LISA GIRARD
Marketing Manager
Data Analyst
I am a collaborative team leader with a proven ability to develop and execute dynamic marketing strategies. I skillfully balance customer-centric approaches that foster engagement, adoption, and retention throughout the customer journey, while also driving revenue and conversions through the sales funnel. I apply data analysis to discover potential audiences, identify patterns and characteristics in existing audiences, and use descriptive and predictive insights to guide informed marketing decisions.
I still like the oxford comma. Ask me about my Swatch collection.
MARKETING CAMPAIGN PORTFOLIO
March 2023 to present
Accounts: Ford Motor Company (US & CAN) and Enterprise Mobility
Growth Marketing, Loyalty programs, Visa acquisition
- Execute complex data extractions for email audience segmentation from multiple Big Data sources including Hadoop/Hive, Teradata, Google Cloud Platform, Salesforce Marketing Cloud, and Adobe Campaign using Python, SQL, BigQuery, and Excel.
- Revealed 6 new marketing segments with a credit card activation propensity model using unsupervised and supervised machine learning. Predicted 50% of high net promoter scores had cardholder characteristics even though only 2.5% were actual cardholders.
- Identified 4 new segments with machine learning sentiment analysis of text-based survey responses.
- Initiated generativeAI projects for visualizing daily report monitoring, bi-weekly loyalty points reporting, and photo recognition/classification from user-generated content.
- Co-Lead AI Concept Team to strategize and develop in-house generative AI tools and applications.
- Collaborate with cross-functional teams to develop data-driven initiatives and analyses to support customer lifecycle campaign strategy via behavior analyses like point earning and redemption, credit card activation and spending, and email engagement.
DATA PROJECTS
RADIO DATA IN A DIGITAL AGE
Tracking charting history on the Billboard Hot 100 chart
Standard A/B testing examining charting history of power gold hits from the 70s-90s compared to charting history of power gold hits released after 1999. Data analysis focused on if digital music content delivery made a difference in how long songs chart since the launching of Napster in 1999.
Final results and recommendations related to:
- Audience development
- Marketing revenue and generation
- Content distribution
EXAMINING PSYCHEDELICS USE AND MENTAL HEALTH CONDITIONS: knowledge, use, and outcomes
Supervised Machine Learning modeling that examines publically-available raw data about psychedelics use in relation to self-reported mental health and physical health conditions.
Final results and recommendations:
- 67% likelihood of people with certain mental health conditions* using psychedelics
- 85% prediction accuracy of those people with certain mental health conditions* and knowledge of psychedelics-as-therapeutic tool are using psychedelics
- Established connection between education of therapeutic tool and use to alleviate mental health issues
Continued education and research about use of psychedelics to treat mental health conditions will:
- Reduce stigma
- Allow for DEA rescheduling & decriminalization
- Provide more tools for those suffering
- Establish statutory and regulatory policies and practices
- Shorten mental health treatment periods to days or weeks
- Increase research funding and testing
- Change methods, modalities, and mindsets around mental health and treatments options
* conditions considered: moderate-to-severe depression, moderate-to-severe anxiety, chronic pain, migraine, and insomnia. Survey raw data collected Nov 2020-March 2021.
EVALUATING SNOWSPORTS PARTICIPATION DECISION FACTORS
Unsupervised Learning Model
Analyzed decision-making conditions and behaviors when choosing to participate in snowsports at a Norwegian ski resort.
Final results and recommendations related to:
- Discovered 6 distinct clusters of “types of skiers” that were identified by family status, distance from resort, weather preference, age, gender, and more
- Advised Marketing, Operations, and C-Level leaders how to use clusters to implement marketing and management changes
BEHIND THE GOGGLES: UNMASKING SKI RESORT CUSTOMERS
Unsupervised and supervised predictive classification modeling and analysis
Unsupervised clustered machine learning followed by supervised machine learning to predict and identify the resulting customer clusters at a Norwegian ski resort.
Final results and recommendations related to:
- Discovered 4 distinct customer clusters
- Determined what characteristics were in each cluster
- Analyzed cluster targets in regards to ancillary spending, lift ticket pricing, and weather preference
- Provided three (3) business-case uses for each cluster definition
- Advised Marketing, Operations, and C-Level leaders how to use clusters to implement marketing and management changes
Mission
HONE SKILLS AND PROCESSES OF DATA SCIENCE
Explore how data can:
- redefine socio-cultural relationships within media and entertainment
- advance the science, reduce stigma, educate, and propel regulation of psychedelic-assisted therapy
- evolve the alpine ski industry in contexts of climate change, socio-economic barriers, and technology
Latest Reads
READS ABOUT DATA AND CULTURE
- AI Superpowers: China, Silicon Valley and the New World Order. Kai Fu Lee. 2018
- Build A Career in Data Science. Jacqueline Nolis, Emily Robinson. 2020
- Be Data Literate. Jordan Morrow. 2021
- Like, Comment, Subscribe: Inside YouTube’s Chaotic Rise to World Domination. Mark Bergen. 2022
- Meme Wars: The Untold Story of the Online Battles Upending Democracy in America. Joan Donovan, Emily Dreyfuss, Brian Friedberg. 2022
- Survival of the Richest. Douglas Rushkoff. 2022
- Bold. Peter Diamandis, Steven Kotler. 2015.
- How to Change Your Mind. Michael Pollan. 2018
- 1984. George Orwell. 1949
SKILLS
Hard Skills
• EDA | cleaning, wrangling, exploring, feature engineering
• Python / SQL
- Pandas
- numpy
- sklearn
- Seaborn
- matplotlib
• Jupyter Notebook/Google Colab notebooks
• GitHub
• Applied statistical analysis:
- Linear regression
- Logistic regression
- Classification
- Signficance testing
- Supervised learning
- Unsupervised learning
- Modeling
- Observations and recommendations
• A/B Testing
- Variable determination
- Hypothesis formulation
- Applied statistical testing | student’s t-test, ANOVA, Kruskal-Wallis, etc.
- Observations and recommendations
• Story telling | data visualization tools
- Looker Studio (Google Data Studio)
- Google Tag Manager/Google Analytics
- matplotlib
- Tableau (coming soon!)
- Microsoft BI (coming soon!)
- Plotly (coming soon!)
• Big Data | Hadoop, Spark
Transferrable Soft Skills
- 20+ years in digital marketing and communications (strategy development, web design, content creation, email marketing, display advertising, social media, analytics)
- critical thinker
- excellent communication skills
- curious, idea generator, researcher
- problem solver
- high integrity, attention to detail
- growth mindset
- collaborative, respectful, interpretive
- end-user/customer comes first (work from the bottom up)
- risk taker
- tenacious and persistent
CONTACT
email lisaraygirard @ gmail.com
My core values are kindness, compassion, and honesty. I believe in collaboration, transparency, digging in deep, and figuring out the why. Simple is better and the end user leads the way.
There is power in the pause and I choose positivity over negativity.
© 2024 Lisa Girard