The more specific a piece of data, the less useful it is in forecasting. This is a maxim of predictive analytics. Predicting audience behaviors based on the year they were born is useful. Predicting audience behaviors based on individuals’ exact birthdays is not useful. Which is why, in OpenAI’s newest paper on hallucination in generative…
How good is your product market fit? Do you have service options for every tier of customer? As the economy grows more uncertain and forecasting the quarter or year ahead becomes more difficult, one of the simplest bulwarks against revenue uncertainty is making sure you have products or services that fit every budget level. If…
Predictive analytics in marketing is broken. More specifically, predictive analytics at the macro level – like what consumers are going to purchase, how they plan, anticipating demand, etc. is badly broken. And it has been since March 2020. Here’s why. By its very nature, forecasting and predictive analytics rely on historical data. The more stable…
Katie shared this chart from McKinsey this morning, which is… inaccurate. Here’s why. There are three major forms of AI – regression, classification, and generative. We’ve had the first two for decades. You’ve experienced classification AI since the late 1990s when intelligent spam filters first appears to classify email as spam or not. You’ve experienced…
Summary In today's episode, I walk through the basics of predictive analytics, its use cases in marketing, and how to apply it to your annual planning. Here's what this means for you. You gain a repeatable way to forecast demand, time campaigns, and squeeze more value out of limited time and budget without guessing. You'll…
Summary In today's episode, I walk through how to forecast your marketing budget using historical analytics data and apply those forecasts to plan smarter budget allocation across channels. Here's what this means for you. You gain a practical framework for predicting weak periods in your traffic, then inverting those predictions to concentrate your spend where…
Summary In today's episode, I walk through how to use predictive analytics and seasonal forecasting to plan marketing campaigns across different industries using a cheese shop as a practical example. Here's what this means for you. You gain a repeatable framework for timing ad spend around demand inflection points and choosing the right data sources…
The power of forecasts lies in their ability to stimulate action, not in their accuracy. Most people don’t care if a forecast is right or not. Forecasts don’t need to be data-driven to be effective. Horoscopes are a good example of a forecast that is not accurate, but still persuades people to take action. The…
Summary In today's episode, I break down why forecasts don't need to be perfectly accurate to serve their real purpose and what that reveals about data-driven marketing. Here's what this means for you. You'll see that the true value of any forecast is the decision it triggers, not the precision of the prediction itself. You'll…
Summary In today's episode, I answer a question about what kinds of predictive analytics modeling live inside Google Analytics and why most of it happens behind the scenes. Here's what this means for you. You'll find out that GA4 exposes very little built-in forecasting to end users, so you need to pull data through the…
