Value (LTV)


       r = short-term cancellation rate (e.g. 0,15)
       p = long-term cancellation rate (e.g. 0.03)
  s = number of months in the “short-term” age group
                        (e.g. 3)


         (1-r)^s x (s + 1/p) = expected months
Some Tools
Event based tracking
Event based tracking
Event based tracking
Customer lifecycle
  management
Customer lifecycle management
Customer lifecycle management
Tips
OODA Loop
Innovation Accounting


  “To improve entrepreneurial outcomes, and to
hold entrepreneurs accountable, we need to focus
 on the boring stuff: how to measure progress,
  how to setup milestones, how to prioritize
 work. This requires a new kind of accounting,
              specific to startups”

            (Eric Ries - The Lean Startup)
Innovation Accounting



            Concentrate on macro metrics

 Everything you do should attempt to change a metric

          Try to use as few tools as possible
One Page Dashboard
Customer Development: pivoting
(Lean) Product Development



Problem:
unknown




                              Solution:
                             unknown
Scalable (lean) startup
SCRUM




        Do you know SCRUM?
Kanban Board




     I know: this isn’t an example of an exciting and well done Sprint :)
(Lean) Product Management



             Well, trying to connect the dots:
    what we learnt so far is how the Product Owner
     can define and prioritize stories at every Sprint
 in a Startup that wants to be called, you know, Lean! :)
Learning Boards - Lean Stack




    We will talk about the Lean Stack of Ash Maurya
     or other possible “lean mapping” frameworks
                  in a future presentation
Focus focus focus
Credits

           Stuart Eccles - Lean Startup Metrics

          Joshua Porter - Metrics-Driven Design

          David Cancel - Data-Driven Marketing

               Lean Startup Machine -
 How to measure the metrics that determine real progress

(and the others specified directly in the slides when picking
              some parts of books or blogs)
The Lean Startup
Running Lean
Business Models
An alternative?




                  Lifestyle business
Thanks!

          Blomming.com
          Company.Blomming.com
          Magazine.Blomming.com
            Help.Blomming.com
           Twitter.com/Blomming
          Facebook.com/Blomming

           nicola@blomming.com
          On FB & Twitter as: njvitto

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Lean Startup Metrics & Analytics

