I iterate through snapshots of the twelve-month buyer file. I sum buyers, I sum orders, I sum items, and I sum demand. Often, I compute a twelve-month repurchase rate, and I sum all first-time buyers as well.
This analysis allows me to see how a business evolves and changes over time. I review a handful of metrics:
- New Buyers.
- Existing Buyer Repurchase Rate.
- Orders per Buyer.
- Items per Order.
- Price per Item Purchased
- Average Order Value
- Demand per Buyer
Most of these metrics move within a 10% band.
In other words, it is rare to find a company that increased items per order from 3.0 to 3.5. Very rare. It is rare to find a company that increased orders per buyer, from 1.4 to 1.6.
Price per Item Purchased, now that one moves up and down as companies liquidate product or shuffle through the merchandise assortment, generally increasing over time.
Average Order Value (Price per Item Purchased * Items per Order) increases at the rate of inflation, on average.
Annual Retention Rate seldom moves outside of a +/- 10% band.
New Customers moves directly as businesses invest more (positive economy) or pull back (recession).
So I can quickly diagnose what's happening to a business by running these metrics for a five year timeframe. And since most of the metrics don't fundamentally move over time, guess which tactic is most correlated with long term sales growth?
You, too, can quickly diagnose what's happening to a business by running these metrics for a five year timeframe.
A show of hands ... how many of you are doing this?
So which tactic is most correlated with long term sales growth?
ReplyDeleteNumber of new customers acquired each year.
ReplyDeleteKevin, do any of your books go into detail on how you do this analysis?
ReplyDeleteThe database marketing book spends considerable time on these metrics.
ReplyDeleteJust bought it, thanks!
ReplyDelete