macquarie adma campaign measurement
DESCRIPTION
The presentation discusses the concepts, principles and significance of data driven marketing.TRANSCRIPT
> Campaign Measurement < Digital Campaign Measurement Macquarie ADMA Workshop
> Short but sharp history
§ Datalicious was founded late 2007 § Strong Omniture web analyBcs history § Now 360 data agency with specialist team § CombinaBon of analysts and developers § Carefully selected best of breed partners § Evangelizing smart data driven markeBng § Making data accessible and acBonable § Driving industry best pracBce (ADMA)
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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 Repor?ng Data mining and modelling Customised dashboards Media aKribu?on models Market and compe?tor trends Social media monitoring Online surveys and polls Customer profiling
Ac?on Applica?ons Data usage and applica?on Marke?ng automa?on Alterian, Trac?on, 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
Stan
dardised
Metric
s Be
nchm
arking and
tren
ding
Standardised Metrics
Benchmarking and trending
> Metrics framework
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
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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 (AcBon)
+Buzz (SaBsfacBon)
> 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%
People reached
People engaged
People converted
People delighted
> Addi?onal funnel breakdowns
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40% 10% 1%
New prospects vs. exisBng customers
Brand vs. direct response campaign
New vs. returning visitors
AU/NZ vs. rest of world
Exercise: Funnel breakdowns
> Exercise: Funnel breakdowns
§ List potenBally insighYul funnel breakdowns – Brand vs. direct response campaign – New prospects vs. exisBng customers – Baseline vs. incremental conversions – CompeBBve acBvity, i.e. none, a lot, etc – Segments, i.e. age, locaBon, influence, etc – Channels, i.e. search, display, social, etc – Campaigns, i.e. this/last week, month, year, etc – Products and brands, i.e. iphone, htc, etc – Offers, i.e. free minutes, free handset, etc
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People reached
People engaged
People converted
People delighted
> Mul?ple metrics data sources
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QuanBtaBve and qualitaBve research data
Website, call center and retail data
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
Calendar events to add context
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> Conversion funnel 1.0
February 2011
Conversion funnel Product page, add to shopping cart, view shopping cart, cart checkout, payment details, shipping informaBon, order confirmaBon, etc
Conversion event
Campaign responses
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> Conversion funnel 2.0
February 2011
Campaign responses (inbound spokes) Offline campaigns, banner ads, email markeBng, referrals, organic search, paid search, internal promoBons, etc
Landing page (hub)
Success events (outbound spokes) Bounce rate, add to cart, cart checkout, confirmed order, call back request, registraBon, 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
Exercise: Sta?s?cal significance
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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” February 2011 © ADMA & Datalicious Pty Ltd 22
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” February 2011 © ADMA & Datalicious Pty Ltd 23
> 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
Exercise: Metrics framework
Level Reach Engagement Conversion +Buzz
Level 1 People
Level 2 Strategic
Level 3 Tac?cal
> Exercise: Metrics framework
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Level Reach Engagement Conversion +Buzz
Level 1 People
People reached
People engaged
People converted
People delighted
Level 2 Strategic
Search impressions, UBs, etc
? ? ?
Level 3 Tac?cal
Click-‐through or interac?on
rate, etc ? ? ?
> Exercise: Metrics framework
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> Media aKribu?on
101011010010010010101111010010010101010100001011111001010101010100101011001100010100101001101101001101001010100111001010010010101001001010010100100101001111101010100101001001001010
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Direct mail, email, etc
Facebook TwiKer, etc
> Complex campaign flows
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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
> 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
$
Exercise: Duplica?on impact
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> Exercise: Duplica?on impact § Double-‐counBng 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 reporBng but once de-‐duplicated they each only contributed 50% of conversions
– What are the iniBal CPA values and what is the true CPA? § SoluBon: $50 iniBal CPA and $100 true CPA
– $5,000 / 100 = $50 iniBal CPA and $5,000 / 50 = $100 true CPA (which represents a 100% increase)
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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
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> Indirect display impact
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> Success aKribu?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 aKribu?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
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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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February 2011 © ADMA & Datalicious Pty Ltd 44 Offline response tracking and improved experience
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> PURLs boos?ng DM response rates
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Text
> Jet Interac?ve phone call data
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> Poten?al calls to ac?on § Unique click-‐through URLs § Unique vanity domains or URLs § Unique phone numbers § Unique search terms § Unique email addresses § Unique personal URLs (PURLs) § Unique SMS numbers, QR codes § Unique promoBonal codes, vouchers § Geographic locaBon (Facebook, FourSquare) § Plus regression analysis of cause and effect
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> Cross-‐channel impact
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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
Closer
SEM Generic
Banner View
TV Ad
> Full path to purchase
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Influencer Influencer $
Banner Click Online
SEO Generic
Affiliate Click Offline
SEO Branded
Direct Visit
Email Update Abandon
Direct Visit
Social Media
SEO Branded
Introducer
> Adobe stacking/par?cipa?on
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Adobe can only stack direct paid and organic responses that end up on your website proper?es, mere banner impressions are missing from the stack and cannot be included via Genesis aser the fact.
> Combining data sources
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> Single source of truth repor?ng
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Insights Repor?ng
> Understanding channel mix
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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 AdverBsing 7%
Affiliate MarkeBng 9%
Referrals 5%
Email MarkeBng 7%
De-‐duped Campaign Report
} Channel % of Influence
Word of Mouth 32%
Blogging & Social Media 24%
Newspaper AdverBsing 9%
Display AdverBsing 14%
Email MarkeBng 7%
Retail PromoBons 14%
Greatest Influencer on Branded Search / STS
Conversions anributed to search terms that contain brand keywords and direct website visits are most likely not the originaBng 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%
> Success aKribu?on models
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Influencer Influencer $
25% Even AKrib.
Exclusion AKrib.
PaKern AKrib.
25% 25%
Introducer
33% 33% 33% 0%
30% 20% 20% 30%
Closer
Channel 1
Channel 1
Channel 1
> Path across different segments
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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
Exercise: AKribu?on model
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Closer
25%
> Exercise: AKribu?on models
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Influencer Influencer $
25% Even AKrib.
Exclusion AKrib.
Custom AKrib.
25% 25%
Introducer
33% 33% 33% 0%
? ? ? ?
> Common aKribu?on models
§ Allocate more conversion credits to more recent touch points for brands with a strong baseline to sBmulate repeat purchases
§ Allocate more conversion credits to more recent touch points for brands with a direct response focus
§ Allocate more conversion credits to iniBaBng touch points for new and expensive brands and products to insert them into the mindset
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