What 23 pounds of seed can teach you about customer reordering behavior

I was ordering some bulk seed online the other day.

I figured I'd buy a years worth at a time. That'll save me the hassle of running out in the middle of the season.

But by the time I got into checkout, I saw my $20 order was going to have a $20 shipping charge.

Basically making it cost the same as buying just-in-time throughout the year from another vendor.

I played with the quantities a bit and found that for every additional 3-4 pounds I order the shipping would only go up by $2.

By the end of it, I ordered about five years of seed and the shipping was only $9 more than one year.

(Any more than five years would risk the seed spoiling)

Now if this store was optimized for a high AOV, they sure got it with my order. I more than doubled my order size (quantity breaks kicked in).

But now instead of ordering five times over the next five years, I've only ordered this once.

Since the seeds are to improve my soil, there's a decent chance I'll never need to order again. In five years the soil will be good enough that further seeds wouldn't be needed.

I don't know their per-transaction costs so I don't know if the behavior I expressed was what they wanted.

From a customer behavior standpoint though, they'll weaker off with this one large order VS frequent smaller ones.

From my one order they won't know if I needed all that seed, was unhappy, and defected to another supplier. Or if I ordered enough for five years and am happy with what I got.

They might not ever know either.

If you have the option, going for more frequent orders can get you a lot better data. You'll need to watch your transaction costs but those costs might be worth the better information you have on customer habits (which you can feed into your marketing system).

That's why standard blog advice like "raise your AOV" need to be questioned and tested to see if they fit your store first.

Repeat Customer Insights and the Latency Report specifically can help spot some of this behavior.

High AOVs on the first order followed by good Repeat Purchase Rates and a long latency time is a symptom of customers stocking-up with large first orders.

The same with weak Repeat Purchase Rates is a sign of customer defections.

The app comes with a 14-day free trial so you can see how it works and get some ideas right away.

Eric Davis

Refine your automated marketing campaigns with better timing

When building any automated marketing campaign that sends messages over time, you need to know how long the campaign should be and how long to delay the messages. The Customer Purchase Latency metrics calculated by Repeat Customer Insights can help you figure out that timing.

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Topics: Average order value Customer defection Strategy

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