Export Your Customer Base to Excel: What to Do With It

The figures and scenarios in this article are illustrative: adapt them to your margins and your own data. They are not EasyFid customer results. See how to measure your results.

Your loyalty program generates a database: names, spending amounts, visit dates. A real goldmine, but it stays useless if it just sits in your phone. Exporting to Excel turns that data into a decision-making tool. Who really comes back? Who've you lost track of for three months? Where do you find your next outreach target?

But Excel is also a responsibility. Your customer data is protected by GDPR. Exporting is fine; doing it wrong is risky. Here's how to leverage your customer base in Excel effectively and compliantly.

Why export your customer base

A shop runs on regulars. But how do you know who's truly a regular? By gut feel? By memory? The problem is your memory forgets names, misses the gaps, overlooks someone who comes rarely but spends a lot. Excel doesn't.

Exporting lets you answer precise questions: How many truly active customers do you have? What's your average transaction size? Are customers disappearing? Who are the 20 % driving 80 % of your sales? These numbers give you a strategy. Reach out to the right customers at the right time with the right message. That's the opposite of mass marketing.

Set up a secure export

What should the export include? Just the essentials: first name, last visit, total spent, number of visits. No personal phone numbers, no full address (unless you have a specific temporary need). Fewer data points mean less risk, and the file stays readable.

Where to store it? Three best practices. First, encrypt your Excel file (Tools menu → Protect Workbook with a strong password). Second, store it in a secure Cloud: Google Drive with restricted sharing, Microsoft OneDrive, or self-hosted Nextcloud. Never on email, never open on the counter. Third, limit access: only you or a manager should be able to open it.

GDPR requires you to protect data. An encrypted Excel on a private Cloud is protection. Leaving a file open on the counter with every customer's first name and phone, that's a violation.

Key metrics to analyze

Once your file is open, track four simple metrics. First, total spending per customer. Sort customers by amount, highest to lowest. Typically, your top 20 represent a big slice of your revenue—you'll see by looking at the numbers. Those are your VIPs, to protect.

Second, visit frequency over the past three months. How many times did each customer come in the last 90 days? You'll spot true regulars (2–3 times a week) versus occasional customers (once every two months). A simple formula does this.

Third, the date of the last visit. How many days ago? Under 7 days = very active. Between 30 and 60 days = slipping away. Over 120 days = dormant. This column alone tells you where to look for loss.

Fourth, average spend per visit. Divide total by visit count; you see who spends big per trip versus who racks up small purchases. Useful for calibrating offers.

Spot your real regulars

Now that you have the numbers, create two columns: "Status" and "Action". Sort your customers into four buckets. Active VIP: spent > €500/year AND last visit < 30 days ago. Action: surprise them with a premium birthday gift, an unexpected discount. Regular: spent > €200/year AND visits > once per month. Action: just keep doing what you're doing—they're loyal.

Volatile: spent > €100/year but last visit > 90 days ago. Action: reach out with a personal note and a gentle offer. New or dormant: very few purchases or last visit > 6 months. Action: archive or reach out once, softly.

In 20 minutes, you've segmented your customer base. That's the start of a real strategy.

Find and re-engage inactive customers

Many small shops lose customers without realizing it. Someone came every Thursday for a year, then vanished. Why? You'll never know unless you look. Excel tells you: "This customer hasn't bought in 89 days." Time to reach out.

How? First, filter customers whose last visit was 60–120 days ago. Sort by amount spent (reach out to the big spenders first). Pick the next 20–30 on the list. Then contact them simply. A call, a text, a note if you see them in. "It's been a while; we miss you. We've got a little surprise this week if you stop by." No pressure, no big discounts, just human connection.

This kind of outreach has a surprising payoff: 30–50 % come back once. And if you keep doing it, 20 % become loyal again. A re-engaged customer costs almost nothing and returns a lot.

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