How to Optimize Your Product and Business Using Analytics by Dan Olsen
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This document outlines Dan Olsen's presentation on optimizing products and businesses using analytics. It discusses three phases of a product - before product-market fit, after product-market fit during growth, and optimizing for revenue. It emphasizes using both qualitative and quantitative learning methods. Key metrics discussed include retention rate, conversion rate, and the "metric that matters most". The presentation provides a case study on redesigning an account signup process to improve conversion rates.
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How to Optimize Your Product and Business Using Analytics by Dan Olsen
- 1. How to Optimize Your Product and Business Using Analytics Dan Olsen May 31, 2017
- 2. My Background Educa/on n Engineering background n Stanford MBA n UX design and coding Experience n Product Management leader at Intuit n CEO & Cofounder, TechCrunch award winner YourVersion n PM consultant: Box, Facebook, MicrosoK, Medallia n Founder: Lean Product Silicon Valley TwiMer: @danolsen My slides: hMp://dan-olsen.com Copyright © 2017 @danolsen
- 6. n Book giveaway on TwiMer n Tweet: include @danolsen n Hashtags #leanstartup #prodmgmt #growth n hMp:///ny.cc/LPP That’s Why I Wrote Copyright © 2017 @danolsen
- 21. Qualita/ve Complements Quan/ta/ve Copyright © 2017 Olsen Solu/ons Qual Why? Quant What? How many?
- 22. Learning Methods Courtesy of Christian Rohrer, http://xdstrategy.com
- 33. Acquisi9on: How much water (prospec/ve customers) are you spraying? prospective customers customers
- 38. Reten/on Rate n Reten/on rate tracks what % of your customers are s/ll ac/ve over /me ~80% never use app again Curve eventually flattens out
- 46. Profit = Revenue - Cost Unique Visitors x Ad Revenue per Visitor Impressions/Visitor x Effec/ve CPM / 1000 Visits/Visitor x Pageviews/Visit x Impressions/PV New Visitors + Returning Visitors Invited Visitors + Uninvited Visitors # of Users Sending Invites x Invites Sent/User x Invite Conversion Rate Define the Equa/on of your Business “Peeling the Onion” Adver/sing Business Model: Copyright © 2017 @danolsen
- 47. Copyright © 2017 @danolsen ( SEO Visitors + SEM Visitors + Viral Visitors ) x Trial Conversion Rate Paying Users x Revenue per Paying User New Paying Users + Repeat Paying Users Previous Paying Users x ( 1 – Cancella/on Rate ) Trial Users x Conv Rate Profit = Revenue - Cost Equa/on of your Business: Subscrip/on Business Model
- 48. How to Track Your Metrics n Track each metric as daily /me series n Create ra/os from primary metrics: X / Y n Example: How good is your registra/on page? n Okay: # of registered users per day n BeMer: registra/on conversion rate = # registered users / # uniques to reg page Date Unique Visitors Page views Ad Revenue New User Sign-ups … 4/24/08 10,100 29,600 25 490 4/25/08 10,500 27,100 24 480 … Copyright © 2017 @danolsen
- 49. Registra/on Page Conversion Rate Daily Signup Page Yield vs. Time New Registered Users divided by Unique Visitors to Signup Page 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% 1/31 2/14 2/28 3/14 3/28 4/11 4/25 5/9 5/23 6/6 6/20 7/4 7/18 8/1 8/15 8/29 9/12 9/26 10/1 0 DailySignupPageYield Changed messaging Added questions to signup page Started requiring registration Copyright © 2017 @danolsen Registration Page Conversion Rate vs. Time RegistrationPageConversionRate
- 53. Iden/fying the “Cri/cal Few” Metrics n What is the upside poten/al of each metric? n How many resources will it take to “move the needle”? n Developer-days, /me, money n How much will the needle move? Revenue impact? n Which metrics have highest ROI opportuni/es? Return Investment Return Investment Return Investment Metric A Good ROI Metric B Bad ROI Metric C Great ROI Copyright © 2017 @danolsen
- 55. Abandonment Rate (7 Day Moving Average) 0% 10% 20% 30% 40% 50% 60% 70% 80% 10/7/02 10/14/02 10/21/02 10/28/02 11/4/02 11/11/02 11/18/02 11/25/02 12/2/02 12/9/02 12/16/02 12/23/02 12/30/02 1/6/03 1/13/03 1/20/03 AbandonmentRate(7DayMovingAverage) Steps 1-2 Copyright © 2017 @danolsen Case Study: Account Signup Process Redesign
- 59. Abandonment Rate (7 Day Moving Average) 0% 10% 20% 30% 40% 50% 60% 70% 80% 10/7/02 10/14/02 10/21/02 10/28/02 11/4/02 11/11/02 11/18/02 11/25/02 12/2/02 12/9/02 12/16/02 12/23/02 12/30/02 1/6/03 1/13/03 1/20/03 AbandonmentRate(7DayMovingAverage) Steps 1-2 Copyright © 2017 @danolsen Redesigned User Flow Improved Registra/on Conversion Rate 37% improvement in conversion rate Released New Design
- 62. • Which metric has highest ROI opportunity? Case Study: Op/mizing Friendster’s Viral Loop Active Users Prospective Users Invite Click Succeed Invite click-through rate Conversion rate Don’t Click Fail Invites per sender % of users sending invites • Mul/plied together, these metrics determine your viral ra/o Users % of users who are active = 15% = 2.3 = 85% Registration Process Copyright © 2017 @danolsen
- 66. Okay, so how can we improve the metric? n How do we increase the average number of invites being sent out per sender? n For each idea: n What’s the expected benefit? (how much will it improve the metric?) n What’s the expected cost? (how many engineer- days will it take?) n You want to iden/fy highest ROI idea Copyright © 2017 @danolsen
- 73. Life/me Value (LTV) n Life/me value of a customer = how much value your average customer will generate n LTV = ARPU x Avg Customer Life/me x Gross Margin n ARPU (Avg Revenue / User) = Total Revenue / # of Users n Average Customer Life/me n How long your average customer generates revenue n Equals 1 / churn rate (5% monthly churn = 20 months avg life) n Gross Margin: the % of revenues leK over aKer subtrac/ng the cost of providing the product/service Copyright © 2017 @danolsen Note: for simplicity, this LTV equa/on ignores the “cost of capital”
- 74. Customer Acquisi/on Cost (CAC) n CAC is the average cost for you to obtain a revenue-genera/ng customer n Takes into account: n Your cost of acquiring a prospect (CPA) n Your conversion rate for conver/ng prospects to revenue-genera/ng customers n CPA varies by channel; diminishing returns n CAC=Cost per Acquisi/on / Conversion Rate Copyright © 2017 @danolsen