Time series data is special because the order in which observations occur is meaningful. For example, looking at sunglasses sales at Sun-Glasses-For-All (an imaginary brand), we can see that knowing yesterday’s sales gives you information about today’s sales. And sales this time last week gives you information about today’s sales […]
Gaussian Processes for Time Series Read More »
There’s a lot of confusion from marketers about the right way to use lift tests or incrementality experiments to calibrate the results of a media mix model (MMM). We see questions like: You need to be thoughtful when incorporating information from incrementality experiments into an MMM, so in this post
How to Use Lift Tests to Calibrate an MMM Read More »
Nearly every business has an annual cycle: seasons where the business waxes or wanes, or specific dates like Cyber Monday, Memorial Day, or Mother’s Day, which see enormous spikes in sales. Imagine you have a business that sells hot wings — when do you think the busiest time of the
You’re probably modeling seasonality the wrong way Read More »
At Recast, we often speak with practitioners who are trying to build their own MMM in-house. While we think there are great reasons to use a tool like Recast instead of building in-house, many people want to try it themselves before committing to working with a partner. In this post,
One of the core problems to solve when doing marketing mix modeling (MMM) is handling how the results from a previous period ‘carry over’ into the next period. In marketing we know that the full effect of advertising isn’t felt on the same day or week in which the campaign
Adstocks: Accounting for the Lagged Effect of Advertising Read More »
You cannot double spend and expect sales to double. Advertising on auction-based platforms like Meta or Google exhibits diminishing returns, meaning as you increase spend, efficiency suffers. When you continue to increase your advertising spend you see increased customer acquisition cost (CAC) and lower return on investment (ROI). Essentially, there’s
Diminishing Returns: Accounting for Channel Saturation Read More »
Disclaimer: This blog post was written by an external contributor about detecting and addressing heteroskedasticity in marketing mix models. The approach laid out in this document is not reflective of how Recast approaches heteroskedasticity and model validation. The actual model specification can be found in the technical model specification. Heteroskedasticity
How to fix heteroskedasticity in your Marketing Mix Model Read More »
We live in an omni-channel world, and that has drastically changed the way consumers buy. It’s no longer a linear journey; it’s an intricate web of touch-points across online and offline channels. So it’s no surprise that this interconnectedness means that actions in one channel can ripple across others, sometimes
What are Halo Effects and how do they impact MMM? Read More »
There are thousands of non-marketing factors that can make an impact on your company’s base sales. Consumer sentiment, GDP growth, inflation, consumer saving rates, interest rates… we could list dozens and dozens of exogenous factors that can change your base sales. But when it comes to marketing mix modeling, we
One of the ever-present problems with marketing mix modeling is that you always have to choose some start date. And since you always need to choose a start date, there’s always some period before the start date that’s impacting your results. Here’s how Recast handles these carry-over effects.
Burn In: How Recast Handles Carry-over Effects Read More »
