Predictive models are powerful tools for making smarter marketing decisions, but as with any model, the details matter. One common consideration is whether to include source as a variable. At first glance, it makes sense since different audiences generate different types of leads. But when predictive values are used not just for reporting, but for network optimization, including source as a variable can introduce risks that undermine campaign performance.

Are first-party data tools and GA4 interchangeable for tracking customer behavior? Short answer: Not even close. While both aim to shed light on how users interact with your site or product, they operate on fundamentally different levels and serve different purposes. Here’s how they break down.

We’ve all tapped “Ask App Not to Track”, and with the growing adoption of privacy-first tools, it’s no surprise that ad tracking and campaign optimization have become more complex. These changes limit how much data platforms like Meta can collect via the pixel, breaking the link between ad exposure and user actions like purchases or sign-ups. As a result, it's become harder to attribute results, build accurate audiences, and optimize campaigns. That’s where CAPI and Advantage

What would you think if you heard one company’s marketing goal was to maximize lead volume at a $100 cost-per-lead (CPL)? You’d probably be preparing for a word problem to follow. 100 is a suspiciously even base, from which incremental calculations are pretty easy. A $100 CPL is surely a sample from which a learning experience will follow and be made much easier to understand because you used base 100. You’d be wrong, but that feeling in your gut that something’s off is not w

Using a strategic, low-risk testing approach, we uncover the real value of a new ad network, unlocking efficient lead generation.

If you’re working with an agency, you’ve probably asked: "Why do you need access to my customer data?" Fair question. Let's break it down.