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Today’s Timeline
11:45am – 12:30pm PST
Unlock Your Brand’s Maximum Potential with
Data Analytics
TINUITI & TABLEAU
PRESENTS:
How To Unify Data with
Bespoke Dashboards for True
Insights
1:15pm – 2:00pm PST
TINUITI & SNOWFLAKE
PRESENTS:
Actionable Steps to Increase
CLV Across Your Integrated
Media Strategy
TINUITI & OBSERVEPOINT
PRESENTS:
Build a Foundation for Data
Integrity with Analytics Auditing
TINUITI & DATAROBOT
PRESENTS:
Leveraging Media Mix
Modeling to Drive Performance
Marketing Results
July, 2020
Leveraging Media Mix Modeling to Drive
Performance Marketing Results
Unlock Your Brand’s Maximum Potential with Data Analytics
● Session recording and slides will be sent out
● Log back in anytime with the same link
● Resources available as handouts
Eyebrow Text
Today’s Logistics
Persephanie Arellano
Webinar Coordinator
Today’s Speakers
Megan Caputo
Director of Integrated Media
Vijay Rajan
Data Scientist
Annica Nesty
Senior Director of Analytics &
Marketing Science
5
1. What is media mix modeling?
2. Why it’s a key tool in strategic media planning?
3. How DataRobot can be used to unlock the power of your
data to drive media performance results?
Agenda
Poll Question
Which channels are you currently
investing most in?
● Paid Search
● Paid Social
● Shopping
● Display
● Affiliate
Defining media mix modeling and performance
strategy
8
What is Media Mix Modeling?
Evaluates past marketing performance to measure how media channels drives sales to determine “true”
marketing ROI and optimal mix of media activity
Media Activity
(Paid search,
Social etc...)
Promotions
(Consumer
promotions etc..)
Economic
Conditions
(Unemployment
rate, Consumer
Price Index etc..)
Sales Units or
Sales Revenue
Other Factors
(New product
launch,
Competitor, Price)
2-5 years of historical data
● At least 5 years of monthly data
-OR-
● At least 2 years of weekly or daily
data
Review and assess historical
performance
Evaluate current marketing
initiatives
Optimize spend across media
channels
Mobius - Data
Requirements
Mobius - Model Requirements
Target Model Drivers
Future forecasts What if analysis Ongoing evaluation
Media Mix Model
9
Things We Hear from Clients:
● How should we be allocating our total advertising budget to reach X ROI?
● How should we be adapting our budget allocation strategy based on COVID/X
macroeconomic trend?
● What media investment is needed for a 30% YoY revenue increase?
What We Offer:
A research project and analysis that breaks down which percentage of your marketing
budget should be going to which channels, using historical data to predict future ROI
Why is This Important?
Few marketers have the right data sources and framework to analyze their Marketing
spend across all channels and determine the right budget allocation strategy. Even fewer
have the ability to factor in economic conditions, competitors, the weather etc to ensure
the highest level of modeling accuracy. A precise media mix model will use your past data
to inform future ROI and investment strategy.
What Analytics Team Would Prescribe: Media Mix Model
Budget Allocation Strategy
10
Things We Hear from Clients:
● Our board/exec team is asking for a forecast on Marketing’s impact on
revenue for the second half of the year/2021
● How will the recession/COVID-19/competitor spending trends impact our
future revenue?
What We Offer:
A research project that breaks down predicted future values of data series such as
sales volumes, revenue, new customers etc. Optional to include other 3rd party
data sources like S&P 500 trends, Consumer Confidence Index, Unemployment
rate, Kantar spend data, etc to further refine the forecast
Why is This Important?
Every business needs an accurate picture of future revenue and customer
acquisition/retention -- insight required for Marketing leaders to unlock more
efficient planning and resource allocation. Using your historical performance data,
we build precise forecasting models that can incorporate seasonality, business
changes, and macroeconomic conditions.
Solution: Forecasting (Basic & Advanced)
Poor Data Visibility & Actionability
11
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Highlights:
● Leveraging client data, marketing data, and machine
learning to address the following business questions:
○ What is the impact across digital channels?
