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In a world where data are plentiful, not rare, what are the new mindsets and skillsets market researchers need to prosper? The presentation will discuss New Realities (that old approaches may not be the right approaches anymore), New Acknowledgements (that assuming what people tell us is true, is often wrong), and New Uses (that MR’s role in “marketing” needs to be broader than it’s ever been).
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©TNS 2012
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Several trends are coming together to challenge the 100 year old business model behind Market Research
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1.
Market Research started because the data needed to make decisions were rare
2.
Specialized skillsets developed around data collection and analyzing data from single projects
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But we now live in a world where data are not rare…
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Market research must evolve to fit this new reality
1How can we capitalize on the wealth of data now available?
How can we understand why things are happening?2
How can we link directly to business performance?3
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We need different mindsets…
Old Research
Asking
Infinite questions we could ask
Client business issue narrows to precise questions – which we formulate before collecting data
Resulting in exact answers (and/or tried and tested ways of interpreting the answers)
New Research
Exploring/Interrogating
Huge amount of data from multiple sources available – but NOT tailored to answer specific questions
Client business issue narrows to precise questions - which we try to answer using data which are already available
Meaning we need to think how best to answer the questions with the data we have
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…and new skill sets
Old Research
Collect Data
Sample Design
Questionnaire Design
Banners & X-Tabs
Descriptive Analysis
New Research
Find Data
Make Connections
Programming & Statistics
Multi-source modeling & prediction
Data Science
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Big Data, Little Data and NEW Market Research
New Realities“Old approaches are no longer the right approaches”
New Acknowledgments“Assuming what people tell us is true, is often wrong”
New Uses“Market Research’s role in ‘Marketing’ needs to be broader than it has ever been”
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New Realities“Old approaches are no longer the right approaches”
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Most of our “Standard” survey metrics have shockingly little relationship to actual buying behavior
Correlations versus actual panel purchase behaviour (P12M)Countries: Laundry detergent & retailers in the UK, USA and ChinaRespondent-level = correlation between ratings of each individual and actual behaviour of individualAggregate-level = correlation between sum score of ratings and actual market share
Awareness
First Mention AwarenessOther SpontaneousFamiliarityAided Awareness
Brand usage
Brand strength
0.920.810.870.68
0.570.250.250.11
Stated Past 3 MonthsRegularly BuyBrand Most OftenConstant Sum (Next 10)
0.980.960.960.96
0.580.620.690.74
Brand Satisfaction (10-point scale)Purchase IntentionRecommendation (NPS)“Only One I’d Ever Buy”
0.710.030.230.95
0.310.080.220.37
Individual
Aggregatevs.
Individual
Aggregatevs.
Individual
Aggregatevs.
-
NOTE: Measures in red are poor reflectors of actual behaviour
10
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Multi-source, Big & Small Data
Multi-sources of data − may require big data platforms
Connection of data sources for holistically understanding attitudes and behaviors
Triangulation of multiple data sources to connect story
Actionable Insights may be more inferential than exact
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Consider how we use multi-source data for Exploring, Interrogating, and Predicting
Hard integration
PredictingExploring/
Interrogating
Querying multiple data sources to address specific questions or bring the story together
Using multi-source data on the same platform for prediction modeling, running of ‘what if’ scenarios, etc.
May use single-source data or rely on lookalike modeling
Soft integration
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Using technology we know more than ever about customers’ experiences without asking
Ad exposure
Mobile usage (apps, features, etc)
Location awareness
Audio sampling
Web search and sites
By relying more on ”passive” listening, we can rely less on questioning
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New Acknowledgments“Assuming what people tell us is true, is often wrong”
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The reality of most questionnaires…
Do you remember if you saw this
ad?
No, I don’t think I
did? Did I?Erm, yes…
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Observing panelist exposure to digital media
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DME Technology tracks online ad exposure across survey
panels using cookies
Campaign Impact and
OptimizationAttitudinal
Impact Survey
Yes Ad
No Ad
Groups of exposed and not exposed
panelists are recruited for the
survey
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So can we use technology to link observational, attitudinal and behavioral data?
Saw the adBought the
product
TNS conducted a digital brand effectiveness study
for a beverage campaign where ad exposure was
tracked across the TNS research panel.
TNS also matched the exposed TNS panelists
with the Kantar Shopcom purchase data platform to determine the lift in actual purchase of the beverage.
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What did we learn?
The campaign had a significant impact on dollars spent on the beverage during the campaign…
16.25% lift in $ per 100 HHs
CONTROLRatio Change: .90
EXPOSEDRatio Change: 1.05
Pre Campaign
Post Campaign
$673
$607
Pre Campaign
Post Campaign
$689
$656
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Surely technology should be able to move us beyond just online ad exposure?
SINGLE SOURCE PANEL
Cross media impact and
Optimization
Attitudinal survey
Ad
DME Technology tracks online ad
exposure
Ad
App on mobile device “listens” to which TV
ads are viewed
App tracks ad exposure on
tablets and mobile devices
Ad
Ad
TNS 4 Screen Pilot
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Example - Traditional recognition metrics are misleading
First, we confirmed that Recognition should not be used to measure effectiveness of TV advertising.
Recognize TV
Do Not Recognize TV
Exposed to TV
Not Exposed to TV
Aided Awareness 70% 47% 57% 51%
Power In The Mind 3.99 1.44 2.81 1.71
Exposed to TV
Not Exposed to TV
Recognized the TV 27% 23%
Did not recognize the TV 73% 77%
While the TV ad positively impacted awareness and brand equity, traditional recognition metrics significantly overstated the impact of the TV advertising.
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New Uses“Market Research’s role in ‘Marketing’ is now broader than it has ever been”
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New Data and Technology allows Market Research to move into areas where it previously hasn’t been able to play
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New Research: Using Market Research to better target opportunities
Via a 3 minute survey it is possible to identify the consumers willing to spend more with your brand…
Buy more
Buy the same
Buy less
Growth Segment
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Look-alike models
Look-alike modeling lets you reach your Brand Growth Target in digital media at mass scale
Growth segment identified via survey
AD AD
AD
AD
Internet Behavior
Purchase Behavior
AD
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Example – ‘Digital Segment Targeting’ delivers more impressions to the right consumers
0%
% of segment
Cum % of all consumers
0%
20%
40%
60%
80%
100%
20% 40% 60% 80% 100%
20% of “Growth Segment”
reached at random
Over 60% of “Growth Segment”
reached using DST
‘Growth Segment’
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Big Data, Little Data and NEW Market Research
New Realities“Old approaches are no longer the right approaches”
New Acknowledgments“Assuming what people tell us is true, is often wrong”
New Uses“Market Research’s role in ‘Marketing’ needs to be broader than it has ever been”
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“Someone has to do something…
…It’s just incredibly pathetic that it has to be us”
Jerry Garcia
©TNS 2012
