Forget Everything You Thought You Knew: Adapting Attribution for the Pandemic & the Rapidly
Evolving “New Normal” of Recovery -Lessons from the Front Lines
Attribution & Analytics Accelerator 2020
Welcome!
2
Today’s Speakers:
Judd Eder
VP Client Success
OptiMine
Jamie Glover
Director, Client Success
OptiMine
About OptiMine
3
Cloud-based cross-channel agile marketing measurement and optimization.
Measure the actionable ROI of all marketing investments (digital & traditional) and their effects across any channel (online, in-store,
call center, channels, agents and more).
PANDEMIC DISRUPTION: MARKETING MEASUREMENT IMPLICATIONS
4
The Pandemic is Driving Massive Disruption and Change
Media Consumption Has Changed
Purchase Behavior Has Changed
Consumer Psychographics Have Changed
Are these the “New Normal”?
FIRST, FORGET WHAT YOU THOUGHT YOU KNEW
6
Pandemic’s Significant Implications for Marketing Measurement
7
1This history & data is
less relevant and not
useful for marketing
measurement.
And, it could be
damaging.
2 The “Recovery
Rollercoaster”: How
does a brand
continuously monitor
and adjust for
unpredictable peaks
& valleys?
Forget History for a Moment
8
Recovery
DataPre-Pandemic
Data
Reven
ue
Year-Month (Calendar)
Client Case Study: Large National Retailer
A “Change Point” is
Detected:
1. Outcome of Interest
(Revenue) and / or
Marketing Channel
Investment has Changed
+/- 3 Std. Dev. YoY
2. Stores Closed Due to
COVID Driving Revenue
Shift and Change
3. Channel Preferences
Shift Significantly
New Modeling Window
Beginning May, 2020
Pandemic
Data
Forget History for a Moment
9
Recovery
Data
Historic & Pandemic
Data
Reven
ue
Year-Month (Calendar)
Client Case Study: Large National Retailer
Re-Build/Train/Score
Models:
1. Using Narrower Window
vs. Attempting to Overlay
Controls for Pre-
Pandemic Period
2. Model & Examine
Incremental Media
Contributions (to
Compare Performance
Change)
3. Evaluate Frequently
(Monthly for this Client)
to Determine When/ How
to Shift Model Training
Window
“Forget” this Historical and Pandemic Data
& Remove from Time-Series
Models
Move to Daily Level Detail in Models
10
Forgetting History: Why it Matters
Marketing Channel COVID-Era ROAS Change
Paid Search – Product Category Terms -8%
OOH NA- No COVID-Era Spend
Paid Search - Brand 36%
Email 149%
Direct Mail 118%
Paid Social - Instagram -35%
Paid Social - Facebook 176%
Paid Social - Pinterest -72%
Paid Search - Non Brand -29%
Hulu NA- No COVID-Era Spend
PLA -29%
TV 128%
Highlighting Change Point-Driven
Performance Measurement:
1. Guidance Using Pre-COVID Data
Would Have Been In-Accurate and
Incorrect
2. Careful Analysis of Why
Performance Changed Is Critical to
Navigating Mix Changes & Driving
Optimal Performance
Brand Example COVID-Era Performance Changes:
11
Forgetting History: Why it Matters
Marketing Channel COVID-Era ROAS Change
Paid Search – Product Category Terms -8%
OOH NA- No COVID-Era Spend
Paid Search - Brand 36%
Email 149%
Direct Mail 118%
Paid Social - Instagram -35%
Paid Social - Facebook 176%
Paid Social - Pinterest -72%
Paid Search - Non Brand -29%
Hulu NA- No COVID-Era Spend
PLA -29%
TV 128%
Highlighting Change Point-Driven
Performance Measurement:
1. Guidance Using Pre-COVID Data
Would Have Been In-Accurate and
Incorrect
2. Careful Analysis of Why Performance
Changed
Is Critical to Navigating Mix Changes &
Driving Optimal Performance:
- Spend Volumes, Yield Curves, CPMs
Drove Some Efficiency Shift
- Execution & Strategy Drove Other
Portions of Shift
- Most Important: The Shifts Have Been
Detected & Measured
Forgetting History: Why it Matters
Highlighting Change Point-Driven
Performance Measurement:
1. Evaluating Why TV Performance
Increased in COVID Era:
• Did Spend Decrease (and
thereby become more efficient)?
• Did CPMs Change?
• Did Strategy or Creative
Change?
2. None of the Above:
Value per Reach increased suggesting
more engaged audience, more relevance
and less clutter → higher performance and
overall increase along the entire yield
curve.
- Most Important: The Shifts Have Been
Detected & Measured and are now
actionable
Agile Marketing Measurement Adaptation
13
Marketing Channel
Index: Incremental Contribution
to
In-Store Revenues
Index: Incremental Contribution
to
E-Commerce Revenues
Direct Mail Low Low
Email Low Medium
OLA- Display Low Medium
OLA- Retargeting Low Medium
Organic Social High High
Paid Search- Brand High Medium
Paid Search- Local Low Low
Paid Search- Prod Category High Medium
Paid Search- Non Brand High High
Paid Social- Facebook Medium Medium
Paid Social- Instagram Medium Medium
Paid Social- Pinterest Medium Medium
PLA High Medium
Print Low Low
Radio- Local Low Low
Radio- Streaming Low Low
TV High High
Marketing Performance- Contributions by
Channel:
1. COVID Forcing Fundamental Shift to E-
Commerce. Is it Permanent?
2. Mix to Drive E-Commerce (vs In-Store)
Revenue is Different
- As E-Commerce Lift Persists, Re-
Formulated Mix is Required
- If Behaviors Shift back to In-Store
(Vaccine?), Mix Can Shift Again
- Most Important: The Shifts Have Been
Detected & Measured and are now
actionable
Incremental Marketing Impacts by Sales Channel:
Placeholder- client example (using 2 year window versus pandemic window)
14
Placeholder- client example (using 2 year window versus pandemic window)
15
BEST PRACTICES FROM THE FRONT LINES:
ADOPT ANALYTIC SPRINTS NOW
What are Analytic Sprints?
Adopt
Analytic Sprints
1 Faster/ Frequent
Measurement
Refreshes- AKA
“Sprints”
2 Designating an “MVP”
With Each Sprint
3 Embrace Ongoing
Agile Methodology
Use Agile Methodology
to Drive Measurement
Adoption, Change
Management
Embracing Agile is Key to Enduring Recovery Era Success
18
1 Faster Measurement Refreshes Continually Adapt &
Adjust to Most Current Pandemic Recovery Swings
2 Agile Analytic Sprints Uncover Opportunities Before
Competitors
3 Moving to Agile Creates Sustainable Information
Advantage & Drives Cultural Change
Q&A
19
Thank You!
Interested in Learning More?
Contact OptiMine:
Or visit us at www.optimine.com
20