○ What is the right mix of spend allocation that
drives the highest ROI?
○ How will the channels perform in the future based
on their optimized spend allocation?
○ What media investment is needed for a 30% YoY
revenue increase?
Background:
In order to predict a second-half of the year forecast and optimal
media mix and with a desire to make their marketing dollars
work smarter, an international ecommerce brand engaged Tinuiti
to develop a proprietary Media Mix Model along with a daily
forecast to maximize sales and revenue using Mobius.
Img Source: Unsplash
12
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Strategy:
In order to help our client achieve their goals, Tinuiti first
deployed Media Mix Modeling, a proprietary solution developed
in Mobius to help our client maximize their spend across their
digital marketing channels. This solution took into account the
last 2 years of digital marketing and revenue data, analyzing it by
market, tactic, and by day over this time period.
The client was mainly interested in understanding the optimal
spend levels for paid search, paid social, display, shopping (PLA),
and affiliate. In addition, our client asked Tinuiti to incorporate
organic search, direct traffic, referral traffic, and email traffic to
the forecast.
The data Tinuiti collected and analyzed in Mobius was used to
create models for future spend showing how changes in
investment across channels could impact revenue and sales.
Img Source: Unsplash
How we assess and quantify media effectiveness?
14
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Additional Elements that may be incorporated into the Mobius
models*:
● Pathmatics competitive spend trends (display, social)
● Kantar competitive spend trends (search/shopping, offline
media, broadcast, etc.)
● Financial Indicators
○ S&P 500 trends
○ Volatility Index
● Google Query (Trends) volume
● Macroeconomic Indicators
○ Consumer Confidence Index
○ Consumer Sentiment Index
○ Business Confidence Index
○ Unemployment Rate
● Population Density (where applicable)
● COVID-19 Specific
○ Cases, Deaths, Geography, Mobility Restriction Data
Img Source: Unsplash
*Some variables may increase scope
Media Activity
(Paid search,
Social etc...)
Promotions
(Consumer
promotions etc..)
Economic
Conditions
(Unemployment
rate, Consumer
Price Index etc..)
Sales Units or
Sales Revenue
Other Factors
(New product
launch,
Competitor, Price)
Mobius - Model Requirements
Target Model Drivers
15
Strategic Investment Quadrant
Maintain
OptimizeFix
Scale
MROI
% Sales Revenue
**Size of bubble reflects
share of spend
Data has been blinded
Define Media ROI (MROI) across channels
Identify gains or losses in ROI across channels
MROISpend($K)
Data has been blinded MMM R^ Value: 0.929
17
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Results:
The full digital mix media model gave our client an extremely detailed analysis of where to optimize their spend across all digital
marketing channels. This included shifting dollars away from social, which historically had been at or near 30%, to search
(capturing current demand). An increase in affiliate and decrease in display were also needed to maximize revenue impact.
Data has been blinded MMM R^ Value: 0.929
18
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Results:
As part of the forecasting, after incorporating the ideal mix of media from the MMM, we worked to develop a detailed daily,
weekly and monthly forecast broken down by region all the while creating backtesting and holdout groups to test the validity
of the forecasting models. After optimizing the media mix, we developed ~80 different models bespoke for our client in
order to achieve the most accurate forecast possible. Below are the actual vs. predicted values for one of the channels
Data has been blinded
19
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Additional Information:
Media mix modeling has extreme levels of detail and does
significantly more than show what happened in the past.
The modeling portion of our proprietary MMM allows our
brands to ask “what if”? In this instance, “what media
spend will I need in order to hit a 30% YoY FY20 revenue
goal?”
This media mix model and subsequent forecasting
achieved a ~95% accuracy rate when predicting future
results.
Img Source: Unsplash
20
Media Mix Modeling + Forecasting Case Study
Client: eCommerce Brand
Mobius Impact:
Because of the ideal media model and a highly tuned forecast,
we were able to show the exact media spend needed (by
channel) in order to achieve the 30% YoY revenue goal the
client had targeted.
IMS and channel execution teams leveraged the media model
findings to build robust, data-backed media plans.
