Sponsor Breakfast Presentation by TruSignal
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Transcript of Sponsor Breakfast Presentation by TruSignal
Using Big Data and Audience Expansion to Find Your Ideal AudienceJune 21, 2013
David Dowhan@daviddowhanPresident, TruSignal
Confidential & Proprietary
Big Data Powered Targeting Future is Here…
Big Data lets target specific users at scale
1:1 digital marketing requires data signals
Challenge—sifting through all of the data to
discover the right signals for your specific goals
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Lots of Data—Most of it useless…
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Profile Data
DemographicsPast Purchases
FinancialsGeography
HobbiesCensusAssets
Household
Behavioral
Intenders
Search Terms
Contextual
Web Navigation
Retargeting
“In-Market”
Social Likes
Technographic
Time of Day
Device Type
Device Speed
Day of Week
Site Index
Ownership
1st Party
2nd Party
3rd Party
Audience
Segments
Clusters
Genetic Algo’s
Lookalikes
Act-alikes
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Key Ingredients for Successful Audience Targeting
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Start with the right raw data
Repeatable process with scale and efficiency
Portable – usable across multiple touch points
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Right Data Depends Upon Marketing Goals
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DaysConversion
Convert Existing Demand
Weeks
Prospecting
Generate New Demand
Targeted BrandingMonthsBuild Awareness
and Future Demand
TimingCampaignGoalsData Type
PROFILEDATA
BEHAVIORALDATA
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rofil
eB
ehav
iora
lCreating Audiences of Scale and Efficiency
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Raw Data Points Audiences
•Demographics•Financial•Lifestyle•Interests•Census
High Scale, Low Signal
•Search Term•Web navigation•Contextual site visit•Lifestage event•Visited your website
Low Scale, High Signal
Act-alike Models Inferred Segments Intenders
Boost scale, without losing signal
Lookalike Models Segment Combinations Prebuilt Clusters
Boost signal, without losing scale
Combine
Expand
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Case Study: Improve Targeting Efficiency
Branding
Prospecting
Converting
Targeting For Efficiency
65%Improvement in targeting accuracy
Large Scale20M
‣ Luxury auto brand launch‣ RTB, premium, video, and social‣ Existing demo targeting
‣ Age 35-64‣ Income $150k+‣ Males‣ College Educated
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Old Way—Scale and Accuracy Problems
Age: 36-64
126,000,000Users
TotalPopulation
Gender: Male
115,000,000Users
Education: College
37,000,000 Users
Income: $150+
32,000,000Users
SmallScale!
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Prebuilt Clusters - Convenient but Inefficient
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40% Audience Reach!
Need to buy 25% of all segments
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Custom Predictive Audience Model
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Which data signal matter?
How they relate to each other?
Relative importance of each signal
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Step 1: Find the Right Data
Analyzed owners of : Audi A6, BMW 5, Infiniti M, Cadillac XTS, Jaguar XF, Lincoln MKS with 40 sources of offline profile data
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Step 1: Find the Right Data
Select Predictive Factors•Income
•Household purchasing power
•Age
•Interest: Money making, DIY, finances
•Hobbies: RV Travel, camping, cooking
•Ethnicity
•High mortgage credit
•Credit card balances
•Occupation
•Mail order buyer (prefers Amex)
•Past Purchases: jewelry, children’s goods
•Pet owner
124 predictive factors from 10 different data sets
Contribution by Data Category
4%
3%
3%
2%23%23%
21%21%
21%21%
19%19%
7%7%
9%9%
4%
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Step 2: Apply Model to Build Scale
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Premium Publishers
Activate custom audiences directly within DoubleClick
for Publishers
Trading DesksAD AGENCY
INDEPENDENT
Step 3: Port Audience to Media Access Points
Ad Networks
DSP’s
Top Portals
RTB Exchanges
Video
Audience POOL
News feedMobile
DoubleClick for Publishers
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Demographic vs TruSignal Comparison
40,000 sample customers
Best demographic targeting
•Males•Age 35-64•$150k+ income•College educated
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Same Scale – Bigger Reach
Scale Reach Efficiency
CriteriaTargeted Audience
% Actual Customers
Efficiency
Gender, Age, Income, Education
8,300,000 26%3.0
TruSignal 8th Percentile 8,000,000 43% 5.4
For the same impression levels, TruSignal improved the total audience reach by 65%
Hold Scale Constant
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Same Reach – Less Budget $$
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Scale Reach Efficiency
CriteriaTargeted Audience
% Actual Customers
Efficiency
Gender, Age, Education 25,700,000 40% 1.8TruSignal 7th %tile 7,000,000 40% 5.7
To achieve the same reach as demo targeting, TruSignal only needs to use 27% of the impressions!
Hold Reach Constant
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Key Take Aways
Big Data powers more efficient technique that move way beyond demographics and pre-built clusters
Campaign objectives determine appropriate raw data and audience development methodology
A well-executed custom approach can produce a scalable, portable, and efficient audience
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Using Big Data and Audience Expansion to Find Your Ideal AudienceJune 21, 2013
David Dowhan@daviddowhanPresident, TruSignal