# Leading Beauty Brand Protected Over $50,000 in Margins During BFCM Using Landing-Page Based Discount
### **Overview**
A fast-growing DTC beauty brand—operating across the US and UK, and processing **15,000+ monthly orders**—wanted to run an aggressive BFCM promotion **without discounting their entire store**.
Instead of applying a blanket 30% discount to all visitors, they wanted a smarter system:\
👉 **Only shoppers who came from a designated BFCM landing page should see the deeper discount.**\
👉 Everyone else (organic, returning, direct traffic) should continue seeing their usual **10% offer**.
The goal was simple:\
**Drive conversions from paid campaigns while protecting margins everywhere else.**
***
## **The Challenge**
Most brands lose enormous margin during BFCM because:
* Every shopper sees the same discount
* Returning customers get unnecessary reductions
* Organic traffic gets the highest discount even when they would’ve paid full price
* Discount leakage can exceed 20–30% of total revenue
This brand wanted to avoid “storewide discount bleeding” and instead:
* Show BFCM offers **only** to ad-acquired visitors
* Keep full margins on all other shoppers
* Maintain a consistent, personalized customer journey
* Ensure the discount logic worked automatically with no manual effort
***
## **The Strategy**
The brand implemented **landing-page–based discount rules** using the Dollarlabs [offer engine](/dollarlabs-ultimate-discounts/offer-engine-formerly-price-lists.md).
#### The logic was simple:
* **If the shopper enters the site through the BFCM landing page → show 30% off everywhere.**
* **If the shopper enters through any other page → show only the standard 10% sitewide offer.**
This created two optimized shopping experiences running in parallel, without conflict:
#### **1. Standard Experience (All Visitors)**
* Saw a clean 10% discount
* No BFCM promotions applied
* Protected full-margin sales from organic & returning users
#### **2. BFCM Experience (Targeted Landing Page Visitors)**
* Saw 30% off banners, product pricing, and cart discounts
* Discounts persisted across product pages and reloads
* Ensured a smooth, high-intent conversion path for buyers coming from ads
In other words, the entire store adapted based on the shopper’s origin.\
No code changes. No theme edits. Zero manual overrides.
***
## **The Results**
Over a recent 30-day period, the brand saw substantial improvements across both margin protection and sales performance.
### **High-Level Performance Snapshot**
* **Gross Sales:** $686,000+ (↑ 51% YoY)
* **Total Sales:** $710,000+ (↑ 12% YoY)
* **Net Sales:** $593,000+ (↑ 9% YoY)
* **Orders Fulfilled:** 14,452 (↑ 301% YoY)
* **Returning Customer Rate:** 39.5%
#### **Discount Impact**
* Total discounts given: **$86,000**
* Discount leakage reduced by **52%**
#### **Margin Protected:**
> **Tens of thousands of dollars saved** by preventing deep discounts from being exposed to non-campaign visitors.
***
## **Why This Worked So Well**
#### **1. Stop Discounting Everyone**
Most BFCM setups discount all shoppers, whether they came through paid campaigns.\
This brand reversed that completely.
#### **2. Reward Only High-Intent, Paid Traffic**
Deep discounts were reserved exclusively for visitors acquired through ads and BFCM email flows.
#### **3. Protect LTV from Existing Customers**
Returning customers who didn’t need incentives kept buying at near-full margins.
#### **4. Seamless Customer Experience**
No coupon codes.\
No surprises in the cart.\
The offer matched the user journey perfectly.
#### **5. Set-and-Forget Automation**
The brand didn’t have to manually update banners, pricing, or conditions.\
The system handled everything dynamically.
***
## **The Bottom Line**
Instead of broadly discounting their entire store during BFCM, this brand took a **precision approach**:
* Target deeper discounts to only the right shoppers
* Avoid unnecessary revenue loss
* Scale paid acquisition efficiently
* Boost YoY sales across the board
**This is the future of discounting—personalized, conditional, and profitable.**
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