adma multi-channel marketing

> Mul&-‐Channel Marke&ng < Effec%ve marke%ng measurement in a mul%-‐channel environment

> About Datalicious §  Datalicious was founded in November 2007 §  Official Adobe & Google Analy%cs partner §  360 data agency with team of data specialists §  Combina%on of analysts and developers §  Blue chip clients across all industry ver%cals §  Carefully selected best of breed partners §  Driving industry best prac%ce with ADMA §  Turning data into ac%onable insights §  Execu%ng smart data driven campaigns September 2012 © Datalicious Pty Ltd 2

> Smart data driven marke&ng

September 2012 © 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

Targe&ng & Merchandising Increase relevance, reduce churn

“Using data to widen the funnel”

> Mul&-‐channel measurement

§ Metrics standardisa%on § Media aRribu%on §  Channel integra%on


> Metrics standardisa&on

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August 2011 © Datalicious Pty Ltd 6

Awareness Interest Desire Ac&on Sa&sfac&on

> AIDA and AIDAS formulas


Social media

New media

Old media

Reach (Awareness)

Engagement (Interest & Desire)

Conversion (Ac%on)

+Buzz (Delight)

> Simplified AIDAS funnel


People reached

People engaged

People converted

People delighted

> Marke&ng is about people


40% 10% 1%

People reached

People engaged

People converted

People delighted


> Standardised roll-‐up metrics

Unique browsers, search impressions, TV circula&on, etc

Unique visitors, site engagements, video views, etc

Online sales, online leads, store locator searches, etc

Facebook comments, Tweets,

ra&ngs, support calls, etc

Response rate, Search response rate, TV response rate, etc

Conversion rate, engagement rate, checkout rate, etc

10% 40% 1%

Review rate, ra&ng rate, comment rate, NPS rate, etc

People reached

People engaged

People converted

People delighted

> Provide context with figures


40% 10% 1%

New prospects vs. exis%ng customers

Brand vs. direct response campaign

> Provide context with figures §  Brand vs. direct response campaign §  New prospects vs. exis%ng customers §  Compe%%ve ac%vity, i.e. none, a lot, etc §  Market share, i.e. small, medium, large, et §  Segments, i.e. age, loca%on, 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 §  Devices, i.e. home, office, mobile, tablet, etc September 2012 © Datalicious Pty Ltd 13

> Addi&onal success metrics


Click Through

Add To Cart

Click Through

Page Bounce

Click Through $

Click Through

Call back request

Store Search ? $

$

$ Cart Checkout

Page Views

?

Product Views

Use addi&onal metrics closer to the campaign origin

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” September 2012 © Datalicious Pty Ltd 15

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” September 2012 © Datalicious Pty Ltd 16

> Rela&ve or calculated metrics

§  Bounce rate §  Conversion rate §  Cost per acquisi%on §  Pages views per visit §  Product views per visit §  Cart abandonment rate §  Average order value


> Align metrics across channels §  Paid search response rate

= website visits / paid search impressions §  Organic search response rate

= website visits / organic search impressions §  Display response rate

= website visits / display ad impressions §  Email response rate

= website visits / emails sent §  Direct mail response rate

= (website visits + phone calls) / direct mail pieces sent §  TV response rate

= (website visits + phone calls) / (TV ad reach x frequency)


Level Reach Engagement Conversion +Buzz

Level 1, people

People reached

People engaged

People converted

People delighted

Level 2, strategic

Display impressions ? ? ?

Level 3, tac&cal

Interac&on rate, etc ? ? ?

Funnel breakdowns Exis&ng customers vs. new prospects, products, etc

> Develop a metrics framework


> Importance of calendar events


Traffic spikes or other data anomalies without context are very hard to interpret and can render data useless

> Poten&al calendar events

§  Press releases §  Sponsored events §  Campaign launches §  Campaign changes §  Crea%ve changes §  Price changes § Website changes §  Technical difficul%es


> Media a=ribu&on

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> Duplica&on across channels


Banner Ads

Email Blast

Paid Search

Organic Search

$ Bid Mgmt

Ad Server

Email Plajorm

Google Analy&cs

$

$

$

> Duplica&on across channels


Display impression

Paid search $

Ad Server

Bid mgmt.