  • 1. (Lean) Startup Metrics & Analytics Nicola Junior Vitto - @njvitto @blomming September 26, 2012 - Better Software - Firenze, Italy
  • 2. Entrepreneurship ...Entrepreneurs recognize they are going to have to follow their own internal compass and embrace the uncertainty as part of the journey. - Steve Blank - more on: http://steveblank.com/2009/06/29/agile-opportunism-entrepreneurial-dna/
  • 3. Get out of the building (by Steve Blank) Your business assumptions can be wrong Go out and speak with your customers
  • 5. Vanity Metrics - Timelines There will always be something up and to the right
  • 6. Vanity Metrics - Google Analytics Forget it!
  • 7. Vanity Metrics - Google Analytics ...and this could become like a drug...killing you!
  • 8. Vanity Metrics - TechCrunch & Co “mDialog raises 5 Million from Blackberry partners” “GroupMe is now sending one Million texts every day” “Google Plus hits 10 Million users in 2 weeks”
  • 10. What’s a startup? A startup is first of all an experiment, it is a human institution designed to deliver a new product or service under conditions of extreme uncertainty At its heart, a startup is a catalyst that transforms ideas into product. (From Lessons Learned blog By Eric Ries)
  • 11. What’s a Lean Startup? Lean startup is a rigorous process for iterating from Plan A to a plan that works. (by Ash Maurya)
  • 12. What Metrics Matter? Example: Facebook on early days 150k users, little revenue Many superior competitors What would indicate their future success?
  • 13. What Metrics Matter? Example: Facebook on early days 75% of users visit one or more times per day Within one month of launching on a new campus, can acquire 90% of the students
  • 14. What Metrics Matter? Good Metrics (Three A’s) Are Actionable Can be Audited Are Accessible
  • 15. Actionable Metric An actionable metric is one that ties specific and repeatable actions to observed results (by Ash Maurya)
  • 17. A/B Testing - New Blomming home VS Define your Goals
  • 18. A/B Testing - Define your goals A/B Testing Goals One single important Goal: % Users that sign-up for the service (as a seller) Secondary Goal: % Buyers that buy something after landing on the homepage
  • 20. Multivariate Testing at Google “Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see whic one performs better. I has a recent debate over wheter a border should be 3, 4 or 5 pixels wide, and was asked to prove my case. I can’t operate in an environment like that.” (by Doug Bowman on Design at Google)
  • 23. Multivariate Testing at Google Google Bing
  • 24. Multivariate Testing at Google “That blue was worth at least $80M” (by Paul Ray - Product Manager at Bing)
  • 26. David Cancel’s Funnel The Problem: 98% of people who visit your site, leave never to return
  • 27. David Cancel’s Funnel 2% “The average conversion rate in the United States of America wheter you’re selling elephants or iPods” (by Avinash Kaushik - Analytics Evangelist, Google)
  • 29. David Cancel’s Funnel The Solution: To find, engage and convert more of your website visitors into customers
  • 30. Online Marketing is shifting
  • 31. Online Marketing Paradigm Shift by David Cancel
  • 32. Online Marketing Paradigm Shift by David Cancel
  • 33. Online Marketing Paradigm Shift by David Cancel
  • 34. Online Marketing Paradigm Shift Internet Marketing 3.0 (different goal) by David Cancel
  • 35. Lifecycle Marketing by David Cancel
  • 37. Optimize for learning Optimize for learning by creating a data-driven marketing framework
  • 38. Optimize for learning Analytics & A/B Testing are also not exactly the answer
  • 39. Optimize for learning Use quantitative & qualitative data to test *your* assumptions
  • 40. Optimize for learning The point of testing is to prove or disprove assumptions quickly
  • 41. Optimize for learning Pay attention to “overtesting” using Multivariate testing because it generally takes too long
  • 42. The Local Maxima Problem
  • 44. AARRR
  • 45. AARRR Dave McClure’s Startup Metrics for Pirates is a good framework for thinking about macro metrics
  • 48. AARRR - Different orders (example) 1. Activation, Retention (happiness) 2. Revenue (sustainability) 3. Acquisition, Referral (virality) (this is the Ash Maurya or 37signals order: “Charge from day one”)
  • 50. Tracking Marketing Channels Google Adwords Banners Social Media Partnerships PR Blogging ...anything that links to your site!
  • 51. Tracking Marketing Channels Use unique urls (tracking parameters) on every url you create/give-out/pay for Use bit.ly Use HTTP referrers to group PR
  • 52. Measuring Cost of Visits Cost per click (site visits) Cost of campaign / Traffic generated (Social media) Cost of effort / Traffic generated
  • 53. Measuring Cost of Acquisition Cost of one visit / conversion rate = Cost of an Acquisition Acquisition could be paid for acquisition of free sign-up ...unfortunately is not so simple
  • 54. Marketing Channels Per channel track: Scale Cost Conversion Optimise and scale channels with best Cost of Acquisition (CoA) and potential to Scale
  • 55. Acquisition Cost of Acquisition < Customer Lifetime Profit Then scale acquisition at a similar or lower rate A/B test acquisition channels to optimise
  • 56. Acquisition including Referral If it costs €3 to acquire a customer through advertising But a customer brought in 2 other customers through referral The COA of that channel is €1
  • 58. Activation Sure, they signed-up!!!
  • 59. Activation Sure, they signed-up!!! BUT did the like it???
  • 60. Activation at Facebook (i) which data points predict whether a user will stay? (ii) if they stay, which data points predict how active they’ll be after three months?
