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At PMG, data and technology are at the heart of everything we do. So, when our clients ask us “How much we should be spending?”, we typically start with a data-driven approach. After some research, we decided to pursue the idea of calculating the point of diminishing returns to answer such a question. When will […]
I’ve run into this issue a couple of times during my time at PMG. I’ve used R to perform some kind of analysis, forecasting, clustering, etc., and I need to get the result into our database so anyone on our analytics team could use the output in a SQL query or connect to it in […]
SQL joins typically look to combine two tables into a set of columns that exist in both. Usually, the values match exactly, making the join straightforward. We can also use ILIKE to make the join case-insensitive and BETWEEEN if we have the date in one table and start date and end date in another. Those […]
My last blog post took a look at calculating average position. Let’s now look at another instance where people make the dreaded “take the average of an average” mistake, calculating impression share. (See the average position post to learn more about averages of averages.) Again, let’s take a look at some dummy data. We have date, […]
I’ve been asked more times than I can remember, “How do you calculate the real average position?” The good news is that everyone asking realizes that taking an average of an average will get you in trouble. The bad news is they still don’t know how to actually calculate the true average position. In this post, […]
Here it is. The highly anticipated second and final installment of my two-part series on Google’s Causal Impact R package. Please try to control your excitement. In part 1, we took a general look at how the package helps marketers measure incrementality and ran through a quick toy example. Here’s a quick refresher on the […]
Incrementality. It’s one of the toughest things to tackle in digital analytics. “How many incremental conversions did that branding campaign drive?” “How many additional clicks did we drive by implementing that new Adwords feature?” The most common solution is a simple lift analysis: calculate the difference between the average conversions before and after the intervention. […]
You know what really grinds my gears? Using correlation to imply causation. It’s 2015 people, you should know better by now. When you Google “correlation vs causation,” about 5.3 million results are returned in a quarter of a second. The first one? “Correlation does not imply causation,” courtesy of Wikipedia. The only positive thing to come […]
You’re wanting to look at ROI by product over time against your goal, and you want to do more than show a data table. You want to come up with a way to visualize the data that’s meaningful and easy to understand. Naturally, you start by plotting a line graph of ROI over time with […]
You know what really grinds my gears? Poor table formatting. It can be hard enough to stare at a large table of numbers and try to find what you need, but sometimes it’s more difficult than it should be thanks to poor formatting. In this episode of WRGMG, let’s take a look at some common […]