CAC Inflation

How Duplicate Customer Records Inflate CAC

Learn how duplicate customer records cause customer acquisition cost errors, marketing data inaccuracy, and lead to wasted marketing spend.

8 min readLast updated Jan 2026

The CAC Problem No One Talks About

Customer Acquisition Cost (CAC) is the foundation of marketing budget decisions. But when your customer data contains duplicates, your CAC calculations are fundamentally wrong.

Duplicate customer records make your customer count appear higher than reality. This creates marketing data inaccuracy that leads to customer acquisition cost errors — and ultimately, wasted marketing spend.

Key Insight

If 15% of your "new customers" are actually returning customers with duplicate profiles, you're misattributing 15% of your acquisition spend.

Understanding CAC Calculation

CAC is calculated by dividing total marketing spend by the number of new customers acquired. The formula is simple:

CAC = Marketing Spend ÷ New Customers

The problem is in the denominator: how do you count "new customers" accurately?

When inaccurate customer data inflates your new customer count, your CAC appears lower than it really is. This creates a false sense of marketing efficiency.

How Duplicates Break the Math

Here's a real-world example of how duplicate customer records distort CAC calculations:

CAC Calculation Comparison

MetricWith DuplicatesClean Data
Marketing Spend$50,000$50,000
"New" Customers1,000850
Calculated CAC$50$58.82
CAC Error Rate-15%Accurate

In this example, the store thinks their CAC is $50, but it's actually $58.82 — a 17.6% error that compounds across all marketing decisions.

The Hidden Cost of Inaccurate Data

CAC errors don't just affect reporting — they cascade into every marketing decision you make.

Wrong Channel Attribution

You might think Facebook has the best CAC, but those "new" customers might be returning customers who originally came from Google.

Overconfident Budget Scaling

If you think CAC is $50 when it's really $60, you might scale budgets based on profitability that doesn't exist.

LTV:CAC Ratio Distortion

Your LTV:CAC ratio might look healthy at 3:1, but with accurate data, it could actually be 2.5:1 — below your target threshold.

Real Impact on Marketing Budget

Let's quantify how marketing data inaccuracy affects a typical Shopify store's annual marketing spend.

Annual Impact Example

Annual Marketing Budget$600,000
Duplicate Rate15%
Misattributed Spend$90,000
Potential Waste/Misallocation$90,000/year

Fixing Your CAC Metrics

The solution is straightforward: clean your customer data to get accurate acquisition metrics.

1

Merge duplicate customer records

Consolidate fragmented profiles to get true customer counts.

2

Recalculate historical CAC

Update past metrics with accurate customer data.

3

Set up ongoing monitoring

Prevent new duplicates from distorting future metrics.

MergeGuard for CAC Accuracy

MergeGuard identifies and merges duplicate customer records, giving you accurate customer counts for true CAC calculations.

Next Steps

Ready to fix your CAC metrics? Explore these related topics: