[Note: This post contains spoilers for the first episode of Tom Clancy’s Jack Ryan] A TV show where the lead character is a SQL-using analyst and economist? Count me in! But, it looks like it will mostly be a wartime heavy action political thriller so I probably won’t be as into it as Moneyball. I […]
Tag Archives: data science
Webinars – Data Science and Content Attribution
I have been on two webinars during my time at Cardinal Path. Content Attribution One of the projects I’m super proud of that I’ve worked on at Cardinal Path is Content Attribution. This is a code base I developed and then helped to deploy to help measure content performance. Do you want to learn what […]
Adding Context to Attribution Data
As with all things, without context, attribution data is hard to interpret. I discuss on Cardinal Path’s blog why it’s so important to make sure your attribution analysis includes controlling for the cost of the media spent. As marketers continue to grapple with assessing every channel and marketing touchpoint, it’s important to note — attribution […]
Getting as Complex as Necessary: Attribution Modelling
Attribution is a hot topic, but it can be daunting to know where to begin. Read my post on Cardinal Path’s blog to find out where you should begin. What does getting as complicated as necessary look like for you? That depends on where you are on the path to attribution. For example, for a […]
Is your website helping drive conversions? Use Content Attribution to find out!
Read my post on Cardinal Path’s blog to learn more about content attribution. Attribution is used to determine which marketing events contribute the most (and most often) to sales conversions. But in almost all cases, customers will see more than just advertising before they convert. Oftentimes, they will be fed content across your website which […]
Uplift Modeling: measuring true campaign impact
How can you tell if your campaign truly worked? Read this post on Cardinal Path’s blog that I wrote to learn about how Uplift Modeling can help you. You’ve just finished running a new advertising campaign. Now you want to know the answer to your obvious and most pressing question: did it work? That is, […]
Choosing the right error metric for your predictive model
Want to learn what to consider when choosing an error metric for your machine learning model? Read this post I wrote on Cardinal Path’s blog! The main considerations are: Do we want to punish overestimates or underestimates more heavily? Are there segments which have greater costs associated with incorrect predictions? Should we punish larger errors […]
How to Best Use Customer Lifetime Value Analysis Results
Check out my post on how to action the results from a customer lifetime value model from the Cardinal Path blog! No matter what analysis or model you are doing for a business, it is all useless if the model doesn’t get used. Learning what decisions can be influenced by what approach will help drive […]
Are You Spending Too Much?
Are you spending too much on online advertising? Find out how to answer this here. In this post I wrote on the Cardinal Path blog, I explain how diminishing returns can be used to optimize your spending budget. As you are probably aware, every dollar spent on advertising does not generate equal return. When looking […]
Data Driven Attribution or Media Mix Modelling?
Read this post I wrote on Cardinal Path’s blog to learn the difference between Attribution and Media Mix Modeling. It can be a bit confusing since they both seem to answer the same or similar questions, but depending on your business, one is probably better suited to your needs. This table from the post summarises […]