Date post: | 29-Nov-2014 |
Category: |
Technology |
Upload: | datalicious-pty-ltd |
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[ Why data is sexy ] No really, it is!
Campaign data
Customer data
Compe5tor data
Consumer data
[ Main data categories ]
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Campaign data
Awareness Interest Desire Ac5on Sa5sfac5on
Online surveys, site polls
Web analy5cs
[ Defining analy:cs strategy ]
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Social media
Search, display ads
Social media
[ Single source of truth ]
data
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[ De-‐duplica:on across channels ]
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Banner Ads
Email Blast
Paid Search
Organic Search
$ Bid Mgmt
Ad Server
Email PlaGorm
Google Analy:cs
$
$
$
Omniture PlaGorm
$
$
$
[ De-‐duplica:on across channels ]
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[ Success aIribu:on models ]
Banner Ad $100
Email Blast
Paid Search $100
Banner Ad $100
Affiliate Referral $100
Success $100
Success $100
Banner Ad
Paid Search
Organic Search $100
Success $100
Last channel gets all credit
First channel gets all credit
All channels get equal credit
Print Ad $33
Social Media $33
Paid Search $33
Success $100
All channels get par:al credit
Paid Search
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[ Campaign stacking by channel ]
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Chart shows percentage of channel touch points that lead to a conversion.
Neither first nor last-‐click measurement would provide true picture
[ Search call to ac:on ]
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[ Analyse channel overlap ]
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Total Ac:ons: 2,023
Display Media 1669 (61.2%)
$125 -‐ $200 CPA
Paid Search 301 / 11.1%
$200 -‐ $500 CPA
189 (62%)
112 (38%)
Straight to Site 1208 (44.3%)
621 (52%)
587 (48%)
DM & EDMs
$200 -‐ $400 CTA
Radio &
Other ATL
Organic Search 493 (18%)
179 (37%)
314 (63%)
Partners
Call Centre
[ Cross-‐channel impact ]
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[ Email iden:fica:on points ]
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Adver5sing Campaign
Cookie ID
Vodafone.com.au Research
Credit Check Fulfilment
Phone Conversion
Retail Conversion
Online Conversion
Credit Check Fulfilment
Credit Check Fulfilment
Vodafone.com.au Research
Vodafone.com.au Research
Online Order Confirma5on
Online Receipt Confirma5on
Online Receipt Confirma5on
Online Receipt Confirma5on
@
@
@
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Customer data
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[ Store locator searches ]
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[ Reasons for store drop-‐out ]
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About a third of those dropping out intend to come back again. 1 in 5 will go away and think more about their purchase. Only 10% have inten5ons purely to use the store for research.
[ Targe:ng framework ]
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-‐12 -‐11 -‐10 -‐9 -‐8 -‐7 -‐6 -‐5 -‐4 -‐3 -‐2 -‐1 0 1 2 3 4 5 6 7 8 9 10 11 12
Weeks
Reten5on
Considera5on
Customer Profile
Prospect
Visitor Behaviour
Customer
[ Prospect targe:ng parameters ]
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[ Affinity targe:ng in ac:on ] Different types of visitors respond to different ads. By using category affinity targe5ng, response rates are liced significantly across products.
Message Click-‐Through Rate By Category Affinity
Postpay Prepay Broadb. Business
Blackberry Bold - - - + 5GB Mobile Broadband - - + - Blackberry Storm + - + + 12 Month Caps - + - +
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On-‐site segments
Off-‐site segments
[ Matching segments are key ]
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On and off-‐site targe5ng plaeorms should use iden5cal triggers to sort visitors into segments
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[ Combining data sets ]
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one-‐off collec5on of demographical data age, gender, address, etc customer lifecycle metrics and key dates profitability, expira:on, etc predic5ve models based on data mining
propensity to buy, churn, etc historical data from previous transac5ons
average order value, points, etc
CRM Profile
UPDATED OCCASIONALLY
+ tracking of purchase funnel stage
browsing, checkout, etc tracking of content preferences
products, brands, features, etc tracking of external campaign responses
search terms, referrers, etc tracking of internal promo5on responses
emails, internal search, etc
Site Behaviour
UPDATED CONTINUOUSLY
Omniture Test&Target
Google Analy5cs
Omniture DataWarehouse
Vodafone Terradata
Omniture DataWarehouse
Eyeblaster
Omniture Discover OnPremise
Online behavioural data stored in Omniture for anonymous prospects and known customers
Customer status and product affinity for prospects and customers passed into Test&Target as well as Eyeblaster for advanced on and off-‐site targe5ng (e.g. help/support messages for
exis5ng customers, acquisi5on messages with customized plans for prospects, etc)
Data on MyVodafone registra5on status to iden5fy non-‐users in order to encourage online self-‐service
Data on MyVodafone self-‐service usage to iden5fy users with poten5al issues in order to increase customer sa5sfac5on
Data on campaign performance to iden5fy most suitable message content and 5ming for each customer or segment
Data on product preferences and research behaviour to customize product offering and feed into churn modelling
Customer data on self-‐service usage, campaign responses and product preferences are filtered against Terradata in Discover OnDemand, contact lists are generated and customized messages delivered through the most suitable channels
[ Where is the money ]
[ october 2007 ]
$
$
$ $
$
$
$
$
$
$
[ datalicious.com.au ]
[ Mosaic ]
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Compe:tor data
[ Brand search volume ]
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[ Market share trends ]
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[ Australia vs. New Zealand ]
[ september 2007 ] [ datalicious.com.au ]
australia.com vs. newzealand.com
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Consumer data
[ Search term volumes ]
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[ Media planning ]
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[ Leading lifestyles, 45+ ]
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Campaign data
Customer data
Compe5tor data
Consumer data
[ Main data categories ]
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