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 …
Introduction Note: this post was developed in partnership with Mike Taylor over at Vexpower where they’re working to educate marketers on how to do effective media mix modeling. This post gets a bit into the weeds, so if you want a more straightforward overview, definitely go check out the companion post over there. Bayesian …
