Next-generation MMM is an integrated process that leverages its understanding of overall demand drivers (marketing and non-marketing) along with other research external to MMM measurement to present a holistic marketing strategy to target growth opportunities. Attribution modeling focuses on understanding the impact of marketing or, more specifically, media campaigns on each individual consumer decision or “conversion.” It is a “bottom-up” approach, measuring total impact by aggregating up from transaction-specific impacts. Both MMM and attribution modeling are great for the purpose they are intended for, with MMM guiding overall marketing strategy and attribution modeling guiding tactical campaign performance.

2. MARKETING PERFORMANCE
MANAGEMENT: ATTRIBUTION
OR MARKETING MIX?
Thought Leadership by
2

3. Srishti Gupta
President
IRI Media Center of Excellence
Joy Joseph
Practice Leader, Marketing Productivity
IRI Strategic Analytics
TODAY’S PRESENTERS
3

4. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
4

5. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
5

6. INFORMATION EXPLOSION HAS CREATED A DIVERSE AND WELL
INFORMED CONSUMER
Health Benefits Occasions
Lifestyle
Democracy of information access has led to a highly evolved
and diversified consumer landscape - targeted marketing has
become indispensable for consumer relevancy
Digital revolution has also created complex
shopper journeys - imperative to integrate online,
offline and touch points to engage across various
stages of the Shopper journey
6

7. PROLIFERATION OF MEDIA TOUCH POINTS HAS LED TO A COMPLEX
CONSUMER JOURNEY
Digital ad optimization supported a far more complex engagement model, individual level
sales conversion rather than aggregate sales contributions were required - enter
Attribution Modeling
A parallel measurement environment was initially OK because Digital stakeholders initially
operated in a separate environment from traditional media, but not for long…
Speed
Granularity
7

8. THESE SEPARATE WORLDS COLLIDED AS ADVERTISERS RAMPED
UP ON DIGITAL INVESTMENTS, FREQUENTLY AT THE COST OF
TRADITIONAL MEDIA
Digital and traditional media stakeholders began finding themselves in the same conference
room with increasing frequency - a comparison and even bake-off between the two
approaches was inevitable.
DIGITAL
AGENCIES
PUBLISHERS/ AD
NETWORKS/
EXCHANGES
CRM/ DIGITAL
MEDIA LEAD
INSIGHTS
BRAND
MANAGEMENT
TRADITIONAL
AGENCIES
MMM Sandbox
Attribution Sandbox
Buy-side
Sell-side
8

9. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
9

10. IN AN INCREASINGLY ADDRESSABLE WORLD, ATTRIBUTION
EPITOMIZES MICRO-MARKETING
Un-Exposed
EXPOSED
Conversions (“Lift”)
Display + Search
Social + Search
Social + Search
Cross-PlatformSynergies
Lifestyles Purchase BehaviorDemographics
Post-campaign
Diagnostics
10

11. HYPER-GRANULARITY UNCOVERS ARBITRAGE OPPORTUNITIES
WITHIN THE LONG-TAIL OF DIGITAL OPTIONS
Leaderboard
Rectangle
Skyscraper
Internalize pay-for-performance:
Align growth opportunities with the
optimal execution mix
11

12. THIRD-PARTY MATCHING ALLOWS ATTRIBUTION PLATFORMS TO
INTEGRATE ACROSS A WIDE RANGE OF DATA SOURCES
HH
12

13. NEAR-REAL-TIME MEASUREMENT TO SUPPORT
PROGRAMMATIC INITIATIVES
Mid-campaign
Attribution Read
Optimize/Course-
correct
Post-campaign
Diagnostics/
Lessons Learned/
Set-up for next
campaign
4-8 Week Cycle-time
DMP/ Conversion
Metrics
Programmatic/
DSP/Ad Exchanges
DMP/ Conversion
Metrics
13

14. ATTRIBUTION COMES WITH ITS OWN ISSUES THOUGH…
• Attribution largely ignores offline touch points, resulting in potentially
inflated ROAS estimates
• Big data doesn’t mean “all data”- Integrating micro-data across multiple
sources with varying quality and inconsistent matching across multiple
third party sources potentially drive biased campaign lift estimates
• Attribution can be too short-term focused, optimizing over weeks rather
than quarters, so cannot address longer-term marketing planning decisions
14

15. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
15

16. MMM ENABLES PORTFOLIO STRATEGY BY OPTIMIZING
ALLOCATION BY BRAND AS WELL AS BY PLATFORM
15
20
30
35
18
36
18
28
Brand A
Brand B
Brand C
Brand D
Current Optimal
SpendAllocation
Cross-PlatformAllocation16

17. BRAND CROSS-EFFECTS & HALO CAN BE LEVERAGED FOR
EFFICIENT CROSS-BRAND CAMPAIGNS
A B C D
A
B
C
D
Halo Impact
AdvertisedBrand
Cross-BrandHalo
SourcesofMktg.Sales
17

18. MMM ALSO SUPPORTS STRATEGIC PLANNING PROCESSES…
Long-termBrandEquity
DemandPlanning
18

19. DETERMINE OPTIMAL SPEND LEVELS ACCOUNTING FOR
SATURATION AND SIMULATE MULTIPLE STRATEGIES FOR
SUPPORTING INNOVATION…
NewProductMarketing
RightSpend
19

20. MOST IMPORTANTLY, MMM ALSO SUPPORTS OFFLINE MEDIA
PLANNING…
20

21. MMM DISADVANTAGES
• Digital can present challenges for MMM, especially where granular data
(down to markets and trade areas) is infeasible
• Hyper-targeted and addressable campaigns do not have the scale to
register accurately in MMM
• Pure MMM takes a one size fits all approach, but marketing
responsiveness varies across consumer groups
• Synergies, especially across digital campaigns are difficult to read without
single source data (down to individual audience level), resulting in
underestimation of cross-platform campaigns in MMM
• Finally, the broad and encompassing demand measurement MMM
undertakes comes at a cost; long cycle times - model updates can often
take 8 or more weeks from data gathering to insights/execution
21

22. LACK OF INTEGRATION CAN IMPACT INSIGHTS AND STRATEGY IN
MULTIPLE WAYS...
Case Study:
12-week Cross-Media Campaign for a OTC Health Brand - MMM indicated the
media portion was around 70 percent of the lift suggested by the attribution model
(11.6 percent vs. 16.5 percent).
A major in-store shopper initiative at a large regional retail chain was skewing
Online Video up in the attribution study, while MMM was underestimating the
highly targeted Display campaign.
MTA Online Video Search TV
Sales Lift 5.7% 3.6% 7.2%
MMM Online Video Search TV Promo
Sales Lift 2.1% 2.9% 6.6% 4.1%
22

23. WHAT DO YOU DO WHEN FACED WITH APPLES AND ORANGES?
23

24. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
24

25. DEFINE THE HORIZON & CADENCE…
Both MMM and
Attribution Modeling
are great for the
purpose they are
intended for:
 MMM guiding overall
marketing strategy
 Attribution Modeling
guiding tactical
campaign
performance
25

26. DESIGNING THE INTEGRATED ANALYTIC MODEL
• Offline and non-marketing drivers’
impact from MMM are leveraged
as covariate controls in Attribution
Modeling to more accurately
quantify Digital/addressable
campaign lifts
• Lifts from Digital and other
targeted campaigns measured in
Attribution models are used in
MMM-driven budget allocation and
portfolio optimizations to more
accurately represent these
26

27. SUCCESS DEPENDS UPON EXECUTION…AND ADOPTION

28. TODAY’S AGENDA
Why is this debate gathering momentum?
The case for and against Attribution
Pros and Cons with MMM
[MMM + Attribution]= Marketing Productivity Excellence
Vision for the future
28

30. SOME PREDICTIONS FOR THE VERY NEAR FUTURE…
 Immediate future will see a more cogent integration of MMM and Attribution
 A greater focus on targeting will push measurement down to at least household-
level, if not individual consumer level
 Now that we have stopped being awestruck by the sheer amount of data that is
creating “insights”, it is time to address issues like data bias
 Focus will shift to predictive accuracy vs. backward-looking campaign scorecard
 Advanced probability based models will be explored to compensate for data
biases and for understanding non-addressable offline media

31. THANK YOU!
Srishti.Gupta@IRIworldwide.com
Joy.Joseph@IRIworldwide.com
QUESTIONS?