The document discusses digital direct marketing and targeting approaches. It provides an overview of targeting basics, applications, approaches, options and attribution. It also discusses targeting technology, including off-site and on-site providers, as well as integration options and limitations. Finally, it covers targeting management strategies around developing a strategy, defining segments, and ongoing processes.

1. [ Digital Direct Marketing ]
From prospect to customer – smart
targeting at different stages of the
customer lifecycle

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Everyone has preferences.
That is human nature. Users inform us of
their preferences through online behaviour.
The ability to make these insights actionable
and to deliver more relevant content creates
a better experience for users as well as
better results for businesses.

3. [ Overview ]
 Targeting basics
– Targeting applications
– Targeting approaches
– Affinity vs. one-to-one
– Targeting options
– Attributing success
 Targeting technology
– Off-site providers
– On-site providers
– Technology limitations
– Integration options
 Targeting management
– Strategy development
– Internal processes
– Potential segments
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6. [ Targeting basics ]
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7. [ Targeting applications ]
 Acquisition
– Convert prospects
 Retention
– Up-sell and cross-sell
– Reduce churn
 Branding
– Convert prospects
– Build customer loyalty
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8. [ Targeting approaches ]
 Contextual targeting
– Ads based on viewed content
– Anonymous prospects (and customers)
 Behavioural targeting
– Ads based on past behaviour
– Anonymous prospects (and customers)
 Profile targeting
– Ads based on user profile database
– Identified customers
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10. [ Affinity targeting ]
 Function of behavioural targeting
– Grouping of visitors into major segments
– Based on content and conversion behaviour
– Ease of use vs. reduced targeting ability
 Most common affinities used
– Brand affinity
– Image preference
– Price sensitivity
– Product affinity
– Content affinity
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11. [ Affinity targeting ]
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Different type of
visitors respond to
different ads. By
using category
affinity targeting,
response rates are
lifted significantly
across products.
Message
CTR By Category Affinity
Postpay Prepay Broadb. Business
Blackberry Bold - - - +
5GB Mobile Broadband - - + -
Blackberry Storm + - + +
12 Month Caps - + - +

12. [ Targeting options ]
 Off-site
– Contextual targeting
– behavioural targeting
 Based on generic online behaviour
 Based on specific site behaviour
 On-site
– Contextual targeting
– behavioural targeting
 Based on specific site behaviour
– Profile targeting
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13. [ Attributing success ]
 View-through conversion
– Ad exposure sufficient
 All ads (or last) user was exposed to receive conversion credit
 Use in combination with click-through conversion tracking
 Cookie expiration settings should be sensible
 Click-through conversion
– Ad click-through required
 Only ads user responded to can receive conversion credit
 Define what ad response receives credit
– First, last, all equally, all partially
 Cookie expiration
– Define duration in days ads can claim conversion credit
 Survey research can help examine ad recollection rate
 Usually different for on-site vs. off-site ads
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14. [ Success attribution models ]
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AD 1
$100
AD 3
AD 1
$100
AD 2
$100
AD 3
$100
$100
$100
AD 1 AD 2
AD 3
$100 $100
Last ad gets
all credit
First ad gets
all credit
All ads get
equal credit
AD 1
$33
AD 2
$33
AD 3
$33 $100
All ads get
partial credit
AD 2

15. [ Targeting technology ]
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16. [ Off-site targeting platforms ]
 Ad servers
– Eyeblaster
– DoubleClick
– Faciliate
– Atlas
– Etc
 Ad Networks
– Google
– Yahoo
– ValueClick
– Adconian
– Etc
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http://en.wikipedia.org/wiki/Contextual_advertising, http://hubpages.com/hub/101-Google-Adsense-Alternatives,
http://en.wikipedia.org/wiki/Central_ad_server, http://www.adoperationsonline.com/2008/05/23/list-of-ad-servers/,
http://lists.econsultant.com/top-10-advertising-networks.html, http://www.clickz.com/3633599,
http://en.wikipedia.org/wiki/behavioural_targeting

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18. [ On-site targeting platforms ]
 Test&Target (Omniture, Offermatica, TouchClarity)
 Memetrics (Accenture)
 Optimost (Autonomy)
 Kefta (Acxiom)
 AudienceScience
 Maxymiser
 Amadesa
 Certona
 SiteSpect
 BTBuckets (free, targeting only)
 Google Website Optimizer (free, testing only)
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19. On-site
segments
Off-site
segments
[ Matching segments are key ]
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On and off-site targeting platforms should use
identical triggers to sort visitors into segments

