GlowUp Cosmetics Case Study - D2C Beauty Brand

How a fast-growing D2C beauty brand turned unprofitable growth into sustainable margins with AI-powered pricing and promotion optimization.

Company Overview

GlowUp Cosmetics is a digital-first beauty brand founded in 2020, selling skincare and makeup products through their website and marketplaces. With a focus on clean beauty and sustainability, they've built a loyal customer base through social media marketing and influencer partnerships.

SKUs

₹8Cr

ARR

100%+

YoY Growth

The Challenge

GlowUp was the classic "growing but losing money on every order" D2C story. Despite triple-digit growth, profitability remained elusive.

Aggressive Discounting Habit

To compete with established beauty brands, GlowUp ran promotions constantly. Buy-one-get-one, 30% off sales, first-order discounts — customers had been trained to wait for deals. The average discount rate crept up to 28% of MRP.

No Visibility into Promotion ROI

The marketing team could tell you CAC and conversion rates, but couldn't answer basic questions: Which promotions actually made money? Were we cannibalizing full-price sales? What's the right discount depth?

Slow, Gut-Feel Decisions

Pricing and promotion decisions took weeks of debate between marketing, finance, and founders. By the time a decision was made, the market had moved.

"We were so focused on growth metrics — CAC, LTV, conversion rate — that we forgot the basics: are we making money on each order? Spoiler: we weren't."

— Priya Sharma, Co-founder & CEO, GlowUp Cosmetics

The Solution

GlowUp implemented Decisio with a laser focus on margin improvement:

1. Price Elasticity Discovery

Astra analyzed GlowUp's sales data to understand true price sensitivity for each product. Surprising findings emerged:

Hero products were inelastic — customers would buy at higher prices
Entry products needed competitive pricing to drive trial
Bundle pricing was leaving significant money on the table

2. Promotion ROI Analysis

Pulse analyzed every promotion from the past year to calculate true ROI, accounting for:

Incremental sales vs sales that would have happened anyway
Cannibalization of full-price sales before and after promotions
Customer quality: were promo customers coming back?

3. Optimal Discount Recommendations

Instead of blanket discounts, Decisio recommended product-specific promotions with the right depth and duration to maximize profit, not just revenue.

Key Discoveries

40% of promotions had negative ROI

More than a third of discounts actually lost money when accounting for margin erosion

Best-sellers didnt need discounts

Top 5 products had near-zero elasticity — customers bought regardless of price

Smaller, targeted discounts worked better

15% off to high-intent customers beat 30% off to everyone

Timing mattered more than depth

Thursday evening promos converted 40% better than weekend

Results After 4 Months

Margin Improvement

3.2% improvement in gross margin — from 42% to 45.2%
Average discount rate reduced from 28% to 18%
Revenue per order increased by ₹85

Promotion Effectiveness

85% improvement in promotion ROI
Negative-ROI promotions eliminated entirely
Promo frequency reduced by 40% with same revenue

Decision Velocity

Decision time from 2 weeks to 2 hours
Clear data-backed recommendations ended debates
Team now runs quick experiments with AI guidance

"We thought we needed more marketing budget. Turns out we needed smarter pricing. The same revenue now comes with 3% more in our pocket. That's the difference between burning runway and building a real business."