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Beyond Page Views: Modern Analytics for Online Marketing

Casey WintersOnline & Interactive Marketing Director

GrubHub@onecaseman

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What are we talking about today?

• The measurement, collection, analysis, and reporting of internet data for the purposes of optimizing web usage.

• EASIER SAID THAN DONE!

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A little history• The early web was built on the concept of static pages• Each page was a chance to show more banner ads and

increase advertiser impressions• So, websites optimized revenue by driving as many page

views as possible

• It doesn’t work that way anymore• Websites have many different business models that

require different optimization methods• Many websites, especially apps, lack a page-based

hierarchy thanks to new programming languages and browser capabilities

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So what are we optimizing towards now?

Short-term metrics:• Leads• Purchases• Conversions• Feature Engagement• Virality

Long-term metrics• Lifetime Value• Days active• Attrition

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Yet, most analytics tools still operate under this page-based framework and can’t measure any

of those things easily

• This creates a culture of focus on “vanity metrics” that don’t drive insights or optimization:– # Uniques– # Visits– Page views/visitor– # Downloads

• For years, marketers and engineers have been tracking to hack these tools to track what they actually care about

• Marketers were forced to learn SQL to retrieve the data they actually needed to do measure their performance

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Anyone remember BranchOut?

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Anyone remember BranchOut?

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Anyone remember Viddy?

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Anyone remember Viddy?

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Anyone remember Viddy?

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Anyone remember Viddy?

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Things you can miss in a page-based framework

• New vs. repeat conversion rates• Lack of cross platform analytics e.g. iPhone app vs.

website performance• Cross-platform usage• # of site uses before conversion occurs• Understanding lifetime value or retention• Mobile attribution• Understanding how online and offline ad impressions

drive value

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So, what’s the new model?• Events instead of Pages• Individual User Data instead of Aggregate Numbers

Key reports:• Cohort analysis• Conversion funnel• Attribution models

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The new key metrics• Daily/Weekly/Monthly Active Users• Average Frequency per Active User• Conversion rates

– New vs. Existing– By marketing channel– By platform

• Cost per Acquisition– By marketing channel

• Lifetime Value– By marketing channel– By platform

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Out with the old and in with the newOld guard:• Adobe SiteCatalyst (Omniture)• Coremetrics• WebTrends• Google Analytics

New breed:• Mixpanel• Kiss Metrics• RJ Metrics• Kontagent (mobile apps only)• Localytics (mobile apps only)

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A note on attribution• Many marketers are still using last touch attribution• As your marketing methods expand, this becomes less

and less accurate• New tools look at correlations of patterns of marketing

exposures (online impressions, search clicks, offline exposure) and model to create fractional attribution models using statistical inference– Convertro– Adometry– Clearsaleing– Visual IQ

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Mobile Marketing Attribution• Normal web funnel:

– Ad click– Arrive on website– Website activity

• Mobile funnel:– Ad click– Arrive at App Store (untrackable for iOS)– Download app (unattributable for iOS)– Open app– App usage

• New solutions:– Mobile App Tracking by Has Offers– AppsFlyer– Kontagent– Mobile ad vendors e.g. Apsalar

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So what is big data for?• Big data describes data sets so large that

databases can’t handle them• This is where things get beyond marketers’

ability to segment data and need technical help

• Used for a lot of statistical correlation inside of massive amounts of related data

• Tools:– Hadoop– MapReduce– Hive