Metrics That Matter

Monday, Mar. 26, 2018
3:30-5:30 PM
Hawes 203

Guest Instructor: Lou Orfanos, CCO & SVP Product, Localytics

Assignment

After reading the blog post below, "The One Metric That Matters," each team must:

  1. Identify -- in very specific terms -- the OMTM for your app for the next six months.

  2. The OMTM is only important if you understand what affects it. This requires developing and testing guesses for underlying behaviors and observations that drive or predict your core metrics. In very specific terms, identify three user behaviors that you hypothesize will be the most powerful predictors of performance for your OMTM. Using Twitter as an example, its OMTM might be the percentage of new users who access their account at least once during three successive 30-day periods after signing up. One predictor for this metric might be the fraction of new users who follow ten or more people within one week of signing up.

  3. For your OMTM and each of the three predictors, specify exactly how you will collect the data required to track behaviors and performance.

 

By 10:00am March 26, each team should post a link to a google doc in the Assignment Master "Mar 26 - OMTM" tab with their OMTM and three predictors, along with a description of how you will collect required data.

Two teams will present their OMTM, user behavior predictors and measurement techniques for critique in class. Keith will notify the teams selected to present by 12pm on the 26th.

Required Reading

  1. The One Metric That Matters. by Croll & Yoskovitz (authors of the excellent book Lean Analytics

  2. How to Choose the RIght UX Metrics, by Telepathy,GV & Kerry Rodden

  3. The Hierarchy of Engagement Expanded, by Greylock Partner, Sarah Tavel

  4. Review Localytics' features to familiarize with their mobile analytics service.

 

Recommended Reading

  1. Startup Metrics, Dave McClure

  2. Onboardly's Shanelle Mullin offers a beginner's guide to startup marketing analytics. (skip down to section titled "How to Use Google Analytics")

  3. The Tools Early Stage Startups Need to Understand Their Customers, interview of Peter Reinhardt by First Round Review

  4. Lean Analytics is a book that looks at key metrics for different business models.

  5. There are links to dozens of posts on conversion rate optimization and A/B testing on Prof. Eisenmann's marketing reading list (scroll down about half way).

Julia Austin, Senior Lecturer

Harvard Business School

Rock Center 115