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Candidate Exercise — Pair Programming

What this session is

This is a collaborative pair-programming exercise in Python (~60 minutes). You'll work through it with one of our team members — treat them as a teammate, not an examiner. We're far more interested in how you reason about an open-ended problem and how you work with someone else than in whether you produce perfect or complete code. There's no single right answer, and you are not expected to finish everything.

What you're working with

We'll share some starter code with three tables dumped as csv's. They were exported from different systems.

Hagerty serves members across several lines of business: specialty insurance, an online marketplace, the Hagerty Drivers Club membership (HDC, which includes the magazine), and live events (such as the Amelia concours). A customer might touch just one of these or several over time. Marketing wants to understand which acquisition channels bring in customers who go on to become paying customers, so they can decide where to invest next.

customers

column description
customer_id customer identifier
account_created_date when the account was first created
acquisition_channel how they were acquired (e.g. organic, paid_search, social, agent, referral)
signup_product the line of business they first showed interest in
state customer's state

transactions

column description
customer_id customer identifier
transaction_date date of the transaction
product_line insurance, marketplace, hdc_membership, or events
transaction_type e.g. payment, refund
amount dollar amount

A note on amount: for most lines this is what the customer paid. For marketplace transactions, amount is the full vehicle sale price — Hagerty's revenue on a marketplace sale is 7% of that, not the whole amount.

customer_attributes

column description
customer_id customer identifier
vehicle_count number of vehicles on file
top_vehicle_value value of the customer's most valuable vehicle (USD)
vehicle_category e.g. classic, muscle, exotic, modern_collectible, truck_suv
age_band customer age band

The task

To start: which acquisition channels bring in the customers most likely to become profitable paying customers? Feel free to ask about anything that's unclear, and tell us about any assumptions you're making along the way.

Tools

Use whatever you'd normally use, including AI assistants (Copilot, Claude, ChatGPT, etc.) and web search. We use these tools day to day and want to see how you work realistically. The only thing we ask is that you stay able to explain and build on whatever ends up on the screen — your teammate will be curious about the choices being made.

Talking through your thinking as you work makes this much more useful for both of us.

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