analyze to optimize - adma digital certificate
DESCRIPTION
The presentation discusses about campaign tracking and analytics.TRANSCRIPT
[ Analyse to op-mise ] Campaign tracking and analy0cs digital cer0ficate guest lecture
[ Company history ]
§ Datalicious was founded in late 2007 § Strong Omniture web analy0cs history § 1 of 4 Omniture Service Partners globally § Now 360 data agency with specialist team § Combina0on of analysts and developers § Making data accessible and ac0onable § Evangelizing smart data driven marke0ng § Driving industry best prac0ce (ADMA)
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[ Smart data driven marke-ng ]
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Media A:ribu-on
Op-mise channel mix
Tes-ng Improve usability
$$$
Targe-ng Increase relevance
[ Clients across all industries ]
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Awareness Interest Desire Ac-on Sa-sfac-on
[ AIDA and AIDAS formulas ]
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Social media
New media
Old media
Reach (Awareness)
Engagement (Interest & Desire)
Conversion (Ac0on)
+Buzz (Sa0sfac0on)
[ Simplified AIDAS funnel ]
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People Reached
People Engaged
People Converted
People Delighted
[ Marke-ng is about people ]
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40% 10% 1%
Quan0ta0ve and qualita0ve research data
Website, call center and retail data
Social media data
Media and search data
Social media
[ Google data in Australia ]
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Source: hXp://www.hitwise.com/au/datacentre
[ Search and brand strength ]
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[ Search and the product lifecycle ]
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Nokia N-‐Series
Apple iPhone
[ Search and media planning ]
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[ Search driving offline crea-ve ]
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[ Facebook insights ]
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Using Facebook Like buXons is a free and powerful way to gain addi0onal insights into consumer preferences and enabling social sharing of content as well as possibly influence organic search rankings in the near future.
[ Conversion funnel 1.0 ]
October 2010
Conversion funnel Product page, add to shopping cart, view shopping cart, cart checkout, payment details, shipping informa0on, order confirma0on, etc
Conversion event
Campaign responses
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[ Conversion funnel 2.0 ]
October 2010
Campaign responses (inbound spokes) Offline campaigns, banner ads, email marke0ng, referrals, organic search, paid search, internal promo0ons, etc
Landing page (hub)
Success events (outbound spokes) Bounce rate, add to cart, cart checkout, confirmed order, call back request, registra0on, product comparison, product review, forward to friend, etc
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[ Addi-onal 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
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 execu-ons if you serve 1,000,000 banners
Google “nss sample size calculator”
How many survey responses do you need if you have 10,000 customers?
369 for each ques-on 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 execu-ons if you serve 1,000,000 banners?
383 sales per banner execu-on or 383 x 6 = 2,298 sales
Google “nss sample size calculator”
[ 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
$
$
$
Central Analy-cs Plagorm
$
$
$
[ Exercise: Duplica-on impact ] § Double-‐coun0ng 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 repor0ng but once de-‐duplicated they each only contributed 50% of conversions
– What are the ini0al CPA values and what is the true CPA? § Solu0on: $50 ini0al CPA and $100 true CPA
– $5,000 / 100 = $50 ini0al CPA and $5,000 / 50 = $100 true CPA (which represents a 100% increase)
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[ Success a:ribu-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 $100
All channels get par-al credit
Paid Search
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[ First and last click a:ribu-on ]
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Chart shows percentage of channel touch points that lead to a conversion.
Neither first nor last-‐click measurement would provide true picture
Paid/Organic Search
Emails/Shopping Engines
Closer
SEM Generic
Banner View
TV Ad
[ Full path to purchase ]
Influencer Influencer
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$
Banner Click $
SEO Generic
Affiliate Click $
SEO Branded
Direct Visit
Email Update Abandon
Direct Visit
Social Media
SEO Branded
Introducer
[ Understanding channel overlap ]
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[ 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 Adver0sing 7%
Affiliate Marke0ng 9%
Referrals 5%
Email Marke0ng 7%
De-‐duped Campaign Report
} Channel % of Influence
Word of Mouth 32%
Blogging & Social Media 24%
Newspaper Adver0sing 9%
Display Adver0sing 14%
Email Marke0ng 7%
Retail Promo0ons 14%
Greatest Influencer on Branded Search / STS
Conversions aXributed to search terms that contain brand keywords and direct website visits are most likely not the origina0ng channel that generated the awareness and as such conversion credits should be re-‐allocated.
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 overes0mated visitors by up to 7.6 0mes whilst a cookie-‐based approach overes-mated visitors by up to 2.3 -mes.
[ Unique visitor overes-ma-on ]
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Source: White Paper, RedEye, 2007
[ 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
© Datalicious Pty Ltd
[ Useful analy-cs tools ] § hXp://labs.google.com/sets § hXp://www.google.com/trends § hXp://www.google.com/insights/search § hXp://www.google.com/sktool § hXp://bit.ly/googlekeywordtoolexternal § hXp://www.google.com/webmasters § hXp://www.google.com/adplanner § hXp://www.google.com/videotarge0ng § hXp://www.keywordspy.com § hXp://www.compete.com October 2010 28
© Datalicious Pty Ltd
[ Useful analy-cs tools ] § hXp://bit.ly/hitwisedatacenter § hXp://www.socialmen0on.com § hXp://twiXersen0ment.appspot.com § hXp://bit.ly/twiXerstreamgraphs § hXp://twitrratr.com § hXp://bit.ly/listooools1 § hXp://bit.ly/listooools2 § hXp://manyeyes.alphaworks.ibm.com § hXp://www.wordle.net § hXp://www.tagxedo.com October 2010 29
ADMA short course “Analyse to op-mise”
In Melbourne & Sydney October/November
By Datalicious
