LuxaDerme

From no reporting to sharp business visibility — turning numbers into decisions for a fast-growing beauty brand.

Accounts & FinanceMIS BuildChannel-Level ProfitabilityBusiness InsightsBeauty & SkincareK-Beauty DistributionD2C + Marketplaces
LuxaDerme case study
ReportedFirst Structured MIS Introduced
ProfitableChannel-Wise Profitability Across Amazon & Website
DiagnosedCOD-Driven Return Patterns Identified Through Data
ActionableData-Led Decisions on Marketing & Retention

Brand: LuxaDerme

Industry: Beauty & Skincare

Brego Solutions: Accounts, MIS & Financial Analysis

Operator-Led, Category-Focused Brand LuxaDerme was founded by Sol Malik under Valeo Nutra LLC in 2013 — with a focus on bringing technologically advanced skincare products to market. Coming from a background in technology, Malik transitioned into the beauty space with a clear focus on building a high-quality, innovation-led skincare portfolio. Over time, LuxaDerme established itself in the premium skincare segment, combining Korean formulations with clinically proven actives and distributing across D2C and marketplace channels in India. The business had momentum. What it lacked was visibility into what that momentum was actually translating into.

LuxaDerme had data — but no structured way to interpret it. There were no consolidated reports, no clear profitability views, and no system to track how orders were converting into actual revenue. This led to multiple blind spots: Channel profitability was unclear Marketing spends couldn’t be evaluated against outcomes Customer behaviour (repeat vs new) wasn’t being tracked meaningfully Returns were visible as a number — but not understood One of the biggest gaps sat inside order-level data. A large portion of orders were coming through COD — but there was no breakdown of: What percentage of these orders were getting delivered How many were being returned (RTO) Why those returns were happening Without this, revenue looked strong at the top — but leakages between order placement and final delivery were not being tracked clearly. The business wasn’t lacking information. It was lacking a system to connect the dots.

Brego focused on structuring the data first — and then using it to answer business-critical questions.

1. MIS & Reporting Framework Built from Scratch

Introduced a structured MIS covering: Revenue (gross to net breakdown) Returns, cancellations, and leakages Channel-wise performance Customer behaviour (new vs repeat) This became the base layer for all analysis going forward.

2. COD vs Prepaid Analysis Through Order-Level Data

Instead of treating returns as a single number, Brego broke them down through reconciliation and RTO tracking: Analysed Shopify reconciliation data to track the journey from order value → net sales Identified that RTO rates were consistently high (double-digit %) across months Layered this with RTO reason-level data, including: Customer refusal Customer unavailable Cash not ready at delivery Address issues This made one thing clear: A significant portion of returns was linked to COD behaviour — not product issues. By mapping: Order Type (COD vs prepaid) → RTO % → Net realised revenue, the team was able to quantify the real revenue loss happening post-order.

3. Channel-Wise Profitability Breakdown

Built profitability views across: D2C website Marketplace channels Factoring in: Discounts Commissions Logistics Returns This helped isolate where margins were being made vs eroded.

4. Marketing & Customer Behaviour Insights

Using MIS and P&L-level tracking, Brego identified: High marketing spends relative to realised (post-return) revenue Low repeat customer percentage compared to expected benchmarks for the category Drop-offs between gross orders and net sales This reframed how performance was being evaluated: Not just on order volume — but on converted, retained revenue.

5. Operational Gaps Highlighted

Data also surfaced process gaps contributing to inefficiency: Lack of structured order confirmation before dispatch No filtering mechanism for high-risk COD orders These were flagged as direct contributors to return rates and margin loss.

Once the data was structured, decisions became sharper and more grounded.

1. From No Reports to Structured Business Visibility

The business moved from fragmented data to a clear MIS covering revenue, returns, and profitability — giving leadership a consistent view of performance.

2. Return Rates Understood — Not Just Seen

Instead of treating returns as a lump sum, the team now understands: Where returns are coming from, Why they are happening, How they impact actual realised revenue. This creates a clear starting point for operational and payment-level decisions.

3. Channel-Level Profitability Clarity

Each channel is now evaluated on actual contribution — after commissions, logistics, and returns — enabling better allocation of spend and effort.

4. Smarter Marketing Decisions

With visibility into: Net vs gross revenue, Return-driven leakages, Repeat customer behaviour, marketing is now evaluated on efficiency, not just scale.

5. Business Decisions Backed by Data

From COD exposure to customer retention, the business now has a financial lens on decisions that were earlier instinct-driven.

Growth gives you data. Clarity tells you what to do with it.

What went live — creatives built, tested, and iterated based on performance.

Your books should be working better for you.

If your financial infrastructure hasn't kept pace with your growth, let's change that. At Brego Business, we start with what's broken, and start building what's next.

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