Magic exist by Marta Loveguard - presentation.pptx
Offline to Online Targeting in a Multi-Device, Multi-Channel World
1. 1 Information contained herein is property of HackerAgency and is strictly confidential.
MOVING BEYOND BEHAVIORAL
Offline to Online Targeting in a Multi-Channel/Multi-Device World
5. 5
WHAT ARE WE TALKIN’ ABOUT?
• Targeting an audience vs optimizing a channel
• Connecting digital systems
• Leveraging search buying signals
• Following the prospect across devices
• How to translate offline data to online results
7. 7
AUDIENCE SEGMENT TOUCH POINT MAP
First Eligible
Seniors entering
Medicare eligibility
Experience Triggers
- Age-in at 65
- Start mktg at 64
- Special needs
- Start mailing 6
months ahead
Customer Types
- Low income
- Retired/Retiring
- On-going worker
- Special needs
Phase
(Time Frame)
Awareness
(6 - 18 months)
Research
(3 months)
Choice Reduction
(1 month)
Purchase
(1 week)
Customer
Goal
What are the questions
customers ask at each
stage? From general to
specific
Key Triggers,
Buy Signals
What keywords,
behaviors, offline
triggers, etc. indicate
interest?
Key
Channels
Which marketing
channels have the
biggest impact per
stage?
Key
Identifiers
What are the unique
identifiers – cookies,
email address, etc. –
that the channels for
that stage use
12. 12
Best Case Scenarios
• Top paid result + top organic result = ~40% CTR
• Top paid result only = ~5% CTR
• Top organic result only = ~30% CTR
Worst Case Scenario
• You don’t show up at all in either = 0% CTR
WE KNOW SEARCH IS AWESOME, BUT
13. 13
YOUR KEYWORD LIST = BETTER TARGETING
• Data from 8 billion searches – including data on Google searches
• Associate cookies to search terms
• Leverage current keyword list
• Message searchers that did or didn’t click on your ads
Medicare insurance
22. 22
HOW OFFLINE TO ONLINE WORKS
Data Safe Haven
Street Address
Phone Number
Email Address
Any Channel
Matchback
Data Process
23. 23
LIST DRIVEN DIGITAL PRO’S AND CON’S
Pro’s
• Leverages offline data
• Extends life of data models
• Provided definitive lift metrics
across sales channels
• Sales channel agnostic
• Optimizes media targeting
Con’s
• More expensive on both a
CPM and process basis
• Harder – more data work
• Doesn’t optimize channels
24. 24
WRAP IT UP!
• Dig into the buyer’s journey
• Set expectations at the buy stage level
• Leverage as many of the buying signals as
possible in the appropriate channels
• Connect as many systems as possible
• Utilize offline and online data in a privacy
centric, but measurable program
25. 25
THANK YOU!
• HMU with questions, comments, etc.
– Scott.fasser@hal2.com
• We’re hiring!
– Check our job board for openings – www.hal2l.com
– Especially interested in a Media Coordinator
Editor's Notes
PRESENTED BY <NAME> | HACKER GROUP
We are classic but not traditional
Leaves out a lot > social, mobile, local search, view based
Size means more channels. Still leaves out a lot.
One example of how Facebook Exchange works
Even though this is first party data from Jet Blue > any unique identifier that can be associated to a Facebook ID can be linked into the Facebook Exchange.
Chango search retargeting out performs behavioral targeting and keyword display. Not as good as search.