  • 61. Activation at Facebook (i) which data points predict whether a user will stay? having more than one session as a new user and entering basic profile information. (ii) if they stay, which data points predict how active they’ll be after three months? how often a user was reached out by others, frequency of third party application use, and how available a user was on the site.
  • 62. Activation at Facebook “At the time, I heard many people criticize Facebook’s early investors, claiming that Facebook had ‘no business model’ and only modest revenues relative to the valuation offered by its investors...” “...Facebook was different, because it employed a different Engine of Growth. It paid nothing for customer acquisition, and its high engagement meant that it was accumulating massive amount of customer attention every day.” (Eric Ries - The Lean Startup)
  • 63. Activation Metrics Activation metrics often drive other metrics in Referral, Retention, Revenue
  • 65. Returning Users Tracking unregistered users that return often (useful for content sites with advertising) Tracking registered users that return and take some sort of action.
  • 67. Twitter Cohorts (example) by Fred Wilson’s blog (more on: http://www.avc.com/a_vc/2009/10/the-cohort-analysis.html)
  • 68. Twitter Cohorts (example) by Fred Wilson’s blog (more on: http://www.avc.com/a_vc/2009/10/the-cohort-analysis.html)
  • 70. Referral Mechanism Social Media Sharing Invite a friend type mechanism App Reviews Word of Mouth
  • 71. Viral Coefficient The average number of customers that each customer refers
  • 72. Viral Coefficient - Example Each company customer invites 5 other customers via email 20% click on that email link 50% of those users convert into customers
  • 73. Viral Coefficient - Example Viral Coefficient = Referrals x click through x conversion 5 x 0.2 x 0.5 = 0.5
  • 74. Viral Coefficient A viral co-efficient greater than 1 means that every customer gets more than one other customer on average
  • 75. Viral Coefficient A viral co-efficient greater than 1 means that every customer gets more than one other customer on average Therefore your product will grow virally
  • 76. Viral Coefficient Measure automatically for all your built in referral mechanism Give customers unique invite URLs and track conversions
  • 77. Viral Cycle Time Viral Cycle Time = the average time taken for a referral to turn into a customer With the viral coefficient and viral cycle time you can determine your viral growth
  • 78. Net Promoter Score Net Promoter Score: Number of people who would recommend your product to a friend A single question survey
  • 79. Net Promoter Score “How likely is it you would recommend my product to a friend or colleague?” 0 1 2 3 4 5 6 7 8 9 10 NPS = % Promoters - % Detractors
  • 80. Net Promoter Score Survey a small percentage of your customers by email weekly Record who you sent to so you don’t repeat the same people every week
  • 81. Net Promoter Score NPS is not a direct measurement that translates to key metrics Can act as a leading indicator of other metrics
  • 83. Making Money Key for any business is to find out how much profit they make for every customer and scaling the number of customers
  • 84. Lifetime Customer Value How much money you make for every customer you acquire For some this a single transaction For subscription businesses it depends on retention
  • 85. Cancellation Rate Cancellation rate = is the percentage number of customers who cancel in any given month compared to total (paying) customers [Cancellation rate] = [product utility] + [service quality] + [acceptable price]
  • 86. Lifetime Customer Value (LTV) LTV = monthly revenue x n° months in lifetime N° months = 1 / cancellation rate LTV = monthly revenue / cancellation rate
  • 87. Lifetime Customer Value (LTV) For example: If €20 a month and cancellation rate is 10% a month LTV = €200
  • 88. Lifetime Customer Value (LTV) Often not that simple. Short term cancellation rates are much higher than long term Use Cohort Analysis to determine
  • 89. Lifetime Customer Value (LTV) r = short-term cancellation rate (e.g. 0,15) p = long-term cancellation rate (e.g. 0.03) s = number of months in the “short-term” age group (e.g. 3) (1-r)^s x (s + 1/p) = expected months
  • 94. Customer lifecycle management
  • 97. Tips
  • 99. Innovation Accounting “To improve entrepreneurial outcomes, and to hold entrepreneurs accountable, we need to focus on the boring stuff: how to measure progress, how to setup milestones, how to prioritize work. This requires a new kind of accounting, specific to startups” (Eric Ries - The Lean Startup)
  • 100. Innovation Accounting Concentrate on macro metrics Everything you do should attempt to change a metric Try to use as few tools as possible
  • 105. SCRUM Do you know SCRUM?
  • 106. Kanban Board I know: this isn’t an example of an exciting and well done Sprint :)
  • 107. (Lean) Product Management Well, trying to connect the dots: what we learnt so far is how the Product Owner can define and prioritize stories at every Sprint in a Startup that wants to be called, you know, Lean! :)
  • 108. Learning Boards - Lean Stack We will talk about the Lean Stack of Ash Maurya or other possible “lean mapping” frameworks in a future presentation
  • 110. Credits Stuart Eccles - Lean Startup Metrics Joshua Porter - Metrics-Driven Design David Cancel - Data-Driven Marketing Lean Startup Machine - How to measure the metrics that determine real progress (and the others specified directly in the slides when picking some parts of books or blogs)
  • 114. An alternative? Lifestyle business
  • 115. Thanks! Blomming.com Company.Blomming.com Magazine.Blomming.com Help.Blomming.com Twitter.com/Blomming Facebook.com/Blomming nicola@blomming.com On FB & Twitter as: njvitto

Editor's Notes