Date post: | 21-Oct-2014 |
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> Digital Measurement < More than just coun.ng hits!
> Short but sharp history
§ Datalicious was founded late 2007 § Strong Omniture web analy.cs history § Now 360 data agency with specialist team § Combina.on of analysts and developers § Carefully selected best of breed partners § Driving industry best prac.ce (ADMA) § Turning data into ac.onable insights § Execu.ng smart data driven campaigns
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> Clients across all industries
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> Wide range of data services
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Data Pla>orms Data collec?on and processing Web analy?cs solu?ons Omniture, Google Analy?cs, etc Tag-‐less online data capture End-‐to-‐end data pla>orms IVR and call center repor?ng Single customer view
Insights Analy?cs Data mining and modelling Customised dashboards Tableau, Spo>ire, SPSS, etc Media aKribu?on models Market and compe?tor trends Social media monitoring Customer profiling
Ac?on Campaigns Data usage and applica?on Marke?ng automa?on Alterian, SiteCore, Inxmail, etc Targe?ng and merchandising Internal search op?misa?on CRM strategy and execu?on Tes?ng programs
> Smart data driven marke?ng
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Media AKribu?on
Op?mise channel mix
Tes?ng Improve usability
$$$
Targe?ng Increase relevance
Metric
s Framew
ork
Benchm
arking and
tren
ding
Metrics Fram
ework
Benchmarking and trending
> Digital metrics
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> Digital data is plen?ful and cheap
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Source: Omniture Summit, MaS Belkin, 2007
HITS How Idiots Track Success
> Basic website metrics § Page view/impression: The number of .mes a page (an
analyst-‐definable unit of content) was viewed. § Visit/session: A visit is an interac.on, by an individual,
with a website consis.ng of one or more requests for an analyst-‐definable unit of content (i.e. “page view”). If an individual has not taken another ac.on (typically addi.onal page views) on the site within a specified .me period, the visit session will terminate.
§ Unique visitor/browser: The number of inferred individual people (filtered for spiders and robots), within a designated repor.ng .meframe, with ac.vity consis.ng of one or more visits to a site. Each individual is counted only once in the unique visitor measure for the repor.ng period.
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Source: Web Analy.cs Defini.ons, Web Analy.cs Associa.on, 2007
> Cookie based tracking process
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Source: Google Analy.cs, Jus.n Cutroni, 2007
What if: Someone deletes their cookies? Or uses a device that does not support JavaScript? Or uses two computers (work vs. home)? Or two people use the same computer?
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 overes.mated visitors by up to 7.6 .mes 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
> Maximise iden?fica?on points
20%
40%
60%
80%
100%
120%
140%
160%
0 4 8 12 16 20 24 28 32 36 40 44 48
Weeks
−−− Probability of iden.fica.on through Cookies
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> Maximise iden?fica?on points
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Mobile Home Work
Online Phone Branch
> Sample customer level data
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> Digital metric categories
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Source: Accuracy Whitepaper for web analy.cs, Brian Clihon, 2008
+Social
> Digital means global
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Source: Carat/Isobar, 2007
“The image is a model of the Internet, based on how many people view different sites and how these sites are related to each other. There are 3 colours on this model. Red, Green and Blue. Each represents users from US, Europe and Asia.
The picture illustrates how non linear the digital world is. It also shows how some sites have a strong centre of gravity for mass audiences; others have strong centres of gravity for niche audiences.
It is important to iden.fy where marke.ng is going to have most impact -‐ crea.ng powerful programs on niche sites, which gradually extend an influence on the larger communi.es; or (more expensive) marke.ng ac.vity on mass sites, that will then generate a frenzy of interest in smaller niche groups.”
Reach (Awareness)
Engagement (Interest & Desire)
Ac?on (Ac.on)
+Buzz (Sa.sfac.on)
Quan.ta.ve and qualita.ve research data
Website, call center and retail data
> Defining metrics frameworks
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Social media data
Media and search data
Social media
> 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
> Measuring reach
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TV/Print audience
Search audience
Banner audience
> Reach and channel overlap
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Users are segmented before 1st ad is even served
> Ad server exposure test
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Banner Impression $ TV/Print
Response Search
Response
Banner Impression $ Search
Response Direct
Response
Exposed group: 90% of users get branded message
Banner Impression $ Search
Response Direct
Response
Control group: 10% of users get non-‐branded message
> Indirect display impact
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> Indirect display impact
April 2011 © Datalicious Pty Ltd 23
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> Indirect display impact
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> New marketplace: Search
May 2011 © Datalicious Pty Ltd 26
> Google data in Australia
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Source: hSp://www.hitwise.com/au/resources/data-‐centre
> Search at all stages
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Source: Inside the Mind of the Searcher, Enquiro 2004
> Search and brand strength
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> Search and the product lifecycle
April 2011 © Datalicious Pty Ltd 31
Nokia N-‐Series
Apple iPhone
> Search and media planning
April 2011 © Datalicious Pty Ltd 32
> Search driving offline crea?ve
April 2011 © Datalicious Pty Ltd 33
> Hitwise Mosaic segment swing
australia.com vs. newzealand.com australia.com vs. bulafiji.com
May 2011 © Datalicious Pty Ltd 34 Source: Hitwise.com.au, 2008
> Hitwise Mosaic segment swing
australia.com vs. newzealand.com australia.com vs. newzealand.com
May 2011 © Datalicious Pty Ltd 35 Source: Hitwise.com.au, 2008
> Measuring engagement
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> Conversion funnel 1.0
May 2011
Conversion funnel Product page, add to shopping cart, view shopping cart, cart checkout, payment details, shipping informa.on, order confirma.on, etc
Conversion event
Campaign responses
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> Conversion funnel 2.0
May 2011
Campaign responses (inbound spokes) Offline campaigns, banner ads, email marke.ng, referrals, organic search, paid search, internal promo.ons, etc
Landing page (hub)
Success events (outbound spokes) Bounce rate, add to cart, cart checkout, confirmed order, call back request, registra.on, product comparison, product review, forward to friend, etc
© Datalicious Pty Ltd 38
> Addi?onal success metrics
May 2011 © Datalicious Pty Ltd 39
Click Through
Add To Cart
Click Through
Bounce Rate
Click Through $
Click Through
Call back requests
Store Searches > ... $
$
$ Cart Checkout
Pages Per Visit
?
