using big data to engage & convert valuable customers...8 big data defined “it doesn’t fit...
TRANSCRIPT
Using Big Data to Engage & Convert
Valuable Customers March 2014
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U.S. 50 States
EMEA 45 Countries
S. AMERICA 9 Countries
ASIA 12 Countries
Sojern by the Numbers in 2013
Global Data Footprint
Impressions
10B
Heads in Beds
1.1MM
Boarding Passes
280MM
Car Rentals
1.9MM
Global Clients
500+
Traveler Profiles
160MM+
Locations
11 Employees
90
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Topics
+Big Data
+Data Types
+Using Data in the Marketing Funnel
+Using Data in Results Analysis
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I Don’t Care What the Data says…
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Question: Find x
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Topics
+Big Data
+Data Types
+Using Data in the Marketing Funnel
+Using Data in Results Analysis
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25,000,000,000,000,000,000 bytes
of digital data
created every day
SearchEngineLand February 2013
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Big Data Defined
“It doesn’t fit on excel” Stephane Hamel, CSO Cardinal Path
“ High volume, high velocity, high variety information assets that demand cost-efficient, innovative forms of processing for enhanced insight and decision making”
Gartner
4 Vs of Big Data: “Volume, Variety, Velocity, Veracity”. IBM / Forrester
“… data centric applications …driving some experience to a customer and causing them to do some things in real time”
Paul Maritz, CEO Pivotal
9 Offsite2013
Real Time Digital Marketing
• Should we buy an
impression against
this user?
• How much should we
pay/bid on this
impression?
• What creative should
we show them?
ALL HAPPENS IN
ABOUT 80 milliseconds
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Bidding on an impression in
real time to show one specific ad
to one consumer in
one specific context at
the right time
Audience Data + Programmatic Buying
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A Huge Topic….
… right message, to the right person, at the right time, in
real time
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Digital Pathway to a Booking
Beyond The Last Click: Google White Paper 2011
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Topics
+Big Data
+Data Types
+Using Data in the Marketing Funnel
+Using Data in Results Analysis
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Wrong?
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Capturing, Curating and Activating data…
Data Sources
TRAVEL
RESEARCH
BOOK
Activate Engage Travellers
Via Media
Channels
Curate Build/Maintain
Traveller
Profiles
Capture Collect/Aggregate
Data
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Data Types for Real Time Targeting
Internal: + Onsite visits / behaviour (who / what)
+ CRM (who / what)
+ Loyalty (who / what)
+ Product / yield (what)
External: + Intent (who / what)
+ Behavioural / history (who / what)
+ Context (where)
Derived / Predicted: + When
+ Who / what
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For a Hotel Group….
Capture / Analyse
For powerful, cost effective customer acquisition I want to know key data
attributes of the customers I’m engaging with
Billions of Data
Points
Key Data Attributes
+ Destination intent
+ Dates of travel
+ Trip length
+ Party size
+ % audience overlap
+ Past booking behaviour
+ Loyalty status
+ Room availability
+ Room yield
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Deriving and Targeting the “When”
6%4%
4%
23%
32%
10%
19%
31+ 22-30 15-21 8-14 3-7 1-2 0DAYS
DAYSBETWEENBOOKINGHOTEL&STAY
hot el
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Topics
+Big Data
+Data Types
+Using Data in the Marketing Funnel
+Using Data in Results Analysis
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Whole Funnel Marketing
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Whole Funnel Marketing
BRANDING
Ave viewer watches 20+ hours of online video / month - Rich branding - Interaction /
call to action opportunities
Audience Targeting - Destination
intention - x weeks before
intended trip - E.g. hotel
facilities
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Whole Funnel Marketing
PROSPECTING
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Whole Funnel Marketing
PROSPECTING
Audience Targeting: new customers - Destination intent - Party size - Date travelling - Act-alikes - Dynamic creative:
destination + product offer
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Whole Funnel Marketing
SMART RETARGETING
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Whole Funnel Marketing
SMART RETARGETING
Retargeting site visitors using e.g: - Loyalty status - Product yield /
availability - Offsite
behaviour
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Topics
+Big Data
+Data Types
+Using Data in the Marketing Funnel
+Using Data in Results Analysis
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I Have the Data …
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Tale of 2 Campaigns…
Campaign 1 Campaign 2
Cost $100,000 $100,000
Conversions 3,784 3,307
CPA $26 $30
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Tale of 2 Campaigns…
Campaign 1 Campaign 2
Cost $100,000 $100,000
Conversions 3,784 3307
CPA $26 $30
Conv / Loyalty Status:
Highest Tier 2562 312
High Tier 972 563
Mid Tier 98 752
Low Tier 22 807
Non Member 130 873
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Tale of 2 Campaigns…
Campaign 1 Campaign 2
Cost $100,000 $100,000
Conversions 3,784 3307
CPA $26 $30
Conv / Loyalty Status:
Highest Tier 2562 312
High Tier 972 563
Mid Tier 98 752
Low Tier 22 807
Non Member 130 873
Non Highest Tier CPA $97 $45
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Extrapolating from Incomplete Data
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Search for Incrementality
Prospecting Retargeting
Hotel Sub Brand 1 13% 12%
Hotel Sub Brand 2 11% -4%
Hotel Loyalty Programme 4% -8%
Lift studies can help refine targeting and attribution
Charity ads vs. campaign ads to same audience targeted profiles for a major hotel group
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Attribution Options
Last Click All credit goes
to the last click
First Click
Post View
All credit goes
to the first click
Last channel
to show an ad
gets the credit
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Clicks?
95% of clicks
don’t convert
90% of converters
don’t click
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Advanced Attribution
Source: Tagman VIS
Algorithmic
Attribution
Let the data
decide where
to assign
credit
37 Offsite2013
Marketers will say my job has
always been to understand
customer segments. The shift is
to go from the segment to the
individual. It spells the death of
the average customer.
- Ginni Rommety, CEO of IBM
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“Who cares? It’s what you’re doing with it…” Stephane Hamel, CSO Cardinal Path