Due to the success and accuracy of these models, the client
re-engaged Tinuiti to update and leverage the models to plan
their US and International business for FY21.
Img Source: Unsplash
How we Partner with DataRobot to optimize budget
allocation across the Media Mix to Increase ROI
DataRobot Marketing Mix App Overview
Upload the historical data
To start marketing mix modeling, drop the historical data and the metadata files in MMM app in DataRobot.
Unification of Data Creates a Model (Project)
Based on the historical data, DataRobot builds a number of
models which one can further explore.
Model built on historical data
After the models are created on
historical data, DataRobot
creates visualizations to show
the incremental sales attributed
to each media.
Visualizations to understand the impact on sales by media
Based on the past performance
of the media and other relevant
features in the dataset, now you
can put in your total budget for a
future period and DataRobot
MMM app will efficiently allocate
that budget in different channels
that will help you optimize sales.
Optimization of future budget allocation
Optimization For Future Budget Allocation
The output is available in a
downloadable format for easy
post-modeling consumption.
The Output is available in a downloadable format
Key Takeaways
Media Mix Modeling quantifies media effectiveness
Data driven approach to optimize media mix and determine
future budget allocation
Media Mix Modeling uncovers insights to inform media
strategy and drive performance marketing results
29
Tinuiti’s Mobius Suite
UNIFY
Connects, collects, and
synthesizes your data in
one place, with
visualization, integrations,
and reporting that makes
your insights easy to
understand and act on.
Think of it as the operating
system where all of your
data lives.
OPTIMIZE
Work within MobiusOS to
provide targeted analytics
products that allow us to
enhance and customize
the way your data is
analyzed to uncover
growth opportunities with
cutting-edge insights. We
can even create bespoke
apps, just for you.
ACTIVATE
Our powerful AI-enabled
eCommerce activation tool
set that uses product data
as the foundation on which
your media, bid, and feed
strategies are optimized
across campaigns for
maxim profitability.
Schedule an analytics consultation
Live Q&A
Megan Caputo
Director of Integrated Media
Vijay Rajan
Data Scientist
Annica Nesty
Senior Director of Analytics &
Marketing Science
THANK YOU!

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Leveraging Media Mix Modeling to Drive Performance Marketing Results

  • 1. 11:00 – 11:45am PST 12:30 – 1:15pm PST Today’s Timeline 11:45am – 12:30pm PST Unlock Your Brand’s Maximum Potential with Data Analytics TINUITI & TABLEAU PRESENTS: How To Unify Data with Bespoke Dashboards for True Insights 1:15pm – 2:00pm PST TINUITI & SNOWFLAKE PRESENTS: Actionable Steps to Increase CLV Across Your Integrated Media Strategy TINUITI & OBSERVEPOINT PRESENTS: Build a Foundation for Data Integrity with Analytics Auditing TINUITI & DATAROBOT PRESENTS: Leveraging Media Mix Modeling to Drive Performance Marketing Results
  • 2. July, 2020 Leveraging Media Mix Modeling to Drive Performance Marketing Results Unlock Your Brand’s Maximum Potential with Data Analytics
  • 3. ● Session recording and slides will be sent out ● Log back in anytime with the same link ● Resources available as handouts Eyebrow Text Today’s Logistics Persephanie Arellano Webinar Coordinator
  • 4. Today’s Speakers Megan Caputo Director of Integrated Media Vijay Rajan Data Scientist Annica Nesty Senior Director of Analytics & Marketing Science
  • 5. 5 1. What is media mix modeling? 2. Why it’s a key tool in strategic media planning? 3. How DataRobot can be used to unlock the power of your data to drive media performance results? Agenda
  • 6. Poll Question Which channels are you currently investing most in? ● Paid Search ● Paid Social ● Shopping ● Display ● Affiliate
  • 7. Defining media mix modeling and performance strategy
