Mobile Analytics - The intersection of Product and Marketing

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Mobile Analytics Presentation By: Chad Pavliska

description

Analytics is at the heart of Lean Startups (learning from empirical data), Marketing (Are our marketing investments working), and Product (Are users engaged). This presentation was given at the Austin iPhone Meetup at Capital Factory in September 2014.

Transcript of Mobile Analytics - The intersection of Product and Marketing

Page 1: Mobile Analytics - The intersection of Product and Marketing

Mobile AnalyticsPresentation By: Chad Pavliska

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Overview

• Intro to Analytics

• Technical deep dive

• The business side of analytics

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MARKETING PRODUCTAnalytics

Design

Engineering

Branding

Execution

InvestorsExecutiv

es

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State of Mobile Analytics

• Still in Early Adopters stage

• Heavily Fragmented market

• New entrants and new categories of tools

• Analytics, People, User Testing, User Feedback, Error Reporting, etc.

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PRO TIP: Know thy vendors business model to understand their focus and direction.

Advertiser or Analytics vendor?

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Aggregate Data

Bulk, anonymous data that shows big picture trends

Individual Data

Data specific down to a single users actions in the app

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Quantitative Data

Generates objective numerical data that can be measured and analyzed.

Qualitative Data

Focus on subjective written or verbal data which can then be interpreted.

“I just don’t like this feature…” - User

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– Steve Blank, Customer Development

“The answers are outside the building.”

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Part II: Tech Deep Dive

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Building Blocks

• Events are the foundation

• Events contain properties

• Some tools allow tracking events by distinct user

• Reports are created based on events and filtered and/or segmented by properties

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Mixpanel Walkthrough

• Engagement Reports

• People Reports

• Client Code Demo

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That’s one tool, what if we want to switch

vendors?

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Hello, Segment.IO

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Segment.io

• Integrations

• Debugger

• Client SDK Architecture and Demo

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Implementation Tips

• Resist temptation to use the business analytics as a centralized debug logging mechanism

• Do read the client SDK code which is often ahead of online documentation

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PART III: Business of Analytics

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Pirate Metrics! AARRR!

• Acquisition

• Activation

• Retention

• Referral

• Revenue

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Lean Startup

• Use the scientific method and empirical data to drive decision making

• Treat everything as a hypothesis

• Build -> Measure -> Learn loop is the fundamental activity of a startup.

• All startup processes should be geared towards accelerating the BML loop.

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Growth Hypothesis

How new customers will discover a product?

Value Hypothesis

Does a product deliver value to customers once they are using it?

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– Eric Reis, on the Value Hypothesis

“If you are building the wrong thing, optimizing the product or it’s marketing

will not yield significant results.”

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– Eric Reis

“"The only way to win is to learn faster than anyone else.”