Beauty Industry Attribution Benchmarks: Are You Measuring What Matters?
Standard marketing attribution benchmarks for the beauty industry, such as ROAS and CAC, are often misleading because they are based on flawed, correlation-based models. The only benchmark that truly matters is incremental lift, and most brands aren't measuring it.
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By Joris van Huët, Founder & CEOUpdated 3 min read
The Problem with Benchmarks in the Beauty Industry
As a beauty brand, you are constantly bombarded with industry benchmarks. What's a good ROAS? What's a good CAC? What's a good conversion rate? While these benchmarks can be useful for context, they are often misleading and can lead to poor decision-making. The fundamental problem is that most benchmarks are based on traditional, correlation-based marketing attribution models.
Deconstructing Common Beauty Benchmarks
See also: ROAS Benchmarks: Meta Ads for Beauty
See also: Supplement Industry Benchmarks: The Metrics That Mislead
Let's take a closer look at some of the most common benchmarks in the beauty industry and why they are so problematic:
Return on Ad Spend (ROAS): This is perhaps the most widely used benchmark, but it is also the most misleading. A high ROAS can be a sign of efficient marketing, but it can also be a sign of channel cannibalization. If your branded search campaign has a 10x ROAS, it might just be capturing customers who were already looking for you. The true, incremental ROAS is likely much lower.
Customer Acquisition Cost (CAC): A low CAC is generally seen as a good thing, but it depends on the quality of the customer you are acquiring. If you are acquiring low-value, one-time buyers, a low CAC is not a sign of a healthy business. The focus should be on acquiring high-value, long-term customers, even if the initial CAC is higher.
Conversion Rate: A high conversion rate is great, but it doesn't tell the whole story. Are you converting new customers, or are you just converting existing customers who would have bought from you anyway? The focus should be on converting new, incremental customers.
The Illusion of Averages
Industry-wide benchmarks are often based on averages, which can be very misleading. Your brand is unique, and your benchmarks should be too.
The Only Benchmark That Matters: Incremental Lift
Instead of chasing misleading industry benchmarks, you should be focused on the only benchmark that truly matters: incremental lift. Incremental lift is the measure of how many sales you are generating that you would not have generated without a specific marketing activity. It is the true measure of your marketing effectiveness.
Incremental Lift = (Sales with Marketing Activity) - (Sales without Marketing Activity)
Measuring incremental lift is not easy. It requires a causal understanding of your marketing, which is something that traditional attribution models cannot provide.
| Feature | Traditional Benchmarking | Causality Engine |
|---|---|---|
| Focus | Industry averages | Your brand's specific performance |
| Methodology | Correlation-based | Causal Inference |
| Key Metric | ROAS, CAC | Incremental Lift |
Stop Comparing. Start Competing.
It's time to stop comparing your brand to misleading industry averages and start competing on what truly matters: incremental growth. It's time to embrace causal inference and build a data-driven marketing strategy that is tailored to your unique brand.
Explore our resources or view our pricing for more information.
Related Resources
Marketing Experiment Tracker: A/B Test Documentation Template
Audience Overlap Attribution Issue: Stop Paying Twice for the Same Customer
Go deeper: Causal attribution, explained.
Sixty-second versions of these ideas: Causality Engine on YouTube Shorts.
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Terms in this article
- AttributionAttribution identifies user actions that contribute to a desired outcome and assigns value to each. It reveals which marketing touchpoints drive 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.
- CausalityCausality is the relationship where one event directly causes another, essential for identifying specific actions that drive desired outcomes in marketing.
- ConversionConversion is a specific, desired action a user takes in response to a marketing message, such as a purchase or a sign-up.
- Conversion rateConversion Rate is the percentage of website visitors who complete a desired action out of the total number of visitors.
- CorrelationCorrelation is a statistical measure showing a relationship between variables; it does not imply causation.
- Customer acquisitionCustomer acquisition attracts new customers to a business. For e-commerce, this means driving the right traffic to the website.
- 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.