Most things can handle one-off spikes of change.
A single hot day might hurt some plants but won't kill all of them.
A stock outage this week from a vendor will lose you some orders, but you'll catch up later in the month.
A flood of orders overnight will cause a busy next day, but won't force you to hire more staff.
The long-term changes are the things that cause a lot of impact though. Even small changes can accumulate enough momentum to unsettle the day-to-day.
Climate change over the years will cause some plants to never thrive in the same area again.
Never getting a stock replenishment will force you to discontinue the merchandise and find replacements.
A never-ending number of orders will require hiring and tooling up before your staff is exhausted.
The problem is there's often no clear line between the one-time and long-term. Is three days of order increases enough to start hiring? Ten days? A month?
Reacting the wrong way, in either direction can be expensive and damaging.
That's why having a good view into trends over the long-term is important. If you can start to see the differences between one-time, cyclic, and permanent events then you'll have better reactions.
Watching how your customers evolve over the months and years is one major sequence of events that I don't see enough Shopify stores watching. This includes watching how many customers shift into becoming loyal, defecting, or to potentially promising. In Repeat Customer Insights I added historic comparisons to Customer Grids to help with this.
But a lot of this requires paying close attention to your metrics and how they change from month-to-month and year-to-year.
Eric Davis
Discover where your best customers come from
Going beyond simple attribution, Repeat Customer Insights lets you analyze and segment your customers by who first sent that customer your way.
This will let you find the best sources of long-term customers, not just anyone who orders.