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Analytics Pros © 2014
Measuring the Physical World
Sam BriesemeisterJan. 23, 2014 @ 15:00
Analytics Pros © 2014 | Confidential
Analytics Pros © 2014
What is this “Physical World”?
What is digital?
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Physical Media
Analog data● Light● Heat● Sound● Radio waves● Gravity
Any kind of sensor
Interpretation● Things● Behaviors
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Modeling the Physical World
Human language● <subject> <verb> [<preposition>] <object>
Examples● User enters store● User looks at sign● User picks up product● User buys product
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Making it Digital
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Digital Signal
● Motion sensors● Cameras &
Imaging○ Photo analysis○ Triangulation
● WIFI signal & radio○ Identification○ Triangulation
● Audio● GPS● Kinect
○ Light○ Thermal
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Measuring You: Identification
● Biometric signature● RFID tagged items● Object recognition
○ Facial analysis● Temporary image analysis
○ Color patterns, etc● WIFI MAC address
○ Project Euclid, etc
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Raspberry Pi Tracking
● PIR sensor detects movement● Other sensors available for better accuracy● Common programming environments● Open source, well-documented● Fairly easy to program● Quite inexpensive
Everybody’s doing it...
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Modeling into Google Analytics
Simple structures, the easy part● Object representation: page URL + title?● Actions: events● Sessions: consecutive events
Some engagement may not fit GA’s model
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Modeling into Google Analytics
Attribution● Important question
Possibilities● integrate promotion in mobile app presence● detection from prior visitor history
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IdentityMulti-Sensor ID and Automation
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Fragmentation
Identity Context Value
Imaging/Facial X
Mobile WIFI ID Ya
Mobile App ID Yb
Web User ID Z
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Identity Aggregation
Identity Context Value
Imaging/Facial X
Mobile WIFI ID Ya
Mobile App ID Yb
Web User ID Z
Multiple Sensors App
Trigger
Login
Identity Relationship● [X, Ya, Yb, Z …] Identity
Service
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Integrating Aggregated Identity
Central Identity Service● Single, authoritative identity● Collects identification from devices● Serves reconciled identity to devices● Pushes identity updates to Analytics
Analytics Model● Google’s User ID feature (closed beta)● User-scope custom dimension
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Identity Management Model
Google Analytics
Device#1
Identity Service
Tracking Service
Device#2
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Identification in Google Analytics
● Google Analytics’ Client/User ID○ Native stitching (forward-only)○ Simple aggregate reporting○ Not available in native reports
● Custom Dimensions: User Scope○ Supports retroactive reconciliation○ Non-native stitching (i.e. external reports)○ Available in native custom reporting
Use both?
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Examples
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Example: Physical Display
Define the Identity:● Mobile App ID (app login) +● Mobile WIFI ID +● Photo profile ID
Define the interaction:● Category: physical display● Action: impression● Label: display ID or name
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Example: Physical Display (cont)
1. Imaging analysis calculates profile2. Photo analysis + WIFI triangulation
a. Identify mobile ID3. Mobile Application detects display RFID4. Submit combined ID to Central ID service5. Central ID service returns reconciled ID6. Tracking sent to Google Analytics with:
a. Updated user ID, and/orb. User-scope custom dimension
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Example: Physical Display (cont)
Purchase process:● Identification features
○ Mobile WIFI ID (triangulation)○ Mobile App ID + NFC if available○ Credit card
● Track Transaction● Evaluate products against display ad
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Example: Physical Display (cont)
What is a conversion?● Brand match on products● Specific product match
Define the interaction:● Category: physical display● Action: conversion ● Label: display ID previously seen (or name)
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Ethics and Privacy
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What are you collecting?
● Impression● Conversion● Engagement● Interaction● User history
○ aggregate value○ lifetime revenue
Everything?
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Why are you collecting it?
● Understanding your audience○ Acquisition … who are they?○ Engagement & Behavior … what are they doing?
● Effectiveness of marketing investment○ Conversion … is this the right audience?○ Revenue … how can I improve this ROI?
Why might you need to know them individually?
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What is Anonymity?
Is it…?● Inability to identify● Refusal to identify● User intent to remain unidentified● Refusal to self-identify
What does your user expect?
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Intentional Anonymity
Considerations● Small subset of users actually delete cookies● Isolated data may still be valuable
○ Short-term life “sampling” effect○ Data skew is often pessimistic
● Do you respect your users?
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Honoring Anonymity in Physical Space
● Opt in ○ Membership cards with RFID
■ Incentive: discount with card purchases○ Mobile app settings
■ Incentive: promotions available only on mobile
● Opt out○ May not be practical; best assume anonymity
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Honoring Anonymity in Physical Space
● Assume anonymity (opt in)○ Short-term identity retention
■ On personal devices■ On platform services (i.e. central ID)
○ Use identity info for Uniqueness only■ Identity local to physical platforms
● Assume persistent identity (opt out)○ Store identifiers on personal devices/cards/RFID○ Shared identity with physical platforms
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Lifecycle of Identity
● Depends on industry?○ Travel & Vacation: long conversion cycle○ Home electronics: relatively short conversion cycle
● Legal requirements● Corporate privacy policies
Can you predict a high-value, long-life customer with time-limited data?● Probably, but maybe not in GA
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Questions