The more you know about that 20 percent, the better you will become at focusing your entire operation -- product selection and buying, displays, advertising, special events, etc. -- on your best customer and his or her preferences.
The goal here is to identify the general, overall characteristics of your best customers. Once you know these characteristics, you can seek out more customers just like them. Think of it as cloning your best customer!
Step One: What's Selling Now?
Conducting an effective analysis of sales can be very revealing. Looking at sales from a variety of productivity measures can provide new insights. Consider these: Total sales volume. Total number of transactions. (This is very important!) Volume and transactions by category. Units per transaction.
By displaying this information on a spreadsheet month by month, you will quickly see your store's seasonality, and how those seasons might not be the same for all product categories.
The sales analysis helps you pinpoint weaknesses -- and opportunities. For example, if your sales trend is up, is it because you are having more transactions or higher average sales? If the average sale is higher, is that because customers are buying more expensive items or a greater number of items at each transaction?
We think you will find this sales analysis step fascinating. And, we are confidant you will find some surprises!
Step Two: Who's Buying What's Selling?
The importance of this step cannot be emphasized enough: It's not enough to know what's selling; you must know who's buying what you're selling! The easiest way to do this is to capture customer information at the point of sale so you can link customer data with transaction data (item purchased, price, SKU, date, time, etc.).
For example, by programming a seven-digit field into your register, you can collect three key pieces of non-invasive information about each consumer: ZIP code (five digits), sex (one digit) and age category (one digit). Instruct salespeople to guesstimate customer's age as they ring up sales.
This method of gathering information is low-cost and unobtrusive, and while designating age categories won't be 100 percent accurate, the correct and incorrect guesses usually will balance out . . . and always will be revealing!
Here are two examples of the types of findings you can develop through this point-of-sale data capture. Notice how readily this information can be put into effective, practical use. Very quickly, the best customers (the customers you want more of) stand out from the rest of the pack. This enables you to focus scarce time and resources where they can serve you the most: on selling to your best customers.
In this example, the client wanted to know which of three particular age groups was buying full-price goods, and which age groups were "cherry picking" clearance items.
Table A shows generally what they found. The 35+ age group was predominantly buying full-price and/or first markdown goods; the 18 to 24 year olds, however, were very price driven.
Knowing this (verifying your hunches, perhaps) leads to a whole series of management decisions and opportunities. For instance:
Targeting your advertising at age 35+ households (reached via direct mail, zoned newspaper inserts, selected radio formats, selected television/cable shows, etc.). Not spending advertising money on the younger "price hounds."
Focusing your advertising message on benefits important to your best customers Influencing what music you play in your store, what hours you are open, how you staff, etc.
Choosing where and how to do outreach advertising -- to appeal to and bring in more of your best customers.
This next example illustrates differences in shopping behaviors which can be linked to the customer's ZIP code. That, in turn, allows you to learn even more about your customers through additional research (using free information at your public library).
Table B shows some major differences between shoppers when we analyze their transactions by ZIP codes. The folks who live in ZIP code XX212 produce the highest average sale and the highest units per transaction. But they buy few items at full price!
A visit to the library to check out the census data on this XX212 ZIP code reveals these kinds of findings: this ZIP has fewer home owners and more renters than other ZIPs around the area; more single people; and many elderly women (widows, perhaps, on fixed incomes?)
But look at what we found about ZIP code XX106. The average sale is close to the store overall average, yet these folks buy very few markdowns. Who are they anyway? A check of the census data suggests highly-educated, professional/managerial jobs, high incidence of early-30s in age, and small household sizes. These are the SINKS and DINKS (Single-Income, No Kids and Dual-Income, No Kids). They are pressed for time, with good incomes, and able to spend on themselves.
Step Three: Tying It All Together
There is enormous value in understanding your best customer categories; it provides a fundamental framework for your management decisions. It helps explain why:
Why does this merchandise sell?
Why does it sell at this price?
Why should I create this look to the store?
All these questions can be answered more consistently and efficiently using your best customer as a foundation.
Pro-actively treat your best customer as the valuable asset she or he is to your window coverings store. Today, it is not enough to have profitable products. Instead, we must find - and nurture - our most profitable customers.