Lean LaunchPad Workshop:Defining an Analytics Strategy презентация

Lean LaunchPad Workshop: Defining an Analytics Strategy Ryan Jung Haas MBA 2014 ryan_jung@haas.berkeley.edu

Why Are Analytics Important?

Why You Need an Analytics Strategy Learn faster by creating feedback loops More clarity based on behavior Consensus on future action

History of Analytics 1990s – Web counters

Keys to a Great Analytics Strategy Tightly integrated with overall business strategy Iterative process Measurable set of hypotheses, results, and revisions

The Modern Data-Driven Lean Startup Goal is to optimize a set of business objectives in a logical progression leveraging quantitative and qualitative facts in order to delight customers in a scalable, repeatable fashion

Most Important Reports Segmentation (Cohorting) Retention Funnels Revenue Tracking Marketing Campaign Effectiveness Path Analysis Notifications

Segmentation / Cohorting What segments are getting what value out of your product?

Value Proposition / Customer Segment

Segmentation Example

Retention Who gets the most value out of your solution?

How Churn affects LTV

Thinking Through Retention

Retention Reports

BIG IDEA: LTV drives CAC which drives channel selection

Funnels How are users interacting with your solution?

Sales Funnels

Funnel Reports

Funnel Reports

Tying funnels to revenues Revenue = installs x [signups / installs] x [purchases / signups ] x [revenue / purchase]

Pitfalls to Avoid

Summary You need to be thinking about analytics because your competition probably already is Analytics is evolving, so keeping up is imperative Analytics needs to be tied to your overall business strategy, should be hypothesis-driven, and is an iterative process

Case Studies

Airbnb Challenge: Initially wanted to optimize booking flow Allowed them to identify to distinct classes of users Can better target users and their needs

Khan Academy Challenge: increase engagement and the rate at which people learn Used funnels to optimize search and registration processes Start with a definition for “user engagement”

Jawbone Challenge: Assess the viability of Jawbone UP Used Segmentation reporting to better understand their users Helps to build customer archetypes Faster iterations and faster time to product-market fit

Cohort analysis Cohort analysis Renewal and upsell rates Return on marketing investment

Highly Loyal Customers

Highly Loyal Customers