Attribution — Returning Customer

Overview

The Attribution — Returning Customer dashboard shows marketing performance for customers who have purchased from you before. Where Attribution Analytics shows blended performance, and Attribution — New Customer isolates acquisition, this view answers a different question: how well is your marketing retaining and re-engaging existing customers?

Retention economics are typically more favorable than acquisition — returning customers have lower CPA, higher AOV, and higher conversion rates. But that efficiency can mask acquisition problems if you're not looking at new and returning customer performance separately. This dashboard makes the retention contribution explicit.

Navigate to: Signal → Marketing Attribution → Attribution - Returning Customer

Summary KPIs

Eight KPI cards sit at the top of the dashboard, each showing the current period value and a period-over-period change indicator.

Metric	What It Measures
Revenue	Total revenue attributed to returning customer orders
Orders	Number of orders placed by existing customers
AOV	Average order value for returning customers
rMER	Retention MER — Returning Customer Revenue ÷ Total Ad Spend. Measures how much returning customer revenue your total ad investment is generating.
Total Ad Spend	Total spend across all connected paid channels for the period
Customers	Number of unique returning customers who purchased in the period
CPA	Ad Spend ÷ Returning Customer Orders
ROAS	Returning Customer Revenue ÷ Ad Spend

Reading these metrics together

High returning customer Revenue % of total with low new customer growth — your brand is retaining well but not expanding. Sustainable short-term, but a risk to long-term growth if new customer acquisition isn't keeping pace.
Returning customer CPA rising — it's costing more to re-engage existing customers. This often signals list fatigue, declining email/SMS engagement, or rising retargeting costs.
Returning customer AOV higher than new customer AOV — normal and healthy. Returning customers know the product and tend to buy more. A widening gap over time suggests strong product loyalty.
rMER declining — your total ad spend is generating less returning customer revenue. Worth checking whether retention-focused spend (email, SMS, retargeting) is holding efficiency, or whether overall spend growth is diluting the ratio.

The MOAT Table — Returning Customer View

The MOAT table is scoped to returning customer orders only, with three tabs: Media Source, Campaign, and Ads. The same attribution model options apply: Any Click, First Click, Last Click, Equal Weight, View-Through.

How to use this table

1. Identify which channels are driving retention — and whether they're the right ones

Look at Revenue % by Media Source. Email and SMS should typically appear near the top — these are owned channels with high returning customer conversion rates. If Paid Social or Google Ads is driving a disproportionate share of returning customer revenue, you may be spending paid budget to re-acquire customers you could be reaching through lower-cost owned channels.

2. Evaluate retention campaign efficiency at the Campaign level

Switch to the Campaign tab. Look for campaigns explicitly designed for retention (remarketing, loyalty, win-back, post-purchase sequences). Check their CPA against your average retention CPA. A win-back campaign with a high CPA relative to the value of the customers it's recovering may not be worth the spend.

3. Assess whether TOF campaigns are accidentally re-converting existing customers

Filter the main Attribution Analytics MOAT to New Customer, then compare the channel Revenue % to what you see here in Returning Customer. If a campaign you're running as a TOF acquisition campaign shows high returning customer revenue attribution, it's reaching your existing audience more than new ones — worth adjusting targeting exclusions.

4. Use the Ads tab to identify retention creative that's working

Retention creative works differently from acquisition creative. In the Ads tab, look for ads with high returning customer conversion rates (Orders ÷ Clicks) rather than just high ROAS. An ad that converts returning customers at a high rate with lower spend is often more valuable for retention than a high-ROAS ad that happens to reach a lot of existing customers.

Key KPIs Trend Chart

The Key KPIs Trend chart plots ROAS, CPA, MER, and AOV for returning customers over time on a dual-axis chart.

Use this chart to identify when retention efficiency changed and correlate it with specific actions — a new email flow, a retargeting campaign launch, a promotion, or a product drop. Retention metrics tend to be more stable than acquisition metrics week-over-week, so a sudden shift is usually meaningful and worth investigating.

Revenue & Ad Spend Trend Chart

The Revenue & Ad Spend Trend chart plots three series:

Ad Spend — total paid media investment
Returning Customer Revenue — revenue from existing buyers
Returning Customer count — number of returning customers purchasing in each period

The Returning Customer count line is the most important one to watch here. Revenue can rise simply because returning customers are buying more per order (AOV effect), but count shows whether you're actually re-engaging a growing or shrinking share of your customer base.

A flat or declining Returning Customer count alongside rising revenue means fewer customers are buying more — which may be fine, but also may signal that your reachable returning customer pool is shrinking.

Both charts support export via the menu icon (top right): PNG, JPEG, PDF, SVG, CSV, and XLS.

New Customer vs. Returning Customer: The Comparison That Matters

The single most useful analysis you can do is open Attribution — New Customer and Attribution — Returning Customer side by side for the same period and compare channel performance across both.

What you're looking for	What it means
Channel has high Revenue % in Returning, low in New	It's a retention channel. Evaluate it on retention CPA, not acquisition ROAS.
Channel has high Revenue % in New, low in Returning	It's an acquisition engine. Protect its budget; don't penalize it for low repeat purchase attribution.
Channel has roughly equal share in both	It's working across the full funnel.
Channel has high blended ROAS but almost all Returning	Blended ROAS is flattering — acquisition contribution is much weaker than the headline suggests.

This comparison is particularly important when reviewing performance with a media agency. Agencies typically report blended ROAS because it looks better. Showing the New vs. Returning split holds the reporting to a higher standard.

Common Questions

My retention ROAS is much higher than my acquisition ROAS — does that mean I should shift budget toward retention? Not necessarily. Retention campaigns reach customers who are already predisposed to buy again — they're cheaper to convert, which is why ROAS is higher. But you can only retain customers you've already acquired. Cutting acquisition budget to improve average ROAS by shifting toward retention is a short-term gain that shrinks your total customer base over time. Use Cohort Analysis to understand whether your existing customer base is large enough to sustain your revenue targets before reallocating acquisition spend.

Why does Email show $0 Ad Spend but high Revenue in returning customer attribution? Email is an owned channel — there's no direct ad spend associated with sends. LayerFive still attributes returning customer revenue to email touchpoints when a customer clicked an email link before purchasing. The ROAS and CPA columns will show 0 for email because there's no spend denominator, but the Orders and Revenue columns reflect real attribution contribution.

rMER is declining but my email and SMS metrics look fine — what else could explain it? rMER uses total ad spend as its denominator, including all paid channels. If your total paid spend has increased (even on acquisition campaigns), rMER will decline even if retention channel efficiency is unchanged. Check whether the decline in rMER correlates with a period of increased paid media investment overall.

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