1. The Channel-less
Consumer
TALK ABOUT US USING
#FUTUREM
Identifying Attribution within Mobile

2. Michael Kaushansky
Analytics and Insights, Havas Media,
michael.kaushansky@havasmedia.com
@kaushansky
2
New Approach to Consumer
Centric Modeling

3. • Deterioration in key performance metrics (leads &
sales)
• We looked for answers: why wasn’t our existing
media mix working? Why wasn’t TV, search and
display across screens generating the same
volume of leads?
• Simulations of existing media mix models pointed
to a shift to digital though unclear where. Current
models were not reflective of emerging trends in
media.
Our global Auto client had experienced a
recent deteriorating trend
3

4. • Click to edit Master text styles
– Second level
• Third level
– Fourth level
» Fifth level
The Role of the Consumer Consumer Expectations
What we experienced was a shift in marketing
dynamics

5. Adding to the shift - the emergence of the
multi-channel marketplace
 2 explosive and complementary markets
 Local Advertising: $35B in 2015
 Mobile Commerce: $39B in 2016
 Location, Location, Location
 70% of mobile revenue tied to location by 2015
 40% of mobile search has local intent
1) BIA/Kelsey, U.S. Local Media Forecast, 03/2012
2) eMarketer, US Mobile Commerce Forecast: Capitalizing On Consumers’ Urgent Needs, 01/2012
3) Forrester Report, US Online Sales Forecast, 2009
4) BIA/Kelsey, U.S. Local Media Annual Forecast (2010-2015), 06/2011

6. Cross Channel Shopping will be 6X of Online
Retail alone
Source: Paypal Media Network

7. Multi-channel brings a new complexity to the
purchase funnel
Source: Paypal Media Network
Nearly 1/3 of retailers credited smartphones
with driving traffic to physical stores in 2011,
up from 1/5 in 2010
-Retail Systems Research, ‘The 21st Century Store: The Search for Relevance”, 6/2011
15% of US online shoppers made a holiday
purchase via their mobile, growing 3X over
Holiday 2010
- Baynote, ‘2nd Annual Baynote Holiday Shopping Survey’, 1/2012
- IBM, ‘Benchmark December holiday report’, 1/2012

8. The purchase funnel becomes… the purchase
pretzel
Source: Paypal Media Network

9. Existing model failed to identify the shift
towards digital
Investment
Sales
Black
Box
Consumer journey is unique
Journey metrics are
essential to understand the
impact of media

10. Our objective was clear…update the model!
 Enhance our existing model to address the
unexpected digital shift
 Approach – divided the journey into stages, defined
success metrics across each stage & linked the metrics
to show progression throughout the journey
 Methodology – developed 4 models which explained
key drivers at each stage, i.e. what drove search, site
traffic, leads and sales

11. Of Course it
will work

12. We modeled the consumer journey across the
5 stages
Stage Success Metric
Awareness Organic Branded Search
Engagement Page Views
Consideration Digital Leads
Shopping Showroom Traffic
Purchase Unit Sales
1
2
3
4
5

13. Consumer Stages
Awareness
Engagement
Consideration
Shopping
Purchase
Hierarchical Modeling explained impact at
each stage
4 Independent
ECONOMETRIC
Models
Known Strong
Existing Correlation
Media Mix
TV
Print
OOH
Display
Search
Mobile
Online video
Paid social
Social

14. We identified 12+ data sources across 52 weeks
Structured
Equation
Source Data Begins Timing Data Descriptions Metrics Available
Digital Media (DFA) 2009 daily actual media spend by channel (OLA, SEM) impressions, clicks, hvts
Kantar Evaliant 2010 weekly competitor web impressions and spend impressions, spend
Kantar Stradegy 2011 weekly offline GRP & spend GRP, spend
Sysomos 2009 weekly social media buzz data buzz volume, sentiment
Hitwise/Compete last year daily site visitation and duration visitation, duration
Google Insights 2004 daily total search trends (paid & organic) search trend index
Autodata/Wards 2008 monthly monthly sales data by brand/model/category sales figures
Google Analytics/ Omniture 2009 daily Website/model/configurator/RFQ pageviews visits, configs, RFQ, Model PV
Harte-Hanks 2001 weekly owners, prospects, email/mail campaign, etc.
Urban Science 2009 weekly leads by channel by week leads
Manufacturer 2009 weekly dealer visits dealer visits
Third Party Sites 2009 monthly Comp model PV, day/week/month model pageviews
Brand Tracker 2010 Semi attitudinal data by month consideration, intent
Census 2000 monthly economic data by Geo economic data
Yt= α + β1Mt + β2Et + β3St + β4Tt + εt, Y (represents the dependent variable, e.g.,sales)
M (media), E (engagement), S (searches), T (store traffic), etc.

15. Results
 As suspected… results pointed media
consumption varying at each stage
 We identified 5 key insights

16. 1. Brand equity dominates & TV is king of paid
(36% contribution from TV)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase

17. 2. More channels at play in driving site traffic,
digital media is the workhorse (33%
contribution)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase

18. 3. Paid Search was essential in driving leads
influenced by DRTV (paid/Mobile search +
DRTV @ 46%)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase

19. 4. Leads were the most significant driver of
showroom traffic (40% contribution)
Stage
Awareness
Engagement
Consideration
Shopping
Purchase

20. 5. Showroom traffic was the best proxy of
units sales
Stage
Awareness
Engagement
Consideration
Shopping
Purchase
3500
4000
4500
5000
5500
6000
6500
7000
7500
8000
2400
2600
2800
3000
3200
3400
3600
3800
SalesUnits
Show-rooming was responsible for 82% of sales
Unit
Sales
Showroom
Traffic

21. Moving the consumer further down journey
increasingly relies on paid media
0%
20%
40%
60%
80%
100%
Media
Base
1 2 3 4 5 sales

22. The new models made our simulations more
true-to-life… (what-if scenarios) identified
dimensioning returns & ROI

23. What we’ve learned…
1. Consistently / frequently assess the journey of your consumers
2. Digital media is significant in the middle of the journey
3. Mobile’s role was stronger than previously thought
4. Promotional messaging is effective if consistent at each stage
5. Exogenous data (weather & holidays) have minimal impact
6. Going dark beyond 5-weeks would be detrimental
7. Optimizing media at each stage points to a 12% improvement

24. Ramifications and things you should consider
Do Your
Homework
Determine
consumer
behavior by
stage/funnel
Weight social
influence
along journey
Set up for
measurement
success
Establish KPIs
along
purchase path
CRM lists
Paid, owned
and earned
media
Unify 3
screens
Creative +
Media
Merge screen
identifiers and
interactions
Crunch data
What does it
tell you?
Weight
activity
against
conversion
contribution
Optimize
accordingly
Future
Consideration
Weight social
influence
along the
journey
Invest in
approach &
tech to unify
screens