Web analy&cs

Display click

Ad server cookie

Organic search

Analy&cs cookie

Analy&cs cookie

Analy&cs cookie

Bid mgmt. cookie

Ad server cookie

Central Analy&cs Plajorm

$

$

$

> De-‐duplica&on across channels


Banner Ads

Email Blast

Paid Search

Organic Search

$

Direct mail, email, etc

Facebook Twi=er, etc

> Campaign flows are complex


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

> 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

> First and last click a=ribu&on


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

> Indirect display impact


Closer

Paid search

Display ad views

TV/print responses

> Full purchase path tracking


Influencer Influencer $

Display ad clicks

Online leads

Affiliate clicks

Social referrals

Offline sales

Organic search

Social buzz

Retail visits

Life&me profit

Organic search

Emails, direct mail

Direct site visits

Introducer

> Purchase path example


> Where to track purchase path


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

> Purchase path data samples

Web Analy&cs data sample LAST AD IMPRESSION > SEARCH > $$$| PV $$$ AD IMPRESSION > AD IMPRESSION > SEARCH > $$$

Ad Server data sample 01/01/2012 11:45 AD IMP YAHOO HOME $33 01/01/2012 12:00 AD IMP SMH FINANCE $33 01/01/2012 12:05 SEARCH KEYWORD -‐ 07/01/2012 17:00 DIRECT $33 08/01/2012 15:00 $$$ $100


> Understanding channel mix



What promoted your visit today? q  Recent branch visit q  Saw an ad on television q  Saw an ad in the newspaper q  Recommenda%on from family/friends q  […] How likely are you to apply for a loan? q Within the next few weeks q Within the next few months q  I am a customer already q  […]

> Website entry survey


Channel % of Conversions

Straight to Site 27%

SEO Branded 15%

SEM Branded 9%

SEO Generic 7%

SEM Generic 14%

Display Adver%sing 7%

Affiliate Marke%ng 9%

Referrals 5%

Email Marke%ng 7%

De-‐duped Campaign Report

} Channel % of Influence

Word of Mouth 32%

Blogging & Social Media 24%

Newspaper Adver%sing 9%

Display Adver%sing 14%

Email Marke%ng 7%

Retail Promo%ons 14%

Greatest Influencer on Branded Search / STS

Conversions aRributed to search terms that contain brand keywords and direct website visits are most likely not the origina%ng channel that generated the awareness and as such conversion credits should be re-‐allocated.

> Adjus&ng for offline impact


+15 +5 +10 -‐15 -‐5 -‐10

0%

> Media a=ribu&on models


$100

0% Last click a=ribu&on

Even a=ribu&on

Weighted a=ribu&on

0% 100%

25% 25% 25% 25%

Display impression

Display impression

Display response

Search response

X% X% Y% Z%

> Media a=ribu&on example


COST PER CONVERSION

Last click aRribu%on

Even/weighted aRribu%on

> Media a=ribu&on example


COST PER CONVERSION

Last click aRribu%on

Even/weighted aRribu%on

? Email

? Direct mail

? Internal ads ?

Website content

? TV/Print

> Channel integra&on

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> Tracking offline responses online

§  Search calls to ac%on for TV, radio, print –  Unique search term only adver%sed in print so all responses from that term must have come from print

§  PURLs (personalised URLs) for direct mail –  Brand.com/customer-‐name redirects to new URL that includes tracking parameter iden%fying response as DM

§  Website entry survey for direct/branded visits –  Survey website visitors that have come to site directly or via branded search about their media habits, etc

§  Combine data sets into media aRribu%on model –  Combine raw data from online purchase path, website entry survey and offline sales with offline media placement data in tradi%onal (econometric) media aRribu%on model


> Search call to ac&on for offline


ChrisBartens.company.com > redirect to > company.com?

