Ad-Spend & ROAS Forecasting for a Digital Agency

Media & Advertising: Media planners could not predict how budget changes across Google, Meta and marketplaces would affect client revenue. ROAS +17%,…

Client: Performance Marketing Agency. Industry: Media & Advertising.

Challenge: Media planners could not predict how budget changes across Google, Meta and marketplaces would affect client revenue.

Solution: A marketing-mix and ROAS forecasting model trained on two years of campaign data, with a budget-scenario planner that recommends channel splits.

Technologies: Python, Bayesian MMM, BigQuery, Airflow, Looker Studio.

• ROAS: +17%
• Planning Cycle: Days → hours
• Clients Onboarded: 40+
• Forecast Error: <10%

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