  • 8. 8 What is Media Mix Modeling? Evaluates past marketing performance to measure how media channels drives sales to determine “true” marketing ROI and optimal mix of media activity Media Activity (Paid search, Social etc...) Promotions (Consumer promotions etc..) Economic Conditions (Unemployment rate, Consumer Price Index etc..) Sales Units or Sales Revenue Other Factors (New product launch, Competitor, Price) 2-5 years of historical data ● At least 5 years of monthly data -OR- ● At least 2 years of weekly or daily data Review and assess historical performance Evaluate current marketing initiatives Optimize spend across media channels Mobius - Data Requirements Mobius - Model Requirements Target Model Drivers Future forecasts What if analysis Ongoing evaluation Media Mix Model
  • 9. 9 Things We Hear from Clients: ● How should we be allocating our total advertising budget to reach X ROI? ● How should we be adapting our budget allocation strategy based on COVID/X macroeconomic trend? ● What media investment is needed for a 30% YoY revenue increase? What We Offer: A research project and analysis that breaks down which percentage of your marketing budget should be going to which channels, using historical data to predict future ROI Why is This Important? Few marketers have the right data sources and framework to analyze their Marketing spend across all channels and determine the right budget allocation strategy. Even fewer have the ability to factor in economic conditions, competitors, the weather etc to ensure the highest level of modeling accuracy. A precise media mix model will use your past data to inform future ROI and investment strategy. What Analytics Team Would Prescribe: Media Mix Model Budget Allocation Strategy
  • 10. 10 Things We Hear from Clients: ● Our board/exec team is asking for a forecast on Marketing’s impact on revenue for the second half of the year/2021 ● How will the recession/COVID-19/competitor spending trends impact our future revenue? What We Offer: A research project that breaks down predicted future values of data series such as sales volumes, revenue, new customers etc. Optional to include other 3rd party data sources like S&P 500 trends, Consumer Confidence Index, Unemployment rate, Kantar spend data, etc to further refine the forecast Why is This Important? Every business needs an accurate picture of future revenue and customer acquisition/retention -- insight required for Marketing leaders to unlock more efficient planning and resource allocation. Using your historical performance data, we build precise forecasting models that can incorporate seasonality, business changes, and macroeconomic conditions. Solution: Forecasting (Basic & Advanced) Poor Data Visibility & Actionability
  • 11. 11 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Highlights: ● Leveraging client data, marketing data, and machine learning to address the following business questions: ○ What is the impact across digital channels? ○ What is the right mix of spend allocation that drives the highest ROI? ○ How will the channels perform in the future based on their optimized spend allocation? ○ What media investment is needed for a 30% YoY revenue increase? Background: In order to predict a second-half of the year forecast and optimal media mix and with a desire to make their marketing dollars work smarter, an international ecommerce brand engaged Tinuiti to develop a proprietary Media Mix Model along with a daily forecast to maximize sales and revenue using Mobius. Img Source: Unsplash
  • 12. 12 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Strategy: In order to help our client achieve their goals, Tinuiti first deployed Media Mix Modeling, a proprietary solution developed in Mobius to help our client maximize their spend across their digital marketing channels. This solution took into account the last 2 years of digital marketing and revenue data, analyzing it by market, tactic, and by day over this time period. The client was mainly interested in understanding the optimal spend levels for paid search, paid social, display, shopping (PLA), and affiliate. In addition, our client asked Tinuiti to incorporate organic search, direct traffic, referral traffic, and email traffic to the forecast. The data Tinuiti collected and analyzed in Mobius was used to create models for future spend showing how changes in investment across channels could impact revenue and sales. Img Source: Unsplash
  • 13. How we assess and quantify media effectiveness?
