Datalicious is a 360 data agency founded in 2007 that specializes in web analytics and digital marketing. It combines analysts and developers to make data accessible and actionable in order to drive smart, data-driven marketing. Datalicious works with clients across industries to optimize campaigns through metrics like media attribution, testing, and targeting to increase metrics like awareness, interest, desire, action, and satisfaction.

1. [ Analyse to optimise ]
Campaign tracking and analytics
digital certificate guest lecture

2. [ Company history ]
 Datalicious was founded in late 2007
 Strong Omniture web analytics history
 1 of 4 Omniture Service Partners globally
 Now 360 data agency with specialist team
 Combination of analysts and developers
 Making data accessible and actionable
 Evangelizing smart data driven marketing
 Driving industry best practice (ADMA)
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3. [ Smart data driven marketing ]
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Media Attribution
Optimise channel mix
Testing
Improve usability
$$$
Targeting
Increase relevance

4. [ Clients across all industries ]
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5. Awareness Interest Desire Action Satisfaction
[ AIDA and AIDAS formulas ]
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Social media
New media
Old media

6. Reach
(Awareness)
Engagement
(Interest & Desire)
Conversion
(Action)
+Buzz
(Satisfaction)
[ Simplified AIDAS funnel ]
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7. People
Reached
People
Engaged
People
Converted
People
Delighted
[ Marketing is about people ]
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40% 10% 1%
Quantitative and qualitative research data
Website, call center and retail data
Social media data
Media and search data
Social media

8. [ Google data in Australia ]
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Source: http://www.hitwise.com/au/datacentre

9. [ Search and brand strength ]
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10. [ Search and the product lifecycle ]
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Nokia N-Series
Apple iPhone

11. [ Search and media planning ]
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12. [ Search driving offline creative ]
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13. [ Facebook insights ]
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Using Facebook Like
buttons is a free and
powerful way to gain
additional insights
into consumer
preferences and
enabling social
sharing of content
as well as possibly
influence organic
search rankings in
the near future.

14. [ Conversion funnel 1.0 ]
October 2010
Conversion funnel
Product page, add to shopping cart, view shopping cart,
cart checkout, payment details, shipping information,
order confirmation, etc
Conversion event
Campaign responses
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15. [ Conversion funnel 2.0 ]
October 2010
Campaign responses (inbound spokes)
Offline campaigns, banner ads, email marketing,
referrals, organic search, paid search,
internal promotions, etc
Landing page(hub)
Success events (outbound spokes)
Bounce rate, add to cart, cart checkout, confirmed order,
call back request, registration, product comparison,
product review, forward to friend, etc
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16. [ Additional success metrics ]
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Click
Through
Add To
Cart
Click
Through
Page
Bounce
Click
Through $
Click
Through
Call back
request
Store
Search ? $
$
$
Cart
Checkout
Page
Views
?
Product
Views

17. How many survey responses do you need
if you have 10,000 customers?
How many email opens do you need to test 2 subject lines
if your subscriber base is 50,000?
How many orders do you need to test 6 banner executions
if you serve 1,000,000 banners
Google “nss sample size calculator”

18. How many survey responses do you need
if you have 10,000 customers?
369 for each question or 369 complete responses
How many email opens do you need to test 2 subject lines
if your subscriber base is 50,000? And email sends?
381 per subject line or 381 x 2 = 762 email opens
How many orders do you need to test 6 banner executions
if you serve 1,000,000 banners?
383 sales per banner execution or 383 x 6 = 2,298 sales
Google “nss sample size calculator”

19. [ De-duplication across channels ]
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Banner
Ads
Email
Blast
Paid
Search
Organic
Search
$
Bid
Mgmt
Ad
Server
Email
Platform
Google
Analytics
$
$
$
Central
Analytics
Platform
$
$
$

20. [ Exercise: Duplication impact ]
 Double-counting of conversions across channels can have
a significant impact on key metrics, especially CPA
 Example: Display ads and paid search
– Total media budget of $10,000 of which 50% is spend on paid
search and 50% on display ads
– Total of 100 conversions across both channels with a channel
overlap of 50%, i.e. both channels claim 100% of conversions
based on their own reporting but once de-duplicated they
each only contributed 50% of conversions
– What are the initial CPA values and what is the true CPA?
 Solution: $50 initial CPA and $100 true CPA
– $5,000 / 100 = $50 initial CPA and $5,000 / 50 = $100 true
CPA (which represents a 100% increase)
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21. [ Success attribution 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
partial credit
Paid
Search
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22. [ First and last click attribution ]
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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
Paid/Organic Search
Emails/Shopping Engines

23. Closer
SEM
Generic
Banner
View
TV
Ad
[ Full path to purchase ]
Influencer Influencer
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$
Banner
Click $
SEO
Generic
Affiliate
Click $
SEO
Branded
Direct
Visit
Email
Update
Abandon
Direct
Visit
Social
Media
SEO
Branded
Introducer

24. [ Understanding channel overlap ]
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25. [ Website entry survey ]
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Channel % of Conversions
Straight to Site 27%
SEO Branded 15%
SEM Branded 9%
SEO Generic 7%
SEM Generic 14%
Display Advertising 7%
Affiliate Marketing 9%
Referrals 5%
Email Marketing 7%
De-duped Campaign Report
}
Channel % of Influence
Word of Mouth 32%
Blogging & Social Media 24%
Newspaper Advertising 9%
Display Advertising 14%
Email Marketing 7%
Retail Promotions 14%
Greatest Influencer on Branded Search / STS
Conversions attributed to search terms
that contain brand keywords and direct
website visits are most likely not the
originating channel that generated the
awareness and as such conversion
credits should be re-allocated.

26. The study examined
data from two of
the UK’s busiest
ecommerce
websites, ASDA
and William Hill.
Given that more
than half of all page
impressions on these
sites are from logged-in
users, they provided a robust
sample to compare IP-based and cookie-based analysis against.
The results were staggering, for example an IP-based approach
overestimated visitors by up to 7.6 times whilst a cookie-based
approach overestimated visitors by up to 2.3 times.
[ Unique visitor overestimation ]
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Source: White Paper, RedEye, 2007

27. [ Importance of calendar events ]
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Traffic spikes or other data anomalies without context are
very hard to interpret and can render data useless

28. © Datalicious Pty Ltd
[ Useful analytics tools ]
 http://labs.google.com/sets
 http://www.google.com/trends
 http://www.google.com/insights/search
 http://www.google.com/sktool
 http://bit.ly/googlekeywordtoolexternal
 http://www.google.com/webmasters
 http://www.google.com/adplanner
 http://www.google.com/videotargeting
 http://www.keywordspy.com
 http://www.compete.com
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29. © Datalicious Pty Ltd
[ Useful analytics tools ]
 http://bit.ly/hitwisedatacenter
 http://www.socialmention.com
 http://twittersentiment.appspot.com
 http://bit.ly/twitterstreamgraphs
 http://twitrratr.com
 http://bit.ly/listoftools1
 http://bit.ly/listoftools2
 http://manyeyes.alphaworks.ibm.com
 http://www.wordle.net
 http://www.tagxedo.com
October 2010 29

30. ADMA short course
“Analyse to optimise”
In Melbourne & Sydney
October/November
By Datalicious

31. Contact us
cbartens@datalicious.com
Follow us
twitter.com/datalicious
Learn more
blog.datalicious.com