20. [ Technology limitations ]
 JavaScript
– Relies on JavaScript to be enabled
 Cookies
– Relies on cookies for identification
 http://blogs.omniture.com/2006/04/08/15-reasons-why-all-
unique-visitors-are-not-created-equal/
 Multiple users per computer
 Multiple computers
 Cookie deletion
 Segments
– Can’t find profitable segments
 Content
– Can’t produce quality content
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21. [ Integration options ]
 Web analytics
– Record behavioural segments allocated through on-site targeting
platform in web analytics platform as well for each visitor
– Example: break down site traffic and campaign
responses by product category affinity
 Ad serving
– Replicate behavioural segments allocated through on-site
targeting platform in off-site ad serving environment
– Example: use on-site targeting platform to dynamically write
ad server tags into each page if visitor is in specific segment
 Affiliates
– Implement on-site targeting platform tags on affiliate
sites in order to grow targeting cookie pool faster
– Example: display customized ads to first time site visitors
although they have only visited affiliate sites so far
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22. [ Integration options ]
 Email
– Adjust email content for customers based on behavioural
segments allocated through on-site targeting platform
– Example: email customers product suggestions based on
their current content affinity and position in purchase funnel
 CRM
– Add customer profile data to on-site behavioural parameters
– Example: record customer’s profitability in on-site targeting
platform upon login on email click-through
 Offline
– Adjust on-site content based on unique offline call to action
– Example: visitors using a specific call to action see on-site
ads matching the offline ads to guarantee consistency
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23. website
data
customer
data
campaign
data
[ Maximise profiling data ]
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24. [ Targeting management ]
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25. 1. Define success
2. Conduct research
3. Define segments
4. Validate segments
5. Define content
6. Test content
7. Business rules
8. Start targeting
9. Communicate results

[ Keys to effective targeting ]
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26. [ Strategy and execution ]
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Ongoing
Targeting
Success
Content
Segments Resources
Process
Resource training
Content production
Platform maintenance
Campaign integration
Ongoing reporting
Agency processes
Success definition
Consumer research
Segment definition
Segment validation
Content testing
Business rules

27. [ Prospect targeting parameters ]
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28. -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
[ Customer targeting journey ]
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Retention
Consideration
Customer Profile
Prospect
Visitor Behaviour
Customer
Prospect sees banner ad, no response
Prospect sees print ad, executes unique search, sees customized offers on site
Prospect visits retail store for demonstration, receives personalized voucher
Referral from affiliate site, prospect sees customized offers on site
Prospects clicks on paid search, starts checkout using voucher but leaves
Prospect receives reminder email, finishes online purchase
Customer frequently visits specific product pages
Customer reads news online, sees banner for special customer offer
Receives welcome email with product FAQ
Customer visits online help site instead of calling call center
Customer receives email with customized content, upgrades online
Customer visits website, sees messaging emphasising upgrade benefits

29. [ Add customer parameters ]
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one-off collection of demographical data
age, gender, address, etc
customer lifecycle metrics and key dates
profitability, expiration, etc
predictive models based on data mining
propensity to buy, churn, etc
historical data from previous transactions
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 promotion responses
emails, internal search, etc
Site Behaviour
UPDATED CONTINUOUSLY

30. [ Multiply identification points ]
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0%
20%
40%
60%
80%
100%
120%
140%
0 4 8 12 16 20 24 28 32 36 40 44 48
Weeks
Probability of identification through cookie

31. [ Email identification points ]
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Advertising
Campaign
Cookie ID
Website
research
Fulfilment
Phone
Conversion
Retail
Conversion
Online
Conversion
Fulfilment
Fulfilment
Website
research
Website
research
Online Order
Confirmation
Online Receipt
Confirmation
Online Receipt
Confirmation
Online Receipt
Confirmation
@
@
@

32. Avinash Kaushik: “The principle of garbage in,
garbage out applies here. […] what makes a
behaviour targeting platform tick, and produce
results, is not its intelligence, it is your ability to
actually feed it the right content which it can then
target […]. You feed your BT system crap and it will
quickly and efficiently target crap to your customers.
Faster then you could ever have yourself.”
[ Quality content is key ]
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33. [ About us ]
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34. [ Datalicious services ]
30/01/2015
Web Analytics Solutions
© Datalicious Pty Ltd
Data
Marketing System Integration
Cross Channel Media Tracking
Insights Action
Online Surveys/Panels
Omniture Specialists
Google Analytics Specialists
Campaign Reporting
Competitor Analysis
Keyword Research
Segmentation/Data Mining
Market/Consumer Trends
Search Lead Media
A/B, Multivariate Testing
Internal Search Optimisation
Campaign Optimisation
Targeting/Merchandizing
Staff Training/Workshops
Quantitative Research
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35. [ Datalicious clients ]
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36. 30/01/2015 © Datalicious Pty Ltd
insights@datalicious.com
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