Demographics and Feedback Loops

Always overlay demographic data, when trying to understand whether a feedback loop might be damaging to the long-term health of your business.

Catalogers know this all too well. Here's what they observed:

• 1999 Catalog-Centric Customers = 49 years old.
• 1999 Online-Centric Customers = 44 years old.

You can see that the online customer is younger. Ok, no worries.

• 2004 Catalog-Centric Customers = 54 years old.
• 2004 Online-Centric Customers = 49 years old.

Oh oh. Both customers age five years. This is bad. A healthy business can cater to a cohort over time ... but there's a limit to that trajectory (retirement). Many healthy businesses are able to recycle into younger customers, and do so via new channels.

• 2009 Catalog-Centric Customers = 59 years old.
• 2009 Online-Centric Customers = 53 years old.

At this point, the catalog industry should have noticed something, and should have taken action. That didn't happen. Now, the trend looks like this:

• 2014 Catalog-Centric Customers = 64 years old.
• 2014 Online-Centric Customers = 57 years old.

When you look at the trend from 1999 to 2014, it's obvious what is happening. One barely needs to project into the future to understand that this feedback loop is going to end in an ugly fashion.

It is very common for businesses to refresh the customer file through newer channels. For most of us, the channel that can refresh the customer file is mobile.

Measure the average age of customers who shop old-school channels, across time.

Measure the average age of customers who shop online, across time.

Measure the average age of customers who heavily invest in mobile.

If you can demonstrate that the mobile customer is younger than average, and that this cohort is growing faster (in counts, not percentages) than old-school channels, then you are avoiding the future impact of a feedback loop.