> Smart Marke+ng < Smart data driven marke-ng
> 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 § Evangelizing smart data driven marke-ng § Making data accessible and ac-onable § Driving industry best prac-ce (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 aLribu+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 ALribu+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
> Metrics framework
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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 (Ac-on)
+Buzz (Sa-sfac-on)
> 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. exis-ng customers
Brand vs. direct response campaign
AU/NZ vs. rest of world
> 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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> 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
Level Reach Engagement Conversion +Buzz
Level 1, people
Level 2, strategic
Level 3, tac+cal
Funnel breakdowns
> Exercise: Metrics framework
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> Single source of truth repor+ng
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Insights Repor+ng
> Manual repor+ng s+ll prevails
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> Media aLribu+on
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Direct mail, email, etc
Facebook TwiLer, 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
Web 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 § 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)
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> First and last click aLribu+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
> Understanding channel mix
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> Adjus+ng for offline impact
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+15 +5 +10 -‐15 -‐5 -‐10
> Targe+ng and tes+ng
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Capture internet traffic Capture 50-‐100% of fair market share of traffic
Increase consumer engagement Exceed 50% of best compe-tor’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
Off-‐site targe-ng
On-‐site targe-ng
Profile targe-ng
> Combining targe+ng pla@orms
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On-‐site segments
Off-‐site segments
> Combining technology
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CRM
> SuperTag code architecture
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§ Central JavaScript container tag § One tag for all sites and plagorms § Hosted internally or externally § Faster tag implementa-on/updates § Eliminates JavaScript caching § Enables code tes-ng on live site § Enables heat map implementa-on § Enables redirects for A/B tes-ng § Enables network wide re-‐targe-ng § Enables live chat implementa-on
Campaign response data
> Combining data sets
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Customer profile data
+ The whole is greater than the sum of its parts
Website behavioural data
> 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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> Sample customer level data
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> Affinity re-‐targe+ng in ac+on
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Different type of visitors respond to different ads. By using category affinity targe-ng, response rates are lijed significantly across products.
Message CTR By Category Affinity
Postpay Prepay Broadb. Business
Blackberry Bold - - - + 5GB Mobile Broadband - - + - Blackberry Storm + - + + 12 Month Caps - + - +
Google: “vodafone omniture case study” or hLp://bit.ly/de70b7
> Ad-‐sequencing in ac+on
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Marke-ng is about telling stories and
stories are not sta-c but evolve over -me
Ad-‐sequencing can help to evolve stories over -me the more users engage with ads
Purchase Cycle
Segments: Colour, price, product affinity, etc
Media Channels
Data Points
Default, awareness
Research, considera+on
Purchase intent
Reten+on, up/cross-‐sell
> Exercise: Targe+ng matrix
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> Quality content is key
Avinash Kaushik: “The principle of garbage in, garbage out applies here. [… what makes a behaviour
targe;ng pla<orm ;ck, and produce results, is not its intelligence, it is your ability to actually feed it the right content which it can then target […. You feed your BT system crap and it will quickly and efficiently target crap to your
customers. Faster then you could ever have yourself.”
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> ClickTale tes+ng case study
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Test Segment Content KPIs Poten+al Results
> Exercise: Tes+ng matrix
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Data > Insights > Ac+on
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