ANZ Marketing Analytics
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> Marke(ng Analy(cs < Using data to boost return on
marke1ng investment
> Short but sharp history § Datalicious was founded in late 2007 § Strong Omniture web analy1cs history § 1 of 4 preferred Omniture partners globally § Now 360 data agency with specialist team § Combina1on of analysts and developers § Carefully selected best of breed partners § Driving industry best prac1ce (ADMA) § Turning data into ac1onable insights § Execu1ng smart data driven campaigns December 2011 © Datalicious Pty Ltd 2
> Smart data driven marke(ng
December 2011 © Datalicious Pty Ltd 3
Media A<ribu(on & Modeling
Op(mise channel mix, predict sales
Tes(ng & Op(misa(on Remove barriers, drive sales
Boos(ng ROMI
Targeted Direct Marke(ng Increase relevance, reduce churn
“Using data to widen the funnel”
> Media a<ribu(on
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
December 2011 © Datalicious Pty Ltd 4
> The ideal media dashboard
December 2011 © Datalicious Pty Ltd 5
Channel Investment ROMI Return
Brand equity Baseline ($100) n/a $40
Offline TV, print, outdoor, etc $7 330% $30
Direct Direct mail, email, etc $1 400% $5
Online Search, display, social, etc
$2 1150% $25
> Duplica(on across channels
December 2011 © Datalicious Pty Ltd 6
Banner Ads
Email Blast
Paid Search
Organic Search
$ Bid Mgmt
Ad Server
Email PlaNorm
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 PlaNorm
Google Analy(cs
$
$
$
$
Expira(on
Banner Ad View
Central Analy(cs PlaNorm
$
$
$
> De-‐duplica(on across channels
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Banner Ads
Email Blast
Paid Search
Organic Search
$
Direct mail, email, etc
Facebook Twi<er, etc
> Campaign flows are complex
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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
= Paid media
= Viral elements
Call center, retail stores, etc
= Sales channels
Display ads, affiliates, etc
TV/Print/DM audience
Search audience
Banner audience
> Media channels feed each other
December 2011 © Datalicious Pty Ltd 10
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
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> Indirect display impact
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> Success a<ribu(on models
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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
> 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
Paid search
Display ad views
TV/print ad views
> Full purchase path tracking
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Influencer Influencer $
Display ad clicks
Online sales
Affiliate clicks
Social buzz
Offline sales
Organic search
Website events
Direct mail, emails
Life(me profit
Social referrals
Retail store visits
Direct site visits
Introducer
> Search call to ac(on for offline
December 2011 © Datalicious Pty Ltd 18
VickyCarroll.myspaday.com > redirect to > myspaday.com?
CampaignID=DM:123& Demographics=F|35& CustomerSegment=A1& CustomerValue=High& CustomerSince=2001& ProductHistory=P1|P2& NextBestOffer=P3& ChurnRisk=Low [...]
> Personalised URLs for direct mail
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Confirma(on email, 1st login
> Offline sales driven by online
December 2011 © Datalicious Pty Ltd 22
Website research
Phone order
Retail order
Online order
Cookie
Adver(sing campaign
Credit check, fulfilment
Online order confirma(on
Virtual order confirma(on
> Event ROI extrapola(on
December 2011 © Datalicious Pty Ltd 23
Product view
Applica(on start
Offline conversion
$10 $100
$100
$100
$30 $60
Campaign
$10 $30
$10
Applica(on complete
@ @
Campaign
Campaign
Campaign
> Single source of truth repor(ng
December 2011 © Datalicious Pty Ltd 24
Insights Repor(ng
> Where to collect the data
December 2011 © Datalicious Pty Ltd 25
Referral visits Social media visits Organic search visits Paid search visits Email visits, etc
Web Analy(cs Banner impressions
Banner clicks +
Paid search clicks
Ad Server
Lacking ad impressions Less granular & complex
Lacking organic visits More granular & complex
> Raw a<ribu(on data
Web Analy(cs data sample (AD IMPRESSION >) AFFILIATE > SEARCH > $$$ SEARCH > SOCIAL > EMAIL > DIRECT > $$$
Ad Server data sample 01/01/2011 12:00 AD IMPRESSION 01/01/2011 12:05 PAID SEARCH 07/01/2011 17:00 EMAIL 08/01/2011 15:00 $$$
December 2011 © Datalicious Pty Ltd 26
> Purchase path for each cookie
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Mobile Home Work
Tablet Media Etc
> Understanding channel mix
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> Website entry survey
December 2011 © Datalicious Pty Ltd 30
Channel % of Conversions
Straight to Site 27%
SEO Branded 15%
SEM Branded 9%
SEO Generic 7%
SEM Generic 14%
Display Adver1sing 7%
Affiliate Marke1ng 9%
Referrals 5%
Email Marke1ng 7%
De-‐duped Campaign Report
} Channel % of Influence
Word of Mouth 32%
Blogging & Social Media 24%
Newspaper Adver1sing 9%
Display Adver1sing 14%
Email Marke1ng 7%
Retail Promo1ons 14%
Greatest Influencer on Branded Search / STS
Conversions aoributed to search terms that contain brand keywords and direct website visits are most likely not the origina1ng channel that generated the awareness and as such conversion credits should be re-‐allocated.
> Adjus(ng for offline impact
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+15 +5 +10 -‐15 -‐5 -‐10
Closer
25%
> Custom a<ribu(on models
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Influencer Influencer $
25% Even A<rib.
