Overview

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Learn how to forecast marketing performance using real data instead of guesswork. In Marketing Forecasting Techniques, you’ll build practical skills to project ad spend and conversion outcomes, helping you plan budgets with greater accuracy. You’ll start by constructing baseline forecasts using methods like linear regression and growth models. You’ll learn how to analyze the relationship between ad spend and conversions and apply tools like Excel or Google Sheets to generate projections. From there, you’ll evaluate model outputs, compare forecasting approaches, and understand the assumptions behind each method. Next, you’ll refine your forecasts by accounting for seasonality and one-time events. You’ll calculate seasonal indices, adjust projections for peak periods like Q4, and apply promotion-based multipliers to reflect planned campaigns. You’ll also learn how to identify outliers and ensure your models reflect real-world conditions. Through hands-on activities, you’ll build forecasts, adjust budgets based on seasonal demand, and present recommendations grounded in data. These exercises mirror the work of performance analysts responsible for planning marketing spend and forecasting results. This course is best suited for marketing analysts, performance marketers, growth marketers, and other marketing professionals who use data to plan budgets, evaluate campaign performance, and forecast results. Basic familiarity with spreadsheets and marketing metrics, such as ad spend and conversions, is helpful for success in this course. By the end of this course, you’ll be able to build, evaluate, and refine marketing forecasts that support smarter budget planning and campaign strategy.

Syllabus

Forecasting: Construct Performance Models

Historical performance trends rarely tell the full story without accounting for seasonality, promotions, and external events that influence campaign performance. This module focuses on refining forecasting models by identifying recurring seasonal patterns, applying seasonal adjustments, and incorporating promotional impacts into budget planning workflows. Learners examine how to distinguish meaningful trends from random fluctuations and improve forecast accuracy during high-variance periods such as holiday campaigns or promotional peaks. The module emphasizes practical decision-making and forecast refinement techniques used in real marketing planning environments. By the end of this module, you will be able to adjust forecasting models for seasonality and produce more reliable campaign budget projections.

Forecasting: Seasonal Adjustments and Refinement

Forecasting is a critical marketing planning skill because campaign budgets and performance targets often need to be defined before complete data is available. This module introduces practical forecasting methods used to project ad spend, lead volume, and conversion outcomes from historical campaign data. Learners explore core forecasting concepts, including linear regression, moving averages, and data preparation, while comparing spreadsheet-based and AI-assisted forecasting workflows. The module emphasizes evaluating assumptions, interpreting outputs, and selecting the right forecasting approach for different planning scenarios. By the end of this module, you will be able to construct a forecast model and project next quarter's spend and conversion volumes.