ADMA Digital Council: Digital Direct Marketing

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

5/26/09
© Datalicious Pty Ltd
2
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 asbetter results for businesses.

[ 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
5/26/09
3

5/26/09
4

5/26/09
5

[ Targeting basics ]
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
5/26/09
6

[ Targeting applications ]
Acquisition
Convert prospects
Retention
Up-sell and cross-sell
Reduce churn
Branding
Convert prospects
Build customer loyalty
5/26/09
7

[ Targeting approaches ]
Contextual targeting
Ads based on viewed content
Anonymous prospects (and customers)
Behaviouraltargeting
Ads based on past behaviour
Anonymous prospects (and customers)
Profile targeting
Ads based on user profile database
Identified customers
5/26/09
8

5/26/09
9

[ 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
5/26/09
10

[ Affinity targeting ]
5/26/09
11
Different type of visitors respond to different ads. By using category affinity targeting, response rates are lifted significantly across products.

[ Targeting options ]
Off-site
behavioural targeting
Based on generic online behaviour
Based on specific site behaviour
On-site
behavioural targeting
Based on specific site behaviour
Profile targeting
5/26/09
12

[ 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
5/26/09
13

[ Success attribution models ]
5/26/09
© Datalicious Pty Ltd, www.datalicious.com
14
AD 1
AD 2
AD 3$100
$100
Last ad gets all credit
AD 1$100
AD 3
$100
First ad gets all credit
AD 2
AD 1$100
AD 2$100
AD 3$100
$100
All ads get equal credit
AD 1$33
AD 2$33
AD 3$33
$100
All ads get partial credit

[ Targeting technology ]
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
5/26/09
15

[ Off-site targeting platforms ]
Ad servers
Eyeblaster
DoubleClick
Faciliate
Atlas
Etc
Ad Networks
Google
Yahoo
ValueClick
Adconian
Etc
5/26/09
16
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

5/26/09
17

[ 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)
5/26/09
18

[ Matching segments are key ]
5/26/09
19
On and off-site targeting platforms should use identical triggers to sort visitors into segments

[ 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
5/26/09
20

[ 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
5/26/09
21

[ Integration options ]
Email
Adjust email content for customers based on behaviouralsegments 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
5/26/09
22

[ Maximise profiling data ]
5/26/09
23

[ Targeting management ]
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
5/26/09
24

Define success
Conduct research
Define segments
Validate segments
Define content
Test content
Business rules
Start targeting
Communicate results
[ Keys to effective targeting ]
5/26/09
25

[ Strategy and execution ]
5/26/09
26
Content
Process
Ongoing Targeting Success
Resource training
Content production
Platform maintenance
Campaign integration
Ongoing reporting
Agency processes
Success definition
Consumer research
Segment definition
Segment validation
Content testing
Business rules
Segments
Resources

[ Prospect targeting parameters ]
5/26/09
27

[ Customer targeting journey ]
5/26/09
28
Retention
Customer Profile
Customer receives email with customized content, upgrades online
Customer visits website, sees messaging emphasising upgrade benefits
Customer frequently visits specific product pages
Customer reads news online, sees banner for special customer offer
Customer visits online help site instead of calling call center
Prospect
Customer
Receives welcome email with product FAQ
Prospect receives reminder email, finishes online purchase
Prospects clicks on paid search, starts checkout using voucher but leaves
Prospect visits retail store for demonstration, receives personalized voucher
Referral from affiliate site, prospect sees customized offers on site
Prospect sees print ad, executes unique search, sees customized offers on site
Prospect sees banner ad, no response
Consideration
Visitor Behaviour

[ Add customer parameters ]
5/26/09
29
CRM Profile
Site Behaviour
one-off collection of demographical data age, gender, address, etc
customer lifecycle metrics and key datesprofitability, expiration, etc
predictive models based on data miningpropensity to buy, churn, etc
historical data from previous transactionsaverage order value, points, etc
tracking of purchase funnel stagebrowsing, checkout, etc
tracking of content preferencesproducts, brands, features, etc
tracking of external campaign responses
search terms, referrers, etc
tracking of internal promotion responses
emails, internal search, etc
+
Updated OCCASIONALLY
Updated continuously

[ Multiply identification points ]
5/26/09
30
Campaign response
Online purchase
Confirmation email
Repeat purchase
Email newsletter
Website login

[ Email identification points ]
5/26/09
© Datalicious Pty Ltd & Omniture Inc
31
Fulfilment
Phone Conversion
Website research
Online ReceiptConfirmation
@
Advertising Campaign
Retail Conversion
Fulfilment
Website research
@
Website research
Online Conversion
Fulfilment
Online Order Confirmation
@
Cookie ID

AvinashKaushik: “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 ]
5/26/09
32

[ About us ]
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
5/26/09
33

[ Datalicious services ]
5/26/09
Data
Insights
Action
Web Analytics Solutions
Keyword Research
Search Lead Media
Marketing System Integration
Campaign Reporting
Campaign Optimisation
Cross Channel Media Tracking
Segmentation/Data Mining
Internal Search Optimisation
Online Surveys/Panels
Targeting/Merchandizing
Quantitative Research
Omniture Specialists
Market/Consumer Trends
A/B, Multivariate Testing
Google Analytics Specialists
Competitor Analysis
Staff Training/Workshops
34

[ Datalicious clients ]
5/26/09
35

5/26/09
insights@datalicious.com
36