new and old media mix: prospective meta marketing...
TRANSCRIPT
New and Old Media Mix: Prospective Meta Marketing Analysis Glen Urban, MIT and Mike Hegener, GM CDB Annual Conference May 23, 2012
2
Outline New Media Studies
• Gen Y Social Media – Renee and Joyce • Ad Morphing – Gui • App Effectiveness – Glen and Shegito
Million Dollar Question -- Wall Street Journal May 6, 2012 -- How to Allocate budget
App compared to TV – Liberty
Prospective Meta Analysis
GM PMMA Project – Design and Pre-test
CMO PROBLEM
• How much to put into new media? • What to drop? Old media like direct mail and
TV? • Change total spending? Not need as much?
More productive so spend more? • Leading Internet Retailer – $650 million and
75% old /25%new
5
Apps vs. TV
Liberty Mutual project
How effective relative to TV?
Experiment A/B trust app versus forced TV exposure
6
Intro to DubbleWrap
7
TV/Print Ads
Responsibility (Anthem II), http://www.youtube.com/watch?v=E9UICosC5aU
8
Pre/Post Differences, App (AB) vs TV Ads (AC)
LM Familiarity/Consideration AB (App)
AC (TV)
T-test
Mean Mean t p
Likelihood of considering LM (1-10) 1.31 0.82 2.083 .039**
8
The app increases likelihood of consideration by 60% more than TV ads
9
Pre/Post Differences, AB vs AC
Points Allocation: Which of the following companies would you prefer next time you need insurance? (100 points total)
AB (App) AC (TV) T-test
Mean Mean t p
Allstate -1.15 -1.91 1.041 0.300 Farmers -0.54 -0.37 -0.231 0.818
GEICO -1.70 0.08 -2.224 0.028**
Liberty Mutual 7.76 5.78 1.702 0.091*
Nationwide -0.51 -0.28 -0.553 0.581
Progressive -1.63 0.46 -2.061 0.042**
State Farm -1.76 -3.03 1.063 0.290 Other -0.50 -0.80 0.397 0.692
9
10
Conclusion: App vs TV • The app was 60% more effective than TV ads at increasing consideration.
• The app was more effective at making customers feel that…
- Liberty Mutual works hard to meet my changing needs - I would recommend Liberty Mutual to a friend - When moving it is important to me to be secured
against all kind of risks
• The app was 34% more effective than TV ads at increasing points allocation.
- The app was able to steal points from GEICO and Progressive where TV ads were not.
10
11
CMO PROBLEM -- Revisted
Change total spending? Not need as much? More productive so spend more?
P&G – Cut $1 Billion over 3 years “by shift to new digital media”
YouTube Sonic versus Super Bowl TV
12
Prospective Meta Analysis in Marketing (PMMA)
Analogy to Medicine
Gold Standard – test/control and pre/post
Large Samples
Protocol same for all studies
New versus Old Media Clinics and protocol
Global clinical studies
Individual level statistical analysis
13
GM PMMA Project
New versus Traditional Media – GM, Erasmus, INSEAD – Singapore, IPC
• TV vs. Search vs. Banners vs. Facebook • Sub experiments:
– Facebook vs. Youtube, blogs,Twitter (USA) – Direct Mail vs. New Media (Netherlands)
• USA, Netherlands, China field sites • 20,000 respondents base experiment and 4,000 for sub experiments • 3 year project
– Expanding scope and media/regions – Validating experiments
Relative effectiveness given exposure • Causation • Buying Process measures
Model for exposure and budgeting/allocation
14
Stimulus Status Main Experiment TV TV ads sandwiched in tv show content Facebook Insert story into user news feed Banners Banner ad on edmunds.com Search Google search result ad Sub-experiment Twitter Promoted Account and Tweet Youtube Sponsored video search result ad Blogs
Allow user option to read review from: Jalopnik /Autoblog or Car and Driver or individual blogger
Direct Mail Folder with letter, pictures, QR code
15
TV
16
17
Banners
18
Search
19
20
Youtube
21
Pretest Results
Chrome works
Respondents willing to download Chrome/web extension – 10% refusal
50/52 completes
Involvement –Average 2 minutes per stimulus
Measurement encouraging • Pre post consideration differences but small sample • No refusal/drop out in survey questions
22
STATUS
Teams working – GM, MIT, Erasmus, INSEAD
Stimuli -- Chrome Web Extension • TV, Google, Banners, Facebook (USA) • Sub-experiment (n = 3,000) – Twitter, blogs, Youtube
(USA), direct mail Europe (N = 1,000) • China (in process) and Netherlands (Opel in Process) • IPC sub test (in design) Direct Mail Europe
Survey Design – Protocol complete and pretested
23
Managerial Implications GM decisions
• Advertising spend: $2B U.S., $4.48B Global – Importance: 10% improvement is real money
Global Focus • Over half of GM sales are outside U.S. • Substantial Global growth opportunities • Huge efficiencies if assets leveraged intelligently
Implementation Challenges • Change management & running the business – new
agencies, leaders, consolidating budgets, staffs – Don’t lose local market knowledge
• Increasing competition, evolving media environment
24
Managerial Implications, cont.
Research focus is on actionable marketing levers
MIT research methodology innovation • Protocols enable Global learnings • Local research promotes local acceptance
GM/MIT Partnership – IPC, Erasmus, INSEAD, OTHERS WELCOME
25
TEAM
GM-MIT Core Andrew Norton - GM Karen Ebben - GM Sigal Cordeiro - GM Mike Hegener - GM David VanderVeen - GM Jonathan Owen - GM Tracey Sheets - GM Joyce Salisbury - GM Phil Keenan - GM Patricia Hawkins - GM Trina Barta - GM Dee Baker - GM Glen Urban - MIT Catherine Tucker - MIT Ryan Ko - MIT Neel Hajare - MIT Brandon Baker - MIT Qui Nguyen - MIT Shireen Taleghani - MIT Bob Yazbeck - Gongos Brandon Benvenuti - Gongos Chelsey Heitmann - Gongos
Extended/International GM Extended Network:
Jon Beebe - GM Andrew Dinsdale - GM
The Netherlands: Gui Liberali - Erasmus Stefan Stremersch - Erasmus Benedict Dellaert - Erasmus
Gert Jan Prevo - Erasmus Philip Dykewicz - GM John Kalishoek - Opel Netherlands
Andres van der Kuil - Opel Netherlands Esther Roodklif - Opel Netherlands China:
Yakov Bart - INSEAD Sharon Nishi - GM International Operations
Steve Worrall - GM International Operations Rayn Wang - GM International Operations Jaime del Valle Sansierra - GM International Operations