CampaignID=DM:123& Demographics=M|35& CustomerSegment=A1& CustomerValue=High& CustomerSince=2001& ProductHistory=A6& NextBestOffer=A7& ChurnRisk=Low [...]

> Personalised URLs for direct mail


> Econometric media modelling


Use of tradi%onal econometric modelling to measure the impact of communica%ons on sales for offline channels where it cannot be measured directly through smart calls to ac%on online (and thus cookie level purchase path data).

> Cross-‐channel impact


> Tracking offline sales online §  Email click-‐through

–  Include offline sales flag in 1st email click-‐through URL auer offline sale to track an ‘assisted offline sales’ conversion

§  First login auer purchase –  Similar to the above method, however offline sales flag happens via JavaScript parameter defined on 1st login

§  Unique phone numbers –  Assign unique website numbers to responses from specific channels, search terms or even individual visitors to match offline call center results back to online ac%vity

§  Website entry survey for purchase intent –  Survey website visitors to at least measure purchase intent in case actual offline sales cannot be tracked


Confirma&on email, 1st login

> Offline sales driven by online


Website research

Phone sales

Retail sales

Online sales

Cookie

Adver&sing campaign

Fulfilment, CRM, etc

Online sales confirma&on

Virtual sales confirma&on

hRp://www.company.com/email-‐landing-‐page.html?

CampaignID=DM:123& CustomerID=12345& Demographics=M|35& CustomerSegment=A1& CustomerValue=High& ProductHistory=A6& NextBestOffer=A7& ChurnRisk=Low [...]

> Email click-‐through iden&fica&on


> Login landing and exit pages


Customer data exposed in page or URL on login or logout

CustomerID=12345& Demographics=M|35& CustomerSegment=A1& CustomerValue=High& ProductHistory=A6& NextBestOffer=A7& ChurnRisk=Low [...]

> About Datalicious

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> Short but sharp history §  Datalicious was founded in November 2007 §  Official Adobe & Google Analy%cs partner §  360 data agency with team of data specialists §  Combina%on of analysts and developers §  Blue chip clients across all industry ver%cals §  Carefully selected best of breed partners §  Driving industry best prac%ce with ADMA §  Turning data into ac%onable insights §  Execu%ng smart data driven campaigns September 2012 © Datalicious Pty Ltd 55

> Smart data driven marke&ng


Media A=ribu&on & Modeling

Op&mise channel mix, predict sales

Tes&ng & Op&misa&on Remove barriers, drive sales

Boos&ng ROMI

Targe&ng & Merchandising Increase relevance, reduce churn

“Using data to widen the funnel”

> Wide range of data services


Data Plajorms Data collec&on and processing Adobe, Google Analy&cs, etc Web and mobile analy&cs Tag-‐less online data capture Retail and call center analy&cs Data warehouse solu&ons Single customer view

Insights Analy&cs Data mining and modelling Tableau, Splunk, SPSS, etc Customised dashboards Media a=ribu&on analysis Media mix modelling Social media monitoring Customer segmenta&on

Ac&on Campaigns Data usage and applica&on Alterian, SiteCore, Inxmail, etc Targe&ng and merchandising Marke&ng automa&on CRM strategy and execu&on Data driven websites Tes&ng programs

