Rainfall is a Path to Purchase

How does rainfall relate to sales?

The weather service now measure things with such precision that we can determine flat (rain) vs. elongated (ice) droplets, etc. A new project on data science competition site Kaggle focuses on predicting how much rain actually hits the ground from a series observations on the way down. The objective of the contest is to estimate the likely outcomes from an hour's worth of data. Such models have implications for agriculture, highway safety, and other resource allocation projects.

Weather now measured in two-dimensions

This sounds like marketing mix and the path to purchase.

Marketing is often faced with a similar problem: how to align out of store activity, digital or otherwise, with in-store sales. Like rain, sales vary with time and space so the analogy is apt.

Recently Yicheng Song and colleagues at Boston University have been working on identifying common path-to-purchase analyses that combine multiple touch points and discrete sales outcomes. Their approach can be summarized as follows:

1. There are patterns to the path to purchase (clusters of consumers emerge along common lines)
2. The path and outcome varies by initial stimulus (catalog, email > online, offline)
3. Paths traverse on and offline steps  (variance is a matter of degree, not one or the other)

What I find interesting is that the approach works with segments and plugs missing data (all too common in path to purchase work) to get a handle on what is likely to happen. Like most marketing analyses these days we don't know anything with certainty but can only talk in directional terms. This means we might be able nudge the pendulum one way or another with a change in the marketing mix but stuff still happens on the way to the store.

Maybe there's something more to be learned from the rain.