Multi-Touch Attribution (MTA) MTA is a method that looks at the touchpoints of individual users to predict their next action. It's a popular approach among digital-first companies because it is easy to track activities on their own web properties. However, MTA is also incomplete, as it doesn't account for real-world marketing channels and the impact of external factors like economic conditions, competition, or seasonality. Additionally, it requires high-quality data, which can be challenging to obtain.Marketing Mix Modeling (MMM) MMM is a statistical approach that analyzes sales and marketing data to forecast the impact of future tactics based on historical data It is typically leveraged on upper funnel activities, aiming to quantify the impact of marketing activities. However, MMM can be slow to update and cannot consider factors outside marketers' control nor handle the complexity of the drivers of consumer behavior.Commercial Analytics is a multi-dimensional statistical model that measures marketing, business, and external data to produce compelling growth plans with measurable results. It sheds light on every business driver's contribution to growth, including marketing, product, customer, retail, and operational and financial data. It also considers external factors like economic, category, seasonality, and competition, providing companies with a single source of truth about everything affecting their business.