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WINE & WEB #66
HOW TO TRACK & ANALYZE
VISITORS ACROSS
MULTIPLE DEVICES
@matchnode @maddencm
@matchnodeWHAT’S TO COME – CONTENTS
1. WHY?
2. SOME TOOLS & PLATFORMS
3. THREE TYPES OF CROSS DEVICE TRACKING
4. KEY REPORTS
5. EXAMPLES
7. THE FUTURE
6. IS THIS CREEPY?
8. ACTIONABLE TAKEAWAYS
@matchnode
3.64 devices per digital consumer in the US
@matchnodeLead AdsWHY?
source: The Magic of Universal Analytics
The Old Analytics
@matchnodeLead AdsWHY?
source: The Magic of Universal Analytics
The “Real” Journey
@matchnodeSOME PLATFORMS & TOOLS
190K20K live sites
61K 253K
Builtwith: source
@matchnode3 TYPES OF CROSS-DEVICE TRACKING
1. Owning an eco-system (a “walled garden”)
2. Having visitors log in (“deterministic”)
3. Fingerprinting (“probabilistic”)
@matchnode1. WALLED GARDEN
+ large install / visitor base
+ used across multiple devices
+ analytics
+ ad platform
@matchnode1A. FACEBOOK’s WALLED GARDEN
reach
frequency
@matchnode1A. FACEBOOK’s WALLED GARDEN
reach
frequency
@matchnode1A. FACEBOOK’s WALLED GARDEN
@matchnode1B. GOOGLE’s WALLED GARDEN
Cross device retargeting + attribution
Session unification: link
No personally identifiable info
@matchnode1B. GOOGLE’s WALLED GARDEN
@matchnode
Source
1B. GOOGLE’s WALLED GARDEN
@matchnode2. DETERMINISTIC (LOGGED-IN)
@matchnode3. PROBABILISTIC (FINGERPRINTING)
@matchnode3. PROBABILISTIC (FINGERPRINTING)
@matchnode3. PROBABILISTIC (FINGERPRINTING)
https://amiunique.org
browser vs device fingerprinting
@matchnode3 TYPES OF CROSS-DEVICE TRACKING
1. Owning an eco-system (a “walled garden”)
2. Having visitors log in (“deterministic”)
3. Fingerprinting (“probabilistic”)
@matchnode
business insightslong term
@matchnodeTWO KEY REPORTS
2. Retention
1. Cohort
@matchnodeCOHORT REPORTS DEFINED
“a cohort is a group of people who share
a common characteristic or experience
within a defined period of time…
…analysis allows you to track groups of
people over long periods of time…
…track their activity apart from other
groups.” Source: KISSmetrics
@matchnodeBASIC COHORT EXAMPLE: SIGNUPS
@matchnodeCOHORT EXAMPLE: COUPONS & CHANNELS
@matchnodeCOHORT EXAMPLE: COUPONS & CHANNELS
Reorder
rate: all
traffic
@matchnodeCOHORT EXAMPLE: COUPONS & CHANNELS
Reorder
rate:
retailmenot
traffic
@matchnodeCOHORT EXAMPLE: COUPONS & CHANNELS
Compare a segment (retailmenot) to the whole
Retailmenot traffic
All traffic
@matchnode
FACEBOOK AD EXAMPLE: MESSAGING
UP AND DOWN THE FUNNEL
@matchnode
FACEBOOK AD EXAMPLE: MESSAGING
UP AND DOWN THE FUNNEL
@matchnode
FACEBOOK AD EXAMPLE: MESSAGING
UP AND DOWN THE FUNNEL
@matchnode
FACEBOOK AD EXAMPLE: MESSAGING
UP AND DOWN THE FUNNEL
@matchnode
TERMINAL RETENTION CURVE
% ACTIVE
(WEEKLY)
WEEKS OUT FROM SIGNUP
THE ULTIMATE RETENTION GRAPH
@matchnodeCREEPY OR NOT?
@matchnodeCREEPY OR NOT?
@matchnodeFTC’s COMMENTS
Source
“cross-device tracking facilitates seamless
experiences, helps to prevent fraud & more
effectively target ads, can increase
competition in advertising. However, often
takes place without consumers’
knowledge. limited choices to control such
tracking, and result in caches of more
sensitive data that need to be protected”
@matchnodeFUTURE IMPLICATIONS
Rearview mirror to predictive
End of privacy concerns
BUT own your data
Evolved enterprises
Source: https://michaelhaupt.com/the-future-of-marketing-and-advertising-e52663f63104#.drezur9n6
@matchnodeACTIONABLE TAKEAWAYS
1. Adopt a multi-device POV
2. Use Facebook ads as a testing ground
3. Start with identifying across sessions (small biz?
tend.io)
4. Advanced: try Mixpanel or KISSmetrics
@matchnodeRESOURCES
--ArsTechnica: Online Fingerprinting: link
--Limits to GA’s User ID Views: link
--Matchnode Analytics Podcast: link
--KISSmetrics blog: link
--Cardinal Path: 3 Types of Cross Device Tracking: link
--Data Does Good: link
--Foursqaure as Google Analytics for Physical World: link
@matchnode
Hit us up @Matchnode
Questions?

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