Catalina Inside the Big Brains of Data

Dan

Ron

Paul

Dr. Wes Chaar

Bonnie

Adam

Alice

Aaron

Peter

Name: Dan Cropsey, Senior VP, head of Data Strategy, Solutions & Partnerships Role: Data Solutionist People Call Me: Energetic Favorite Data Phrase: Explanatory variables tell you what’s happening and how we can help. Fun Fact: Packer fan living in Bears country.

Name: Ron Menich, VP of Advanced Analytics and Data Science Role: Operations Analyst People Call Me: Intense Favorite Data Phrase: Reinforcement Learning is a rapidly growing area of artificial intelligence that learns from rewards and punishments how to improve performance. Fun Fact: I record my weight every morning on a Google spreadsheet and track the mean estimate over time.

Name: Paul Flugel, VP of Marketing Performance & Brand Analytics Role: Performance Measurer People Call Me: Unflappable Favorite Data Phrase: If you can’t explain it simply, you don’t understand it at all Fun Fact: I taught physics in sign language at the National Institute of the Deaf.

Name: Wes Chaar, Chief Data & Analytics Officer Role: Data Analytics Visionary People Call Me: Provocateur Favorite Data Phrase: Stochastic – the randomness in the world, systems and processes – made me want to understand how to predict outcomes and make decisions in uncertain environments. Fun Fact: I’m tri-lingual.

MODERATOR

Name: Bonnie Garrison, VP of Business Intelligence and Systems Analytics Role: Connector (better word?) People Call Me: Awkward Favorite Data Phrase: The Greek letter Mu – everything reverts to the mean. Fun Fact: I went all the way through grad school with all As except for a B in handwriting in the 4th grade.

Name: Adam Drini, Exec director of Retail Analytics Role: Attribution Analyzer People Call Me: A happy warrior Favorite Data Phrase: A data lake is a vast abyss of information that’s murky and deep and hard to navigate. Fun Fact: I spent four years in Army active duty before going to college and starting my career.

Name: Alice Fang, VP of Retail Analytics Role: Retail Analyst People Call Me: Efficient Favorite Data Phrase: Incrementality is the most important decision metric for measuring data efficiency Fun Fact: I love Zumba!

Name: Aaron Augustine, Exec Director of Analytics Architecture Role: Analytics & Technology Bridge Builder People Call Me: Switzerland (I don’t take sides) Favorite Data Phrase: Data flow – making insights and analytics repeatable. Fun Fact: I’m a triplet. Alt. I’m older than I look.

Name: Peter Williams, VP of Data Fusion, Integration & Solutions Role: Data Fusionist People Call Me: Persistent Favorite Data Phrase: Asymptotics is the study of how to estimate when you’re unconstrainted by your ability to collect data. Fun Fact: I speak Mongolian.

Meet Catalina’s Nerd Squad

There have never been more ways to gather data about shopper behavior. But it’s nearly useless without the ability to rapidly turn that data into actionable insights that empower retailers to deliver truly relevant shopping experiences. That’s where artificial intelligence meets human intelligence. At Catalina, an ensemble cast of industry vets and rising stars affectionately known as the Nerd Squad bring those together to push shopper marketing to the next level. The Nerds write the algorithms that crunch the data and analyze the outputs for many of the world’s retailers and brands.

How can retailers and brands create a more personalized experience for every shopper?

Begin with the shopper’s POV and ask: What do they want?

What makes today’s shopper data more powerful?

NERD SQUAD Checklist

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Alice FANG, retail analytics

Dan CROPSEY, data strategy and solutions

Shoppers will reward the brands and retailers that save them time and provide relevance via personalized assortments and marketing.

To find out what’s inside these big brains, Dr. Wes Chaar, Chief Data & Analytics Officer at Catalina, recently hosted a roundtable with members of his nerd squad. They revealed some important insights on what’s driving effective media, advancements for improving personalization, and the best way to maximize data for business growth.

Dr. Chaar:

1. Think in terms of insight, segmentation, predictive analytics and measurement. 2. Use UPC-level consumer purchase data to meet them at their moment of inspiration. 3. Implement a contact strategy to deliver relevant messages and creative at the right time to drive engagement and response. 4. Assess and optimize your content across channels in real-time - instead of post-campaign.

Dr. Chaar:

Peter WILLIAMS data fusion and integration

What we know about shoppers is much more cohesive. Think about Spotify. Three years ago, they could recommend three to five songs and get it mostly right. Now they layer in recent releases within subcategories to create an unexpectedly meaningful listener experience. Today, we can layer on granular insights to deliver far more precise promotions to shoppers based on their behaviors and motivations - whether someone avoids GMOs, favors low-carb or prefers eco-friendly ingredients – and it can be done at scale.

