1. Can Digital Metrics be a
Substitute for Sales Data?
Satya Menon
Chief Scientist
Millward Brown
@satya_menon
Ciju Nair
VP Analytic Consulting
Millward Brown
@cijutr
6. Marketing Eco-System
What is the Short-term Impact on business?
What is Longer term Impact on brand equity?
EARNED OWNED
PAID
SHARED
EXPERIENCE
ATL/BTL
Online/Mobile ads
Brand Partnerships
Search
PR/News
WOM/Buzz
Social Media
Viral Video
Brand Website(s)
Social Media
Fan Pages
Corporate Events
Employees
Dealers/staff
Test drives
Auto Shows
Loyalty programs
7. Connected Data Helps Drive Modeling
Insights….
SALES DATA
Includes Inventory,
Incentives & Pricing
COMPETE PANEL
MACROECONOMIC
INDICATORS
2 million panelists
Online clickstream
behavior
SOCIAL DATA
8. How does Digital influence Sales?
Digital &
Social Media
Direct sales impact
In-direct sales impact
Owned Media
Earned Media
Other Sales Drivers
Brand Health
Paid Media
Paid Media Halos from brand
variants
POE Amplification
Media Synergies
Creative Wear-out
Magic moments/Tent pole events
Fighting strategy & Weights
Trade activity
Trade Halos from brand variants
Product launches / innovation /
cannibalization
Sampling / Test drive etc.
Events & Sponsorships
Co-Marketing
Competitor Trade
Competitor Media
Macroeconomic factors
Seasonality
Holidays
Sales
9. So what is new – Digital as leading
indicator of Sales?
• Leading metrics
• Direct and indirect effects
• Multiplier effect
• Noise, threshold and other drivers
In summary, digital metrics can act as leading indicators of sales and
hence also act of sales proxy in many categories
10. Cleaning – Social data
Spam cleaning used to filter out non-US content and mentions of
handles not belonging to the cosmetic brand.
CLEAN
OFF TOPIC
SPAM
TOTAL3,385,502
279,323
(8%)
520,997
(15%)
2,585,182
MATERESA JUAN TALISIC
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Victor Speed Jackson to the conversation
GreenPetProducts
@diez_maybelline thanks for the follow
TY MARIE
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it!!! I bought mine at Target xoxo
GoCelebrityUS
RT @msleamichele A signed bookplate, @LOrealParisUSA
Colour Riche lipcolour AND an ambition card!
http://t.co/IohqOU0fst
my-safest-haven
utosnimavic:
Nyx, Goddess of the night #Nyx #Goddess of Night
#Mythology
Selflessism
#ugh computer pls #i can't handle the torment #someone save
me from my virus infected laptop #or place me in hybernation
until christmas bc mac #ugh
11. Since it was launched in early October 2013, Dodge Durango’s Ron Burgundy campaign has
generated a True Reach® of 10 million views. A vast majority of the viewership has come
from shared content as earned media amounting to roughly 10 times the
media that was paid for by Chrysler.
Dodge Durango’s Ron Burgundy campaign
12. Durango Campaign
* POE is Paid, Owned and Earned media. Figures in brackets are pre vs post launch of campaign
Media
Contributions
5.2%
POE
Amplification
2.6%
(1.1% to
4.3%)
Online
Engagement
12%
Durango TV
Advertising
4.2%
Durango TV
Advertising
2.3%
Durango
Organic
Search
2.1%
Seasonalit
y
1.7%
Durango
Shoppers
3.8%
Gas Price
-2.7%
Durango
Online
Ads
0.7%
Durango
Print Ads
0.3%
Durango
Online
Ads
0.05%
Durango
Print
Advertising
0.02%
Other
Dodge TV
Advertising
0.07%
Other Dodge
Online
Advertising
0.2%
Durango
Online
News
2.9%
Dodge
Durango
Social
2.1%
Incentives
17.0%
(16.7% to 17.4%)
Segment
Shoppers
1.0%
Category and
Macroeconomic
-1.1%
Increment
al Sales
37%
Base
63%
Paid media impact increased from 1.5% to 10.9%
POE Amplification increased from 1.1% to 4.3%
Online Engagement had high sales contribution at 12%
13. Impact on Sales Pre & Post Campaign
0
200
400
600
800
1000
1200
1400
1600
Durango Shoppers Leading 4 Weeks
Durango Incentives
Durango TV
Durango Online
Durango Print
Average Gas Price
Dodge Durango Social
Seasonality
Base
Estimated Sales
Contribution
Ron Burgundy campaign
Durango Shoppers was a leading indicator (4 weeks) predicting future sales
14. Pre-launch social and online activity
were leading indicators for PS4 sales
0
100000
200000
300000
400000
500000
600000
700000
800000
900000
Online Ad
Holidays
Facebook +_Twitter + YouTube
TV
Shoppers
Base
Estimated Sales
Contribution
PS4 launchElectronics Entertainment Expo
Conference
PS4 TV followed by Online
shoppers and Online media
(comparable to TV) were the
biggest drivers of PS4 sales.
