Tesla

The Essence

Creating a data-driven customer acquisition strategy for 5 key markets: San Diego, Houston, Chicago, Cleveland, and Philadelphia.

Type

Contract Project through NextGen Consulting

Jan 2024 - May 2024

Ingredients

Tools Microsoft Excel, Python, Pandas, Matplotlib, Google Suite

Skills Data-Driven Decision Making, Data Visualization & Analysis, Competitive Analysis

Infusion

Role Project Manager

Team 2 Project Managers, 5 Analysts

Duration 4 months

What I Worked on

I led a team of 5 analysts in developing a customer acquisition roadmap for Tesla, refining the project scope to align with stakeholder needs. I structured a realistic 4 month project timeline, breaking down tasks by skills and deliverables. I guided analysts in creating customer profiles, conducting competitor research, and using data analytics (Python, Excel, Jupyter Hub) to extract key insights. We built targeted acquisition strategies for Tesla across 5 major U.S. markets (designated marketing areas - DMAs). I managed weekly client check-ins, iterated on findings, and presented an 80+ page industry report and 40+ slide deck at Tesla HQ to their Growth & Strategy Team. My work focused on user segmentation, UX strategy, and data-driven decision-making to optimize Tesla’s market expansion.

Problem

Tesla wanted to increase market share in key United States regions but lacked granular insights on customer behavior, competitor positioning, and effective local strategies. They needed a data-driven approach to identify, and then target underleveraged customer segments, improve product positioning, and refine acquisition strategies.

Solution

We analyzed customer data, competitor strategies, and market trends to create a segmentation-driven acquisition roadmap. Using data analytics and UX research principles, we developed targeted strategies per region, focusing on localized marketing, incentives, and engagement tactics to improve Tesla’s customer reach and conversions.

Process

Setting the Vision

Scope Refinement

When we received the initial project scope, my co-PM and I revised it and worked with our Tesla contact to finalize a structured plan for our four-month timeline. We went back and forth multiple times to ensure the final goal was clear, achievable, and aligned with both Tesla’s needs and our team’s capabilities.

From there, we broke the project down by skills and action items, maintaining flexibility for adjustments as our research evolved. This approach helped us identify which aspects of the scope aligned best with each analyst’s strengths, ensuring an efficient and well-coordinated execution.

Project Timeline

With a clear project vision, I developed a week-by-week timeline for both the midterm report and final slide deck. This structure ensured we had enough time for client check-ins, team reviews, and adjustments as needed. I built flexibility into the schedule, allowing us to track progress and refine content while staying on track for key deadlines. Once the plan was set, we got to work right away!

Background Research

Mosaic Groups

Our work refers to the mosaic groups as defined by the Experian dictionary provided by our client. Groups you will see often in our research are: Power Elite, Booming with Confidence, Flourishing Families, Suburban Style, and Significant Singles.

Designated Marketing Areas

Our client wanted us to research 5 key designated marketing areas (DMAs): Houston, San Diego, Philadelphia, Chicago, and Cleveland.

These were the key insights from our Macro DMA Level Analysis

Customer Profiles per DMA

To complete our background research and better understand our customers, we guided our analysts in creating customer profiles, similar to user personas in the UX process. These profiles helped us visualize key customer segments, their behaviors, and motivations, ensuring our acquisition strategies were data-driven and targeted.

Here’s an example of a profile from Chicago:

Competitive Analysis

Finally, to get a better understanding of the current market landscape, we conducted a competitor deep-dive on Honda, Kia, Ford, Hyundai, and Toyota, analyzing brand positioning, product differentiation, and consumer perceptions & pain points.

Data Analysis

Aim

To understand Tesla’s market performance and customer segmentation, we leveraged data analytics tools (Python, Pandas, Excel, Jupyter Hub) to clean, analyze, and visualize key insights from the dataset provided by Tesla.

Initial Data Processing

We received a dataset on Model Y’s performance across different Designated Market Areas (DMAs), categorized by customer behaviors (mosaic groups). After cleaning the data with Python and Pandas, we prepared summary statistics as a baseline to measure Tesla’s nationwide market presence.

Data Visualization

Using data visualization tools, we generated graphs to highlight for every DMA. These insights were compiled into a data pack, making complex information more accessible and actionable for stakeholders:

  • Customer behaviors – Which segments are currently engaged and which are underrepresented.

  • Market opportunities – Identifying regions where Tesla can expand its reach.

  • Regional differences – Understanding how factors like income, infrastructure, and brand perception impact adoption rates.

Customer Segmentation

Acquisition Strategy Roadmap

At a high level overview:

  1. Awareness → Consideration → Decision

    • A marketing funnel approach similar to UX journey mapping, guiding customers through the buying process.

  2. Product Positioning by Region

    • Tailoring Tesla’s messaging and engagement tactics based on customer demographics and relevant competitor presence.

  3. Customer Engagement Initiatives (Region specific)

    • Tech Event Sponsorships (San Diego & Houston) – Aligning with Tesla’s innovation-driven brand image.

    • Incentives for First-Time EV Buyers (Cleveland & Chicago) – Addressing affordability and adoption barriers.

    • Localized Messaging (Philadelphia) – Enhancing accessibility and engagement in high-potential markets.

Final Recommendation

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Reflection

Defining a Vision

As a PM, I learned how to define a project vision and work with my client to refine it, ensuring it met both short and long-term needs. I took ownership of the entire end to end process—from research to the final deliverable.

Next Steps

Leading With My Skills

Leading a team taught me the value of providing the right resources and support, which helped me grow as well. My background in UX design thinking and empathy helped me better understand customer segments and refine strategies.

Team Dynamic

One of the most rewarding parts of my role, was seeing my analysts come into meetings full of energy, always pushing each other to dig deeper. My job was fostering a fun, engaging, and collaborative work culture.

Where I Take My Career Next

This project gave me hands-on experience in user research, data-driven decision-making, and strategic design thinking, all of which are essential in UX and product design. By creating customer personas, analyzing behaviors, and refining acquisition strategies, I learned how to translate data into actionable insights that improve user experience. Leading the project also strengthened my ability to collaborate cross-functionally, iterate on feedback, and balance execution with long-term strategy. It reinforced the importance of understanding user needs and market trends to create effective, user-centered solutions—a skill set I’ll carry forward in my career as a UX/Product Designer.