More information leads to more refinement and sub-segments. We can find that shopper who’s on a Paleo diet and uses online sports media.

Adam DRINI digital analytics

MEET ALICE

The Nerd Squad Navigates What’s Top of Mind in Retail

Inside the Big Brains of Big Data

Paul

How do today’s buyer profiles supersede demographics?

Dr. Chaar:

How will micro-marketing impact engagement strategies?

Dr. Chaar:

How will data fusion reshape the customer journey?

Dr. Chaar:

How can retailers and brands more directly link spending to performance?

Dr. Chaar:

Bonnie

Dan

Peter

Wes

Ron

Adam

Alice

Aaron

Incrementality: The most important decision metric for measuring data efficiency.

MEET DAN

Data Strategy: Getting all the data ingredients to work together to understand and influence a shopper’s behavior.

Advanced Analytics and Data Science Using open source machine learning and cloud computing technology to process data that answers the questions: “Why did it happen?”, “What will happen?”, and “What should happen? Analytics Architecture The mission of the Analytics Architecture team is to enable analytics at scale. We do this by making sure the Analytics and Data Science teams have the necessary Cloud infrastructure, tools and data to execute research and development of machine learning/AI models at scale. Asymptotics The study of how to estimate when you’re unconstrained by your ability to collect data. Data Flow Making insights and analytics repeatable. Data Fusion A set of mathematical and statistical methodologies that helps you tackle challenging business problems that can’t be solved with one data source or view of consumer behavior. Data Lake A vast abyss of information that’s murky and deep and hard to navigate. Data Solutions Technology, software, systems, and algorithms that make it easier to store, access, analyze and commercialize data. Data Strategy Getting all the data ingredients to work together to understand and influence a shopper’s behavior. Explanatory variables Using data to put what’s happening into perspective. ID Mapping Connecting a shopper’s loyalty card IDs to their digital devices so you can precisely reach your ideal targets. Incrementality The most important decision metric for measuring data efficiency. Marketing performance Using data to measure and improve how well brand campaigns work for you. Reinforcement Learning A rapidly growing area of artificial intelligence that learns from rewards and punishments how to improve performance. Stochasticity The quality of randomness in the world.

GLOSSARY

MEET PETER

Asymptotics: The study of how to estimate when you’re unconstrainted by your ability to collect data.

Name: Peter Williams VP of Data Fusion, Integration & Solutions Role: Data Fusionist People Call me: Persistent Favorite Data Word: Asymptotics is the study of how to estimate when you’re unconstrained by your ability to collect data. Fun Fact: I speak Mongolian.

Data Fusion: A set of mathematical and statistical methodologies that helps you tackle challenging business problems that can’t be solved with one data source or view of consumer behavior.

Name: Adam Drini Exec director of Retail Analytics Role: Attribution Analyzer People call me: A happy warrior Favorite data phrase: A data lake is a vast abyss of information that’s murky and deep and hard to navigate. Fun Fact: I spent four years in Army active duty before going to college and starting my career.

Data Lake : A vast abyss of information that’s murky and deep and hard to navigate.

MEET ADAM

Buyer profiles give brands and retailers a way to listen to customers through the data, finding patterns that identify what an individual is buying – and why – to drive purchases. Data can uncover a shopper’s switch from a Whole 30 to a plant-based diet, so offers continue to resonate as lifestyles shift.

Bonnie GARRISON business intelligence and systems analytics

Buyer profiles help to clean up age-old muddy data questions. Technology has demonstrated that my 20-year-old son and I share the same purchase behavior with certain products. That distinction would be lost with a demographic-only view.

Alice FANG retail analytics

Name: Bonnie Garrison VP of Business Intelligence and Systems Analytics Role: Connector People Call Me: Awkward Favorite Data Word: The Greek letter Mu – everything reverts to the mean. Fun Fact: I went all the way through grad school with all As except for a B in handwriting in the 4th grade.

MEET BONNIE

The good news is that mass personalization and optimization will be able to adjust marketing content and touchpoints in near real time at scale based on individual behavior, marketing goals and budgets.

Dan CROPSEY data strategy and solutions

Data Strategy: Getting all the data ingredients to work together to understand and influence a shopper’s behavior.

Name: Ron Menich VP of Advanced Analytics and Data Science Role: Operations Analyst People call me: Intense Favorite Data Phrase: Reinforcement Learning is a rapidly growing area of artificial intelligence that learns from rewards and punishments how to improve performance. Fun Fact: I record my weight every morning on a Google spreadsheet and track the mean estimate over time.

MEET RON

Advanced Analytics and Data Science: Using open source machine learning and cloud computing technology to process data that answers the questions: “Why did it happen?”, “What will happen?”, and “What should happen?

Data Fusion: A set of mathematical and statistical methodologies that helps you tackle challenging business problems that can’t be solved with one data source or view of consumer behavior.

Fusing data creates a more holistic view of the consumer. Through Catalina’s ID Graph, we can link information across vendors through households.

Aaron AUGUSTINE analytics architecture

Data fusion enables more precise and personalized insights at greater scale to deliver a more relevant message through the optimal channel, time, day and format.

Adam DRINI digital analytics

As we build new capabilities and layer in new data across media channels and measurement, we can lean into data fusion to extend insights to broader consumer groups – or even at the national level. It is a key part of our machine learning toolkit to grow our data and create holistic insights that improve the shopper experience and the efficiency for retailers and brands.

Peter WILLIAMS data fusion and integration

Name: Aaron Augustine Exec Director of Analytics Architecture Role: Analytics & Technology Bridge Builder People Call Me: Switzerland (I don’t take sides) Favorite Data Phrase: Data flow – making insights and analytics repeatable. Fun Fact: I’m a triplet.

Data Flow: Making insights and analytics repeatable.

MEET AARON

ID Mapping: Connecting a shopper’s loyalty card IDs to their digital devices so you can precisely reach your ideal targets.

Analytics Architecture: The mission of the Analytics Architecture team is to enable analytics at scale. We do this by making sure the Analytics and Data Science teams have the necessary Cloud infrastructure, tools and data to execute research and development of machine learning/AI models at scale.

Today, we are focused on creating outcome-based data solutions that link media from traditional channels like print and TV, the digital ad ecosystem, and what consumers purchase. This means retailers and CPGs will be able to demand guaranteed performance from their ad spend.

Peter WILLIAMS, Data fusion and integration

Data Solutions: Technology, software, systems, and algorithms that make it easier to store, access, analyze and commercialize data.

I agree there will be a shift from pay-for-delivery to pay-for-performance.

Adam DRINI digital analytics

By shifting to a consumer mix model (CMM) that focuses on consumer purchase habits, we can capture each media exposure, CPG activation, and purchase for a consumer. That means we can layer in new levels of precision in measurement. Analyzing purchase data in the context of consumer mix inherently leads to richer insights on loyalty, targeting and ROI precision.

Wes CHAAR Chief Data & Analytics Officer

MEET WES

Name: Wes Chaar Chief Data & Analytics Officer Role: Data Analytics Visionary People Call Me: Provocateur Favorite Data Word: Stochastic – the randomness in the world, systems and processes – made me want to understand how to predict outcomes and make decisions in uncertain environments. Fun Fact: I’m tri-lingual.

Stochasticity: The quality of randomness in the world

Expert advice for brands and retailers:

Name: Paul Flugel VP of Marketing Performance & Brand Analytics Role: Performance Measurer People Call Me: Unflappable Favorite Data Phrase: If you can’t explain it simply, you don’t understand it at all. Fun Fact: I taught physics in sign language at the National Institute of the Deaf.

MEET PAUL

Marketing performance: Using data to measure and improve how well brand campaigns work for you.

Paul FLUGEL marketing performance and analytics

Shoppers demand simplicity and frictionless buying. The way they are buying is changing across industries, but the one common thread is ease of the experience, that puts the shopper in control of the experience they have.

Scroll down or jump to a topic:

Personalizing shopper experiences Shopper data Buyer profiles vs. demographics Micromarketing Data fusion & the customer journey Spending linked to performance NERD SQUAD checklist Contact Us Glossary

Nerds on Your Side

ABOUT CATALINA'S DATA

CONSUMER PRIVACY

Catalina’s team of 125+ analytics and data science professionals, affectionately referred to as the “Nerds on Your Side”, are experts in their field and passionate about what they do.

Nerds on Your Side

Consumer privacy is critical to Catalina and its customers, so the company invests in data experts and partners who share our commitment to the letter - and spirit - of privacy laws.

CONSUMER PRIVACY

Catalina sits squarely at the intersection of big data and big brains. Securely maintaining enormous data lakes containing point-of-sale basket data comprising over 1.4 trillion rows of data, captured through $398 billion in annual transactions, from 500 million consumer IDs around the world, Catalina’s shopper intelligence is second to none.

ABOUT CATALINA'S DATA

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Apply granular, real-time insights for a personalized shopping experience

Layer on behavior-based insights for more precise promotions

Leverage buyer profiles to tell you the WHAT and the WHY

Use micro-marketing strategies to improve relevancy in real-time

Go deeper via data fusion

Work toward paying for performance rather than delivery

Select and click on a nerd for a complete bio

Please contact us for more information.

Micro-marketing engages shoppers based on their needs and wants, delivering the most relevant media at the right time in the right channel. Each micro-market segment will likely respond differently to messages or offers.

Ron MENICH advanced analytics