Determine Optimal Marketing Budget Allocation for Maximum Profit
Quick Overview
This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Determine Optimal Marketing Budget Allocation for Maximum Profit states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Determine Optimal Marketing Budget Allocation for Maximum Profit
Company: OneMain Financial
Role: Data Scientist
Category: Analytics & Experimentation
Difficulty: medium
Interview Round: Online Assessment
##### Scenario
Onemain Financial must decide how to allocate marketing budget across three acquisition channels—Phone Calls, Social Media Ads, and Email Blasts—whose click-through rates, conversion rates, and revenue-per-cost values are provided in an Excel sheet.
##### Question
Given a total budget B, calculate the expected net profit for each channel. 2. Using the conversion rate, estimate the average cost and the average profit generated by a single inbound phone call. 3. Each channel has an individual spend cap. With a fixed overall budget, determine the spending allocation that maximizes total profit and explain your reasoning.
##### Hints
Compute unit profit (revenue – cost) first, then apply budget constraints and simple greedy/linear optimization to maximize profit.
Quick Answer: This interview question evaluates metric design, causal reasoning, experiment setup, diagnostics, SQL/statistical checks, and recommendations in a realistic interview setting. A strong answer for Determine Optimal Marketing Budget Allocation for Maximum Profit states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.
Determine Optimal Marketing Budget Allocation for Maximum Profit
Budget Allocation Across Acquisition Channels
Context
You are given an Excel sheet with per-channel performance metrics for three acquisition channels: Phone Calls, Social Media Ads, and Email Blasts. For each channel, the sheet provides:
Click-through rate (CTR)
Conversion rate (CVR)
Revenue-per-cost (RPC), i.e., expected revenue generated per $1 of spend
An individual spend cap for that channel
If RPC is not directly provided, it can be derived from CTR, CVR, average revenue per conversion (R), and the channel's pricing model (e.g., CPM, CPC, cost per send). Assume linear returns up to each channel’s cap (no saturation within cap) and that all rates are stable over the budget range considered.
Tasks
Given a total budget B, compute the expected net profit for each channel if you allocate an amount s to that channel (you may consider the case where all of B is spent in a single channel, ignoring caps for this part).
Using the conversion rate for the Phone Calls channel, estimate:
The average cost per inbound phone call
The average profit per inbound phone call
Each channel has an individual spend cap. With a fixed overall budget B, determine the spending allocation across channels that maximizes total profit. Explain your reasoning.
Hints
First compute unit profit per $1 of spend for each channel: unit profit = revenue-per-cost − 1.
Then apply budget constraints and use a simple greedy/linear optimization to maximize profit under caps.
Clarifying Questions to Ask Guidance
Clarify the business objective, unit of analysis, time window, exposure definition, and primary metric.
State assumptions about instrumentation, randomization, sample size, and data quality.
Separate descriptive analysis from causal claims.
What a Strong Answer Covers Guidance
A metric framework with primary, guardrail, and diagnostic metrics.
A credible analysis or experiment design with clear assumptions and bias checks.
SQL/statistical logic for segmentation, variance, confidence, and data validation where relevant.
An actionable recommendation that explains trade-offs and next steps.
Follow-up Questions Guidance
What sanity checks would you run before trusting the result?
How would you handle novelty effects, seasonality, or selection bias?