  • 14. 14 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Additional Elements that may be incorporated into the Mobius models*: ● Pathmatics competitive spend trends (display, social) ● Kantar competitive spend trends (search/shopping, offline media, broadcast, etc.) ● Financial Indicators ○ S&P 500 trends ○ Volatility Index ● Google Query (Trends) volume ● Macroeconomic Indicators ○ Consumer Confidence Index ○ Consumer Sentiment Index ○ Business Confidence Index ○ Unemployment Rate ● Population Density (where applicable) ● COVID-19 Specific ○ Cases, Deaths, Geography, Mobility Restriction Data Img Source: Unsplash *Some variables may increase scope Media Activity (Paid search, Social etc...) Promotions (Consumer promotions etc..) Economic Conditions (Unemployment rate, Consumer Price Index etc..) Sales Units or Sales Revenue Other Factors (New product launch, Competitor, Price) Mobius - Model Requirements Target Model Drivers
  • 15. 15 Strategic Investment Quadrant Maintain OptimizeFix Scale MROI % Sales Revenue **Size of bubble reflects share of spend Data has been blinded
  • 16. Define Media ROI (MROI) across channels Identify gains or losses in ROI across channels MROISpend($K) Data has been blinded MMM R^ Value: 0.929
  • 17. 17 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Results: The full digital mix media model gave our client an extremely detailed analysis of where to optimize their spend across all digital marketing channels. This included shifting dollars away from social, which historically had been at or near 30%, to search (capturing current demand). An increase in affiliate and decrease in display were also needed to maximize revenue impact. Data has been blinded MMM R^ Value: 0.929
  • 18. 18 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Results: As part of the forecasting, after incorporating the ideal mix of media from the MMM, we worked to develop a detailed daily, weekly and monthly forecast broken down by region all the while creating backtesting and holdout groups to test the validity of the forecasting models. After optimizing the media mix, we developed ~80 different models bespoke for our client in order to achieve the most accurate forecast possible. Below are the actual vs. predicted values for one of the channels Data has been blinded
  • 19. 19 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Additional Information: Media mix modeling has extreme levels of detail and does significantly more than show what happened in the past. The modeling portion of our proprietary MMM allows our brands to ask “what if”? In this instance, “what media spend will I need in order to hit a 30% YoY FY20 revenue goal?” This media mix model and subsequent forecasting achieved a ~95% accuracy rate when predicting future results. Img Source: Unsplash
  • 20. 20 Media Mix Modeling + Forecasting Case Study Client: eCommerce Brand Mobius Impact: Because of the ideal media model and a highly tuned forecast, we were able to show the exact media spend needed (by channel) in order to achieve the 30% YoY revenue goal the client had targeted. IMS and channel execution teams leveraged the media model findings to build robust, data-backed media plans. Due to the success and accuracy of these models, the client re-engaged Tinuiti to update and leverage the models to plan their US and International business for FY21. Img Source: Unsplash
  • 21. How we Partner with DataRobot to optimize budget allocation across the Media Mix to Increase ROI
  • 22. DataRobot Marketing Mix App Overview Upload the historical data To start marketing mix modeling, drop the historical data and the metadata files in MMM app in DataRobot.
  • 23. Unification of Data Creates a Model (Project)
  • 24. Based on the historical data, DataRobot builds a number of models which one can further explore. Model built on historical data
  • 25. After the models are created on historical data, DataRobot creates visualizations to show the incremental sales attributed to each media. Visualizations to understand the impact on sales by media
  • 26. Based on the past performance of the media and other relevant features in the dataset, now you can put in your total budget for a future period and DataRobot MMM app will efficiently allocate that budget in different channels that will help you optimize sales. Optimization of future budget allocation Optimization For Future Budget Allocation
  • 27. The output is available in a downloadable format for easy post-modeling consumption. The Output is available in a downloadable format
  • 28. Key Takeaways Media Mix Modeling quantifies media effectiveness Data driven approach to optimize media mix and determine future budget allocation Media Mix Modeling uncovers insights to inform media strategy and drive performance marketing results
  • 29. 29 Tinuiti’s Mobius Suite UNIFY Connects, collects, and synthesizes your data in one place, with visualization, integrations, and reporting that makes your insights easy to understand and act on. Think of it as the operating system where all of your data lives. OPTIMIZE Work within MobiusOS to provide targeted analytics products that allow us to enhance and customize the way your data is analyzed to uncover growth opportunities with cutting-edge insights. We can even create bespoke apps, just for you. ACTIVATE Our powerful AI-enabled eCommerce activation tool set that uses product data as the foundation on which your media, bid, and feed strategies are optimized across campaigns for maxim profitability.
  • 30. Schedule an analytics consultation
  • 31. Live Q&A Megan Caputo Director of Integrated Media Vijay Rajan Data Scientist Annica Nesty Senior Director of Analytics & Marketing Science