Use both historic and recent data for decisions

It's that time of the year to start getting the garden ready.

A big part is figuring out when its safe to plant outside in spring. If it's too cold, the plants will weaken or die. Wait to long and they miss out on early growth.

Many companies have created calendars for measuring this, called the frost dates or frost-free dates. They use historical data to provide statistics of how likely frosts are. Basically they'll tell you "on this date there is a X% change of frost in this location".

Problem is, climate change in the recent years has really messed with the historic data. April 1st used to be a safe date (30%) but now one place is saying March 6th is safe. An extra 25 days is a lot of extra time, almost 10% of the entire growing season.

Great for tomatoes and peppers if it's true. Hazardous if it's too early.

Historic data is great but you have to keep in mind recent data too. Any changes or trends can weaken the predictive value of historic data. That's why I use historic data, year-over-year, and current-previous when analyzing data in Repeat Customer Insights. They each contribute to the big picture.

With this new frost data, I now need to see if my own planting schedule needs to move up.

Eric Davis

Promote products that create your best customers

When it's time to run a promotion, how do you pick the products to feature? Best sellers are okay but wouldn't it better to promote the products that crate the best customers? Repeat Customer Insights will analyze your product and buyer behavior to show which products and variants lead to the highest quality customers.

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Topics: Analysis Historic performance

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