A Compendium of Stupendous Amazing Things.
You’re late to the party, here’s your roadmap on how to catch up.
Getting it right can be technically challenging, requiring good user experience, smart data collection practices, and a well thought out data and martech stack.
If you’re not doing CAPI, you need to.
And if you’re not doing it right, you need to fix it.
We have seen as much as a 50% improvement in CPA/CAC when CAPI is implemented well.
We made Pickaxe analyze Game 6 of the NBA finals. I’m more hopeful about its basketball future than I am about the Nets.
We ran the NBA Finals through our insights engine to see if it could tell us what we missed.
Turns out it thinks defensive really does win championships.
Careful analysis of usage patterns can help streamers differentiate between “legitimate” household usage and rampant “egregious” password sharing.
Are we getting 2 inches of snow? or 20? The forecast model’s don’t agree on that point, and that disagreement is exactly why we’re such a fan of using an ensemble model learning approach (and a team A vs B approach).
I’m off today but our insights engine is still delivering news about your data (and this New Yorker cartoon explains how)
Our insights engine uses machine learning and data analysis to monitor your metrics and alert you when there’s good news or bad news.
Nexstar needed a better way to understand user behavior, ad anomalies, and advertising performance across the hundreds of federated stations and websites that they operate from a mix of technology platforms built by them, or that they had acquired from multiple legacy parent companies over the years. The result was inconsistent and disparate reporting.
With thousands of advertisers, this Publisher was spending several days each month configuring Google Data Studio to generate campaign-close reporting. Not only were the visualizations lackluster and off brand, but the Publisher was also running into significant INFOSEC concerns granting advertisers access to their data in a secure way.
The CMO and marketing team at Spartan Race were having challenges with getting accurate attribution across all of their paid media channels, including above the line sources like TV ads and Out Of Home. And recent changes in cookie blocking and iOS added significant confusion in the data, causing major conflict between what they believed was driving conversion vs what their internal data was showing was driving conversions.