Exclusion A<rib.
Custom A<rib.
25% 25%
Introducer
33% 33% 33% 0%
? ? ? ?
Closer
Channel 1
Channel 1
Channel 1
> Path across different segments
December 2011 © Datalicious Pty Ltd 33
Influencer Influencer $
Channel 2
Channel 2 Channel 3
Channel 2 Channel 3 Product 4
Channel 3
Channel 4
Channel 4
Introducer
Product A vs. B
New prospects
Exis(ng customers
> Experience op(misa(on
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
December 2011 © Datalicious Pty Ltd 34
Capture internet traffic Capture 50-‐100% of fair market share of traffic
Increase consumer engagement Exceed 50% of best compe1tor’s engagement rate
Capture qualified leads and sell Convert 10-‐15% to leads and of that 20% to sales
Building consumer loyalty Build 60% loyalty rate and 40% sales conversion
Increase online revenue Earn 10-‐20% incremental revenue online
> Increase revenue by 10-‐20%
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> New consumer decision journey
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The consumer decision process is changing from linear to circular.
> New consumer decision journey
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The consumer decision process is changing from linear to circular.
Change increases the importance of experience during research phase.
Online research
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Customised landing pages
> Seamless research experience
December 2011 © Datalicious Pty Ltd 42
TV, print, direct mail, etc
Organic, paid search
Display ads
Display ad re-‐targe(ng
Applica(on process
Fall-‐out email follow-‐up
ANZ.com re-‐targe(ng
Ad Server / SuperTag
Ad Server / SuperTag
AdWords
Test&Target / SuperTag
Test&Target / SuperTag
> Network wide re-‐targe(ng
December 2011 © Datalicious Pty Ltd 43
Frequent Flyer campaign
Card customer
Card prospect
Loan prospect
Access Advantage campaign Home Loans campaign
Access customer
Access prospect
Loan prospect
Loan customer
Loan prospect
Access prospect
Group wide campaign with approximate impression targets by product rather than hard budget limita(ons
> Network wide re-‐targe(ng
December 2011 © Datalicious Pty Ltd 44
Card customer
Card prospect
Loan prospect
Access customer
Access prospect
Loan prospect
Loan customer
Loan prospect
Access prospect
Targe(ng before tes(ng
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Purchase Cycle
Segmenta(on based on: Search keywords, display ad clicks and website behaviour Data
Points Access Advantage
Frequent Flyers Etc
Research, considera(on
Acquisi(on message #A1
Acquisi(on message #A3
Acquisi(on message #A5
Ad clicks, prod views
Conversion intent
Acquisi(on message #A2
Acquisi(on message #A4
Acquisi(on message #A6
Applica(on starts
Reten(on, cross-‐sell
Reten(on message #R1
Reten(on message #R2
Reten(on message #R3
Email clicks, logins, etc
> Developing a targe(ng matrix
December 2011 © Datalicious Pty Ltd 46
Campaign response data
> Combining data sources
December 2011 © Datalicious Pty Ltd 47
Customer profile data
+ The whole is greater than the sum of its parts
Website behavioural data
> Transac(ons plus behaviours
December 2011 © Datalicious Pty Ltd 48
+ one-‐off collec1on of demographical data age, gender, address, etc customer lifecycle metrics and key dates profitability, expira(on, etc predic1ve models based on data mining
propensity to buy, churn, etc historical data from previous transac1ons
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 promo1on responses
emails, internal search, etc
Site Behaviour
Updated Con(nuously
> 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 iden1fica1on through Cookies
December 2011 49 © Datalicious Pty Ltd
Test Segment Content Success Difficulty Poten(al
Test #1A New prospects
Acquisi(on offer A
Clicks, orders, etc
Low $50k Test #1B New
prospects Acquisi(on offer B
Clicks, orders, etc
Test #2A Exis(ng customers
Up-‐sell offer A
Clicks, orders, etc
High $75k Test #2B Exis(ng
customers Up-‐sell offer B
Clicks, orders, etc
> Developing a tes(ng matrix
December 2011 © Datalicious Pty Ltd 50
> The holy trinity of tes(ng 1. The headline – Have a headline! – Headline should be concrete – Headline should be first thing visitors look at
2. Call to ac(on – Don’t have too many calls to ac1on – Have an ac1onable call to ac1on – Have a big, prominent, visible call to ac1on
3. Social proof – Logos, number of users, tes1monials, case studies, media coverage, etc
December 2011 © Datalicious Pty Ltd 51
> Best prac(ce tes(ng roadmap § Phase #1: A/B test
– Test the same landing page content in completely different layouts
§ Phase #2: MV test – Then test different content element combina1ons within the winning layout
§ Phase #3: Challenge – Con1nue tes1ng and introducing layout and content challengers
December 2011 © Datalicious Pty Ltd 52
Element #1: Prominent headline
Element #2: Call to ac1on
Suppor1ng content
Element #3: Social proof / trust
Terms and condi1ons
> Use unique phone numbers
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2 out of 3 callers hang up as they cannot get their informa1on fast enough. Unique phone numbers can help improve call experience.
December 2011 © Datalicious Pty Ltd 54
Contact me [email protected]
Learn more
blog.datalicious.com
Follow me twi<er.com/datalicious
December 2011 © Datalicious Pty Ltd 55
Data > Insights > Ac(on
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