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What is user analytics
 

What is user analytics

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Summary overview describing User Analytics

Summary overview describing User Analytics

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    What is user analytics What is user analytics Presentation Transcript

    • Monetrix User Analytics April 2012 Slide 1
    • There is no longer such thingas an offline business; everycompany must have a digital strategy to survive. 2012 © Monetrix. Commercially confidential Slide 2
    • Fortune 1000 – Top User-Centric Companies Technology Retail Airlines Financial Other 2012 © Monetrix. Commercially confidential * Source: “Users Not Customers”, Aaron Shapiro 3 Slide
    • The most successful companies focus on users first, and look at customers as a subset of the larger group.“Create powerful user experiences “Keep users happy, and customersinstead of just trying to get people will follow” to buy stuff” “grow your user base and your USERS customer base grows as well” CUSTOMERS * Source: “Users Not Customers”, Aaron Shapiro 2012 © Monetrix. Commercially confidential Slide 4
    • Typical Web Application User Funnel Attracting and monetizing an online audience is a marketing challenge. 10,000,000 Registered Users 1,964,286 Active Users (19.6%) 158,929 Paying Users (1.6%) 15,893 Top Customers (0.2%) 2012 © Monetrix. Commercially confidential Slide 5
    • There is a huge opportunity toanalyze online and offline user data to improve sales and marketing effectiveness. 2012 © Monetrix. Commercially confidential Slide 6
    • However...Organizations Struggle With Lack of resources to dedicate to analytics Huge data volumes across many online and offline data sources Poorly instrumented web applications aren’t capturing the right data points Complex data structures and ETL tools for collecting and enriching data Inability to make analysis easy for the business • Complex database schemas that end-users users don’t understand • Heavy reliance on skilled SQL programmers to answer basic queries • Poor query performance when using self-service query tools 2012 © Monetrix. Commercially confidential Slide 7
    • Online and Offline Data Sources Offline Online  Twitter  Finance/Accounting  Facebook  Marketing Apps  Youtube  CRM  LinkedIn  Inventory  Website  Manufacturing Apps  Mobile  ERP  Ecommerce  Other DBs & Files  Custom Web App 2012 © Monetrix. Commercially confidential Slide 8
    • Data Capture API API for Data Capture Online  Website  Mobile  Ecommerce  Custom Web App 2012 © Monetrix. Commercially confidential Slide 9
    • User Analytics Application Offline Online  Twitter  Finance/Accounting  Facebook  Marketing Apps  Google Analytics  CRM  LinkedIn  Inventory  Website  Manufacturing Apps DistributedDatabaseTechnology  Mobile  ERP  Ecommerce  Other DBs & Files  Custom Web App Node.jsCSV DataFileLoader Node.jsAPI and Custom 2012 © Monetrix. Commercially confidential ETLTransformations Connectors Slide 10
    • Problems Solved...w Monetrix API & Pre-Built Application Lack of resources to dedicate to analytics Huge data volumes across many online and offline data sources Poorly instrumented web applications aren’t capturing the right data points Complex data structures and ETL tools for collecting and enriching data Inability to make analysis easy for the business • Complex database schemas that end-users users don’t understand • Heavy reliance on skilled SQL programmers to answer basic queries • Poor query performance when using self-service query tools 2012 © Monetrix. Commercially confidential Slide 11
    • What is Monetrix?Monetrix is a user analytics application designed tohelp data-driven marketers be more user-centricand effective at growing and monetizing the usersof their digital channels. 2012 © Monetrix. Commercially confidential Slide 12
    • What does it do?Monetrix captures, aggregates and enriches userdata from a company’s online & offline source tocreate a 360° user view made of user metrics,attributes, and profiling strategies. Marketers canaccess this view with a web-based interface togain customer insight and take action. 2012 © Monetrix. Commercially confidential Slide 13
    • 360° User View Base Profile - (age, gender, channel, platform, version, geo, primary use, browser) Social Platform Profiles – (likes, dislikes, demographics) 360° User View Tenure – days since the first time they did something Recency – days since the last time they did something Frequency – count how often they do something Monetization – count or rank of how much they spend Pre-Built Data Capture Sociability – count or rank of how social they are Pre-Defined CSV Input Files Connectors API Engagement – count or rank of how engaged are Users.csv App Instrumentation Events.csv Movement – what types of movements have they done Sessions.csv Transactions.csv 2012 © Monetrix. Commercially confidential Slide 14