Marketing Psychology: Building The Desire Path

Marketing Psychology

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Marketing is many things, but one part that can’t be understated is psychology. Human behaviour drives so much of our decision-making processes that understanding it can mean the difference between a product succeeding and failing.

The decision to make a purchase might start from a logical place (a need arises, so I need something to fill the gap), but it can (and often does) move to an emotion-driven place pretty quickly.

Predicting human behaviour can be a full-time business, however, reacting to human behaviour can also be effective. Not to mention a bit more budget-friendly.

Staying Reactive

Ogilvy’s Rory Sutherland put it best when he said “It is perfectly reasonable to be logical and wrong.” Predicting human nature is a tough business, and it’s much easier to react to accumulated data.

This is where the concept of the “desire path” comes into play.

While the term is actually in regard to urban planning, it can be applied to other areas. A desire path is an unplanned secondary path created through repeat foot traffic. It is often the shortest route between two points.

It looks like this:

When a desire path occurs, the reaction for most is to put up a fence to ensure people use the pre-built path. However, the much stronger idea is to use this new data and pave the path.

Before you go throwing up new paths everywhere, there is one more idea you should know about. One that affects the desire path principle.

Survivor Bias

While not directly related, the desire path and survivor bias are often two sides of the same coin.

Survivor bias is the logical error of concentrating on data that passes a selection process while overlooking those that did not.

Story time! During the second world war, the U.S. military compiled data on every bomber that returned from combat to see where most hits were occurring. It looked like this:

Their rational conclusion was to add armour to the most hit areas of the plane. Makes sense right? Well, a professor at Columbia University rightly pointed out an issue with this conclusion. All the collected data was from bombers that were hit and returned home. The areas of the plane with no red marks meant that if a plane was hit in this area, it would be critically damaged and crash.

So, the data indicated one thing, but the missing data confirmed the opposite was true!

Take Off The Blinders

When analyzing data collected from your website, social media, sales team, or any other source, make sure you’re not only reacting appropriately, but taking into account the data that isn’t there too.

Data should drive the decisions you make. However, making sure you’re spending the time to interpret data correctly, could mean the difference between your bombers coming home or not!

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