Avg Cart Value
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> Book: Tuned In
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Source: hSp://www.pragma.cmarke.ng.com/tunedin
“70% or more of new products or new product decisions were made without
market data”
> Measuring ac?on
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> Key metrics by website type
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Source: Omniture Summit, MaS Belkin, 2007
> Duplica?on across channels
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Banner Ads
Email Blast
Paid Search
Organic Search
$ Bid Mgmt
Ad Server
Email Pla>orm
Google Analy?cs
$
$
$
> Cookie expira?on impact
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Banner Ad Click
Email Blast
Paid Search
Organic Search
Bid Mgmt
Ad Server
Email Pla>orm
Google Analy?cs
$
$
$
$
Expira?on
Banner Ad View
Central Analy?cs Pla>orm
$
$
$
> De-‐duplica?on across channels
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Banner Ads
Email Blast
Paid Search
Organic Search
$
> Poten?al duplica?on impact § Double-‐coun.ng 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 repor.ng but once de-‐duplicated they each only contributed 50% of conversions
– What are the ini.al CPA values and what is the true CPA? § Solu.on: $50 ini.al CPA and $100 true CPA
– $5,000 / 100 = $50 ini.al CPA and $5,000 / 50 = $100 true CPA (which represents a 100% increase)
April 2011 © Datalicious Pty Ltd 48
Direct mail, email, etc
Facebook TwiKer, etc
> Campaign flow and calls to ac?on
April 2011 © Datalicious Pty Ltd 49
POS kiosks, loyalty cards, etc
CRM program
Home pages, portals, etc
YouTube, blog, etc
Paid search
Organic search
Landing pages, offers, etc
PR, WOM, events, etc
TV, print, radio, etc
C2
C3
= Paid media
= Viral elements
Call center, retail stores, etc
= Coupons, surveys
Display ads, affiliates, etc
C1
> Success aKribu?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 aKribu?on
April 2011 © Datalicious Pty Ltd 51
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
April 2011 © Datalicious Pty Ltd 52
Influencer Influencer $
Banner Click Online
SEO Generic
Affiliate Click Offline
SEO Branded
Direct Visit
Email Update Abandon
Direct Visit
Social Media
SEO Branded
Introducer
> Search call to ac?on for offline
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> Research online buy in store
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Source: 2008 Digital Future Report, Surveying The Digital Future, Year Seven, USC Annenberg School
> Store locator searches
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> Offline sales driven by online
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Website research
Phone order
Retail order
Online order
Cookie
Adver?sing campaign
Credit check, fulfilment
Online order confirma?on
Virtual order confirma?on
Confirma?on email
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” April 2011 © Datalicious Pty Ltd 58
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” April 2011 © Datalicious Pty Ltd 59
> Addi?onal success metrics
April 2011 © Datalicious Pty Ltd 60
Click Through
Add To Cart
Click Through
Page Bounce
Click Through $
Click Through
Call back request
Store Search ? $
$
$ Cart Checkout
Page Views
?
Product Views
> Measuring buzz
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> Importance of social media Search
WOM, blogs, reviews, ra?ngs, communi?es, social networks, photo sharing, video sharing
May 2011 © Datalicious Pty Ltd
Promo?on
62
Company Consumer
Sen.ment
Reach Influence
> Measuring social media
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Sen?ment analysis: People vs. machine
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> Useful links
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> News and research
§ hSp://blog.datalicious.com § hSp://www.emarketer.com § hSp://www.marke.ngcharts.com § hSp://www.techcrunch.com § hSp://www.smartbrief.com/iab § hSp://www.trendwatching.com § hSp://www.springwise.com § hSp://www.useit.com/alertbox § hSp://weblogs.hitwise.com May 2011 © Datalicious Pty Ltd 67
© Datalicious Pty Ltd
> Trends and data
§ hSp://www.google.com/trends § hSp://www.google.com/sktool § hSp://www.google.com/webmasters § hSp://www.google.com/adplanner § hSp://www.google.com/videotarge.ng § hSp://www.hitwise.com.au/datacenter § hSp://www.compete.com/ § hSp://www.alexa.com/ § hSp://wiki.kenburbary.com/ May 2011 68
April 2011 © Datalicious Pty Ltd 69
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Data > Insights > Ac?on