Fashion Attribution Benchmarks: The Numbers That Lie
Fashion brands are obsessed with benchmarks like ROAS and CAC, but these numbers are often dangerously misleading. Based on flawed, correlation-based attribution, they don't reflect true incremental value, leading to poor investment decisions in a hyper-competitive industry.
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By Joris van Huët, Founder & CEOUpdated 3 min read
In the fast-moving world of fashion ecommerce, brands are constantly looking for an edge. This has led to an obsession with marketing benchmarks. What is a good ROAS? What is an acceptable CAC? The problem is, the benchmarks everyone is chasing are built on a foundation of flawed marketing attribution data, making them not just useless, but actively harmful.
Deconstructing Fashion's Favorite Metrics
Let's examine the most popular benchmarks in the fashion industry and expose the hidden flaws:
A high ROAS on a branded search campaign, for example, is often just a measure of your brand's existing demand, not the effectiveness of the ad itself.
Are you acquiring a high-value customer who will make repeat purchases for years to come, or a one-time buyer who was lured in by a steep discount? A low CAC is meaningless without understanding the lifetime value of the customer.
Conversion Rate: A high conversion rate is always desirable, but it's important to understand what you are converting. Are you converting new customers who were introduced to your brand through your marketing efforts, or are you simply converting existing customers who were already planning to make a purchase?
The Vanity of Averages
The fashion industry is incredibly diverse, ranging from fast-fashion giants to niche luxury brands. The "average" benchmark is irrelevant to your specific brand, your specific customers, and your specific goals.
The Only Metric That Matters: Incremental Value
Instead of getting caught up in the vanity metrics that dominate the fashion industry, you should be focused on the one metric that truly matters: incremental value. Incremental value is the measure of the sales, revenue, and profit that you are generating on top of what you would have generated without your marketing efforts. It is the true measure of your marketing ROI.
Incremental ROAS = (Incremental Revenue) / (Ad Spend)
To measure incremental value, you need to move beyond correlation-based attribution and embrace a causal approach.
Causality Engine: Fashion Benchmarks
See also: Supplement Industry Benchmarks: The Metrics That Mislead
See also: Beauty Industry Attribution Benchmarks: Are You Measuring What Matters?
Causality Engine uses causal inference on the GA4 history you already have to estimate what each channel caused.
| Feature | Traditional Benchmarking | Causality Engine |
|---|---|---|
| Focus | Comparing to industry averages | Measuring your own incremental growth |
| Methodology | Correlation-based attribution | Causal Inference |
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Terms in this article
- Attribution SoftwareAttribution Software measures campaign impact by tracking customer interactions across touchpoints. It assigns value to each channel, showing what drives conversions.
- Causal InferenceCausal inference is the set of methods for estimating how much an outcome changes because of a cause, rather than alongside it. It works by comparing what happened with an estimate of what would have happened without the cause.
- Conversion rateConversion Rate is the percentage of website visitors who complete a desired action out of the total number of visitors.
- Data Driven AttributionData-Driven Attribution uses machine learning to analyze customer touchpoints and assign conversion credit. It determines the true impact of each marketing channel.
- Marketing AttributionMarketing attribution assigns credit to marketing touchpoints that contribute to a conversion or sale. Causal inference enhances attribution models by identifying true cause-effect relationships.
- Marketing ROIMarketing ROI (Return on Investment) measures the return from marketing spend. It evaluates the effectiveness of marketing campaigns.
- Vanity MetricVanity Metric is a data point that appears impressive but does not measure actual business success. It lacks a clear causal link to business objectives.
- Vanity MetricsVanity Metrics are measurements that look good but do not provide insight into business performance or aid decision-making. They do not reflect true impact.