> Over 50 years of experience


Chris%an Bartens Founder & Director §  Bachelor of Business

Management with marke%ng focus

§  Web analy%cs and digital marke%ng work experience

§  Space2go, E-‐Lou, Tourism Australia

§  SuperTag founder, ADMA Analy%cs Chair, I-‐COM Board Member

LinkedIn profile

Elly Gillis General Manager §  Bachelor of

Communica%ons with print and digital focus

§  Digital marke%ng and project management work experience

§  M&C Saatchi, Mark, Holler, Tequila, IAG, OneDigital, Telstra

§  Australian gold medal in surf boat rowing

LinkedIn profile

Michael Savio Head of Insights §  Bachelor of Arts &

Science with applied mathema%cs focus

§  CRM and marke%ng research and analy%cs work experience

§  ANZ Bank, Australian Bureau of Sta%s%c, DBM Consultants

§  ADMA lecturer on marke%ng tes%ng

LinkedIn profile

Chaoming Li Head of Data §  Bachelor of

Technology with microelectronics focus

§  Souware and website development work experience

§  Standards Australia, DF Securi%es, Globiz, Etang

§  Developing his own CMS pla|orm

LinkedIn profile

> Best of breed partners


> Clients across all industries


> Great customer feedback “[…] Datalicious quickly earned our respect and confidence […] understand our business needs, deliver value, push our thinking […]. Likeable, transparent and trustworthy. I would be happy to recommend Datalicious to anyone.” Murray Howe, Execu%ve Manager, Suncorp Group "[…] Datalicious brought with them best prac>ce analy>cs to demonstrate the true value of our marke>ng dollars […] have become a criBcal business partner […] provided great insights which have driven key business decisions.” Trang Young, Senior Marke%ng Manager, E*Trade Australia “The Datalicious guys are great to work along side […] 'no stone unturned' approach to finding solu>ons to challenges […] knowledge and passion for web analy>cs and best of breed web opBmizaBon was second to none” Steve Brown, Senior Business Analyst, Vodafone “[…] The Vodafone implementa>on of SiteCatalyst is one of the most impressive I have seen and ranks in the top 10 […]. It is an amazing founda>on for taking ac>on on the data and improving ROI.” Adam Greco, Consul%ng Lead, Omniture


> Great customer feedback "[…] Datalicious understand the value of informa>on and how to leverage it using best of breed soEware. I would recommend the team without hesita>on [...]." James Fleet, Marke%ng Director, Appliances Online "[...] Datalicious have been inBmately involved in building our analyBcs soluBon. Most importantly their knowledge of best prac>ce combined with innova>ve solu>ons has allowed our business to remain nimble and current. They are also nice guys." Tzvi Balbin, Group Digital Marke%ng Lead, Catch of the Day "[...] Datalicious are helping us to move from a last click campaign measurement model to a more accurate media aFribu>on approach. [...] potenBal to significantly change our media planning [...]. Highly recommended." Keith Mirgis, Senior Digital & Social Media Marke%ng Manager, Telstra "We engaged Datalicious to support a strategic change in our business [...] understand our customers [and their transac>ons] beFer to ensure we retained as many as possible [...]" Natalie Farrell, Direct Marke%ng Manager, Luxo~ca


> About SuperTag

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> SuperTag tag management

64

SuperTag

Conversion Tracking

Conversion De-‐duping

Media A=ribu&on

Behavioral Targe&ng

A/B Tes&ng Heat Maps

Live Chat

Web Analy&cs

Any JavaScript

Easily implement and update any JavaScript based tag on any site without IT involvement De-‐duplicate conversions for CPA deals and align repor%ng figures across pla|orms Collect accurate mul%-‐channel media aRribu%on data to provide advanced insights Enable advanced features such as targe%ng, tes%ng and chat to op%mise user experience

September 2012 © Datalicious Pty Ltd

> Unique SuperTag architecture

65

T

B

B

B

§ One tag for all sites & pla|orms §  Hosted internally or externally §  Easy tag implementa%on/updates §  Tag/business rule tes%ng on live site §  Facilitates A/B & MV test execu%on §  Implementa%on of heat-‐maps §  Re-‐targe%ng across channels & tools §  Live chat & phone number targe%ng §  Collect raw page & impression data

T T

SuperTag


Injec%ng JavaScript tags into the page based on business rules using the SuperTag top and boRom containers. The SuperTag top and boRom containers are JavaScript func%ons called in the page code just auer the opening <body> tag and just before the closing </body> tag on all page across all domains.

superT.t()

superT.b()

> Overcoming team barriers

66

Marke&ng SuperTag Technology

Easy to use online user interface enabling marketers to manage tags without intensive technology support