However online ads generated
twice the shopper demand as TV
TV GRPs and Social conversation
volume in FB, Twitter & Youtube
during E3 conference had a lagged
impact on PS4 launch sales
16. Sharing some thoughts on Social data
and what next…
Every time we look at comparisons of social
versus sales the same questions come up:
1. How much sales lag is due to category
dynamics
2. How much of the sales lag is artificial and due
to the different data reporting time frames
3. Understand threshold levels at which Social
and other digital metrics start having a Sales /
Brand Equity impact
4. Online vs Offline impact of social
conversations
We would love to know the answers! “We are further exploring some partial truths
we already know from experience (limited case studies) and academic work. “
Diminishing
Return
Optimal RangeWastage
Steep increase next $
more profitable than
previous $ spent
Slow increase and next $
more profitable than
previous $ spent
Media reaches saturation
levels and next $ not as
profitable as last
Guiyang Xiong, Sundar Bharadwaj (2014) Prerelease Buzz Evolution Patterns and New Product
Performance. Marketing Science http://dx.doi.org/10.1287/mksc.2013.0828
17. …Re-Think Predictive Value in Social Conversations
of key consumer segments over time
It is critical that we understand the Social/WOM
“contagion effects” of advertising via sharing and
conversations.
Inferring drivers of Future Brand Performance and
Growth
“We are also exploring how consistency of:
1. Brand Love Scores (derived from social
conversations among consumers) and/or
2. an intermediary metric like state dependence
behavior can also be used to classify and separate -
loyals from switchers
and their flow/evolution patterns over time can be used
to infer impact of social/WOM on sales and predict
how different brands will fare in future”
Overwhelmed
strugglers
Price-sensitive
Chillers
Stylish Fun-seekers
Go-
with-
the-
Flow
Traditional
Performers
Conscious Living
18. Key Take Aways
There is significant value in digital metrics as:
• Leading indicator of future Sales/Brand Equity
• As a Proxy for Sales and as a supplement to competitor intelligence
Key intermediary digital metrics we find to be of immense value in signaling intent to purchase and
driving sales are:
• Online shoppers (Volume of shoppers engaging in any digital activity e.g. MB Digital)
• Organic search (Google, other search engines and site search e.g. Amazon, Ebay)
• Social buzz (Twitter, Facebook, Youtube etc.)
• Website visits (content/information sharing and ecommerce )
Estimation Bias when computing Digital ROIs
• TV ROIs are higher when including the amplification effects, it has in driving social and online
shoppers
• Digital ROIs could look inflated at low levels of spend and expected to come down when scaled
19. Can Digital Metrics be
a Substitute for Sales
Data?
DOUBLE TAKE
Satya Menon
CHIEF SCIENTIST
Millward Brown Analytics
@satya_menon
Ciju Nair
VP ANALYTIC CONSULTING
Millward Brown Analytics
@cijutr
Notas del editor
Leading metrics: Some metrics are leading by measurement e.g. online shoppers (MBD metric), others like search measure are proxies of purchase intent and hence sales
Direct and indirect effects: Advertising drives immediate sales directly and indirectly via amplification effects of Paid on Owned and Earned media
Multiplier effect: via word of mouth (online/offline) in some capacity….and there is hidden information of significant predictive value in these conversations
Noise, threshold and other drivers: social data especially needs to be filtered for noise and unrelated comments in addition to impact of other drivers on sales. Lastly, it also needs to have enough volume to be above threshold levels
In summary, digital metrics can act as leading indicators of sales and hence also act of sales proxy in many categories
i.e. how long it takes someone to buy a phone versus a car or replace an empty bottle of whisky?
I might tweet about a new campaign now but not buy a new bottle till the old one is done. We are interested in understanding what time differences exist between most folks tweeting and then translating into a purchase on average by category – of course, the distribution of that time in between could exhibit significant heterogeneity
e.g. especially in some categories like healthcare/pharma where there are longer lead times from incidence of a condition to scheduling/getting doc appointments, ordering and picking up prescriptions etc.
Same is the case with auto where it’s complex with consumers taking less than 2 weeks to over 90days to buy a car. So there is significant differences between consumers/segments too.
Other instances are wrt auto/home purchases – loan / lease approvals, purchase and registration dates etc.