Keynote: How Data-Driven Attribution Returned Greater Returns For TransUnion
Transcript of Keynote: How Data-Driven Attribution Returned Greater Returns For TransUnion
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Confidential | Internal use only
Gaining Unprecedented Insight
Data Driven Attribution
DECEMBER 2015
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2 | © 2015 TransUnion LLC All Rights Reserved Confidential | Internal use only
Agenda• TransUnion
• The Need for a Better Model
• Data-Driven Attribution
• Integrating Offline Channels
• Audience and Remarketing Lists
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3 | © 2015 TransUnion LLC All Rights Reserved Confidential | Internal use only
Empowering smarter decisions and creating better lives
Information is a powerful thing.
And the right information—analyzed by experienced people—can help all of us learn from the past, navigate the present and predict the future.
That's why at TransUnion we go beyond credit data to offer the insights businesses and consumers need to make informed decisions and achieve great things.
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The need for a better model
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More innovation in the past 20 years than the previous 120
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If YouTube were a kid, it would be a fourth grader
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Marketing ROI
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Data Driven Attribution
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…understanding the true connection between marketing and results.
The Business Opportunity…
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Data-driven attribution has opened new frontiers
Data-driven attribution (DDA) has been a key driver in rebalancing TransUnion’s marketing program, allowing for lower spend with consistent impact
1 Display strategy has largely shifted to align with DDA insights
2 DDA insights revealed the need for continued investment in non-brand tactics
3 DRTV investment has been validated through impact to search channels
Spend
Orders
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Data Inputs – 1st and 2nd party
Display• Campaign• Site• Placement• Format
Email• Campaign• Segment• Primary Message• Secondary Message
Affiliate• Campaign• Publisher• Offer
Conversions• New Customer• Returning Customer
Paid Search• Campaign• Provider• Keyword Group• Keyword Creative
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Simple vs. Data-Driven Attribution
SimpleRules-Based
0% 0% 0% 100%
LAST EVENT
25%
EVEN
25%25%25%
40%
POSITION
15%15%30%
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Data-Driven Attribution Methodology
Data Driven A/B Testing
3.1%
2.5%
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Valuing Impressions and Views
Paid Search
Display ImpressionEmail
Paid SearchEmail
Likelihoodof conversion
Likelihoodof conversion
3%
2%
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Valuing Impressions and Views
Paid Search
Display Impression
Paid SearchEmail
50% increase in probability of conversion
Likelihoodof conversion
Likelihoodof conversion
3%
2%
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Don’t give up on display
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Display strategy has largely shifted to align with DDA insights
ORIGINAL STATE
2014 Media Funnel
Display
Display
r%Display budget allocated to retargeting
CURRENT STATE
2015 Media Funnel
Display
Display
2xr%Display budget allocated to prospecting (DDA proved that the channel acts as an introducer)
RESULTS
9% increase in orders from 2014
34% lift on Paid Search conversion rate
DDA insights highlighted impact of Display as an upper funnel channel
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ROI Example: Frequency Capping
Site Recommended daily cap
% of Cumulative Conversions
% of Cumulative cost
A 5 95.75% 65.89%
B 4 95.35% 81.87%
C 4 99.92% 65.66%
D 11 98.20% 69.49%
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Non-Brand Mobile Queries Continue to Grow2
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DDA highlighted the need for continued non-brand Paid Search investment
DDA OBSERVATION RESULTS
197% increase in non-brand orders
78% stronger conversion rate from users who
clicked on non-brand ads
exposure to non-brand ads positively impacts
likelihood to convert on brand queries
ACTION
1 2 3
2014 2015non-brand spend
(for month of analysis, August)
higher non-brand investment YOY
2
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Data Driven AttributionIntegrating TV
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87% of TV viewers interact with second screen*
*Accenture Report April 2015
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Incorporating offline media
Tablet Video
TV AdMobile Paid
Search
Desktop Conversion
Data Integration
Offline Media
Cross-Device Attribution
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6am 8am 10am 12pm 2pm 4pm 6pm 8pm 10pm 12am
Digital Activity
Baseline Web traffic or search activity
TVTV
TVTV
TV
TV
TVTV
Determine incremental impact of TV Airings through machine learning response models
Baseline = web traffic or Google Search queries
How it Works• Evaluate minute-by-minute
and hour-by-hour activity• Machine learning modeling
establishes baseline • Model incremental impact
of airings
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TV Attribution Key Metrics
Response Rate Per Million
TV Attributed Clicks
TV Ad Impressions
* 1,000,000
Cost per TV Attributed Click (CPAC)
TV Ad Cost
TV Attributed Clicks
Strength Index
Search ShareShare of total TV-driven search lift
TV Ad ImpressionsIndexed
Cost Index
Cost
TV ATTRIBUTED WEB VISITS
TV ATTRIBUTED SEARCH
IndexedSearch Share
Share of total TV-driven search lift
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TV Spot (T0) T1
TV Credit30%
TV Credit0%
Combining TV and Digital Conversion Paths
Display Credit
TV Credit10%
DN Credit -30%
DN Credit -10%
DN Credit100%
T2
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Optimizations are improving TV response
TV Impressions
TV IMPRESSIONS & RESPONSE RATE BY DAY
TV Im
pres
sion
s
January February March
Response R
ate
Response Rate (TV Attributed Clicks per 1MM viewers)
AVG. RESPONSE RATE
32 AVG. RESPONSE RATE
21 AVG. RESPONSE RATE
18
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Search – Audience and Remarketing Lists
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Goals
• Increase marketing efficiencies across AdWords and DoubleClick campaigns
• Drive up the number of conversions
• Find a platform that could test a number of audience lists without growing the complexity of tags
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Tactics
• Used Google Analytics Premium audience lists and Remarketing Lists for Search Ads for smarter, more efficient bidding in AdWords and DoubleClick
• Organized audience lists in Google Analytics to maximize budget and avoid overexposure
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Results
• Google Analytics Premium delivered the highest total conversions, most revenue, and second lowest eCPA across all programmatic display buying efforts
• Visitors who launched non-branded searches had:
– 65% higher conversion rate
– 58% higher revenue/transaction
– 50% lower cost/transaction