> Cross-‐plajorm integra&on

67

Web Analy&cs Heat Maps Targe&ng Live Chat Tes&ng

SuperTag

CRM/eDMs Paid Search Ad Servers Affiliates DFPs

Centralised uniform business rules to trigger conversions and segment visitors across mul%ple marke%ng pla|orms


September 2012 © Datalicious Pty Ltd 69 Easy to use drag & drop interface to manage tags

§  Adobe SiteCatalyst §  Adobe Test&Target §  Google Analy&cs §  Google DoubleClick §  Microsot Atlas §  MediaMind §  ClearSaleing §  ClickTale §  Olark §  Etc

SuperTag JS hos&ng on client CDN

> SuperTag deployment op&ons

71

Client website

SuperTag JS hos&ng on client server

Email/FTP SuperTag JS publishing

Manual JavaScript

management

Client website

Client website

SuperTag JS management app.supert.ag

Real-‐&me SuperTag JS publishing

SuperTag JS hos&ng on CDN c.supert.ag

CDN = Content delivery network

Dedicated Github client JS archive


JavaScript

JavaScript

JavaScript Tags

Tags

Tags

> CookieBouncer extension


Cookie Bouncer

Search Domain A Prod view

Domain A Checkout

Domain B Payment

Domain A Conversion

Search Domain A Prod view

Domain A Checkout

Domain A Payment

Domain A Conversion

Campaign = search

Campaign = Search

Campaign = Domain A

Campaign = Domain B

Campaign = Search

Cookie

Cookie Cookie

Cookie Cookie

> DataCollector extension

August 2012 © Datalicious Pty Ltd 73

SuperTag app genera&ng JS app.supert.ag

Full SuperTag JS hosted by client or on c.supert.ag

Client pages referencing SuperTag JS

Browser execu&ng SuperTag JS

SuperTag DataCollector(s) d.supert.ag

Splunk saved searches and dashboards

JavaScript JavaScript

Requests

Tags

Logs

Lookup tables

Databases, files, etc

Splunk regex builder and data extracts

3rd party data plajorms (i.e. CRM, POS, IP)

Dedicated client Splunk server(s)

Display ads loading sta&c 1x1 pixel

Requests

> ExactTarget email extension


SuperTag app genera&ng JS app.supert.ag

Full SuperTag JS hosted by client or on c.supert.ag

Client pages referencing SuperTag JS

SuperTag ExactTarget integra&on

JavaScript Tags

Requests

Data Databases, files, etc

ExactTarget business rules and condi&ons

Addi&onal client data

(i.e. CRM, POS)

Dedicated ExactTarget

DataExtension

Relevant ExactTarget

email campaign

Data

List Targeted ExactTarget campaign list

Emails

Clicks, data

> Unique selling points (USPs) §  Superior pla|orm architecture for more flexibility –  Turn any page element into variables for data collec%on or business rules for tag execu%on

–  Cross-‐pla|orm integra%on and data exchange –  Splunk integra%on for advanced data mining

§  Superior tes%ng, deployment and audit features –  Tes%ng of tags & business rules on the live website –  Complete audit trail of all tag changes and tests

§  No lock-‐in, stop using the SuperTag at any %me –  External and internal JavaScript hos%ng available –  Perpetual JavaScript usage rights & Github archive

§  All inclusive pricing structure incen%vizing use September 2012 © Datalicious Pty Ltd 77

> Blue chip SuperTag clients


> Great customer feedback

"Managing third party tags has never been easier [...] simplicity of seMng business rules [...] reducBon in CPA [...].“ Jason Lima, Online Marke%ng, IMB "[...] SuperTag tool is so easy to use [...]. Live tes>ng is par>cularly useful [...] highly recommended [...]." Helene Cameron-‐Heslop, Analyst, Appliances Online "SuperTag speeds up tag implementa>on and gives us increased flexibility [...] manage media and website analyBcs [...].” Alex Crompton, Head of Digital, Aussie

79 September 2012 © Datalicious Pty Ltd


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Data > Insights > Ac&on


adma multi-channel marketing

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