You don’t just want an MMM model. You want a model that can be trusted. But since MMM models are really powerful, they can also be subject to overfitting. So, how can we build confidence in the model and the recommendations we’re making to the marketing team? The answer: backtesting […]
How to do holdout accuracy and backtesting for your MMM (and why it matters) Read More »
It is said that the best product ideas come from having to scratch your itch – from facing a big, challenging problem and urgently needing to find a solution for it. Recast has a similar genesis story. I ran the data science and analytics team at Harry’s, known for its
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 »
If you’re considering working with a marketing mix modeling vendor, you’ve probably heard of Google’s open-source MMM tool, Lightweight MMM, Meta’s Robyn MMM, and our very own MMM platform here at Recast. Now, we know that choosing an MMM is a complex decision that has many variables you have to
Recast vs LightweightMMM vs Robyn Read More »
People often ask us about the differences between Recast’s next-generation MMM platform and Google’s open source MMM tool, Lightweight MMM. In this blog post we do a compare-and-contrast between these tools – we’re obviously biased but will do our best to lay out the pros and cons of each tool
Recast vs LightweightMMM Read More »
As more marketing teams understand the need to add new measurement methods beyond digital tracking, we expect more and more emphasis on MMM and experiments. Experiments and MMM can be very complimentary – but they have to be done well. One of the challenges with both methods is that they’re
High-velocity Marketing Testing Read More »
Recast’s MMM uses Bayesian statistics, but why doesn’t everyone else? We asked this to Recast’s co-founder Michael Kaminsky, and the rest of this article covers what he answered: “When I started my career as an econometrician, I was pretty comfortable with the frequentist methods that people who did a technical
Why isn’t everyone Bayesian? Read More »
The central modeling challenge for an MMM is the following: given any set of marketing inputs (budget decisions, promotion dates, new product launches, etc.) to be able to accurately predict what our customer’s performance will be. But, how do we judge our model’s ability to meet this challenge? How do
How we do holdout testing at Recast Read More »
Today, we introduce the Lift Test Calculator – an open-sourced tool designed by Antonio Vargas, a senior data scientist at Recast. The Lift Test Calculator was created to address the gap in the way lift tests are conducted and interpreted. Antonio and the Recast team recognized that marketers often ran
Recast’s Lift Test Calculator [Download + Video Walkthrough] Read More »
