The team at Meta did another Marketing Mix Modeling summit last week, and given the popularity of the last one we covered, we thought we’d do it again. This summit covered a lot of familiar themes – e.g. the loss of tracking from iOS14 – but with a particular focus …
The Marketing Science team at Meta set the Marketing Mix Modeling world alight when they released Robyn, their open source solution. Entering the market at a time when everyone was scrambling to solve the iOS14 problem, helped to introduce the method to a wider audience, and validate that it was …
One commonly asked question from clients just getting started with Marketing Mix Modeling (MMM), is how much data they need to build a model. It’s a particularly important question in B2B, where there isn’t always the volume that large scale consumer brands enjoy. In theory there’s no ‘right’ answer to …
How much data do you need for your Marketing Mix Model? Read More »
Disclaimer: This blog post was written by an external contributor about Uber’s open-source Orbit library for time series forecasting and its applications to marketing mix modeling. The approach laid out in this document is not reflective of how Recast approaches time series forecasting and modeling time-varying effects. The actual model …
At Recast I have the privilege and challenge of introducing advanced statistical concepts to people who have a strong desire to be more data driven, but who do not have much of a background in formal statistics. While word has gotten out that “statistical significance” isn’t all it’s cracked up …
Occasionally, prospective customers react with shock when we tell them that we don’t “control for the COVID pandemic”. “The pandemic really impacted our business, so how can your model be accurate if you don’t control for Covid?” they ask. The answer is simple: Recast models changes in the macro-environment, but …
Marketing Mix Modeling (MMM) has been around since the 1960s, where it was used to correlate spikes and dips in sales to marketing activity. There has been a recent resurgence of interest in marketing mix modeling, as consumers increasingly opt out of digital tracking and digital-first brands mature to offline …
Marketing Mix Modeling Software: Build vs Buy Calculator Read More »
Marketing mix modeling is hard. Trust us. When we were starting Recast, we thought it’d be easy: we’d use some off-the-shelf Bayesian time-series models and six months later we’d have a top-shelf model. But unfortunately, it didn’t work like that. It took us multiple years of PhD-level research time to …
In 2017 Nielson conducted a study of 500 advertising campaigns across all major media platforms: TV, digital, magazines and radio. They found that a remarkable 47% of the campaign’s contribution to sales was attributable to Creative. A further 15% came from Brand, which we can think of as the culmination …
Creative performance drives 47% of sales: why is it missing from most models? Read More »
Most people aren’t aware that Facebook (Meta) invented a new ‘accuracy’ metric. Their own documentation calls it a ‘major innovation’ of Robyn, their Marketing Mix Modeling (MMM) library. It’s both genius and controversial. The metric we’re talking about is “Decomp RSSD” and it’s a measure for how much the model …
