A home-care FMCG brand needing price-per-wash benchmarking across powder, liquid, and bar detergents for the top 10 companies, normalized across q-commerce platforms.

Industry

FMCG • Home Care / Detergents

Region

India

Formats

Powder • Liquid • Bar

Top 10

Detergent Companies

Formats Compared

₹/Wash

Normalized Metric

Cross-Platform

Q-Commerce

Contact Sales

Key Takeaways

Actowiz benchmarked the top 10 detergent companies across q-commerce by normalizing every SKU to price-per-wash across powder, liquid, and bar formats. Because these formats are dosed differently and span many pack sizes, raw pack price is not comparable; only ₹ per wash reveals true value. Using a consistent washes-per-pack basis per format and size, Actowiz produced a cross-format, cross-platform view of detergent value that exposed real value gaps hidden by headline pricing — giving the client an honest, like-for-like read on where its per-wash value stood against every major competitor.

What did the client need?

The client is a home-care FMCG brand that needed to compare detergent value the way consumers experience it — not by pack price, but by price-per-wash. Across powder, liquid, and bar formats and multiple pack sizes, headline prices are meaningless without normalization.

Actowiz tracked the top 10 detergent companies across q-commerce platforms and normalized every SKU to a price-per-wash figure, enabling true cross-format and cross-platform comparison.

What made this hard?

Format incomparability. Powder, liquid, and bar are dosed differently — raw price tells you nothing about value per wash.
Pack-size sprawl. Each format spans many pack sizes, all needing a common per-wash basis.
Wash-count basis. A defensible washes-per-pack assumption was needed per format to compute price-per-wash.
Top-10 company set. Many brands and sub-brands across 10 companies had to be mapped and tracked.
Cross-platform consistency. Pricing had to be captured uniformly across platforms for fair benchmarking.

How did Actowiz solve it?

Actowiz built a detergent-specific pricing pipeline with a price-per-wash normalization layer across all three formats.

Approach

Company & brand mapping. All SKUs mapped to their brand and parent company across the top 10.
Format tagging. Every SKU tagged powder / liquid / bar.
Price-per-wash model. Pack price divided by an agreed washes-per-pack basis per format/size.
Cross-platform capture. Uniform price capture across q-commerce platforms.
Comparison outputs. Price-per-wash tables by company, format, and platform.

Data Attributes Extracted

Attribute	Description
Company / Brand	Parent company and detergent brand
SKU / Product	Product title and pack size
Format	Powder / Liquid / Bar
Pack Size	Weight or volume
Price	Listed price
₹ per Wash	Normalized price-per-wash
Platform	Source q-commerce platform
Scrape Date	Cycle date

What were the results?

True value comparison. Price-per-wash revealed real value gaps hidden by pack pricing.
Cross-format insight. Powder vs liquid vs bar compared on one honest metric.
Competitive positioning. Clear view of where the client's per-wash value stood vs the top 10.
Pricing decisions. Data-backed input for pack architecture and promo strategy.

Project at a Glance

Metric	Value
Industry	FMCG • Home Care / Detergents
Region	India
Scope	Top 10 detergent companies
Formats	Powder, liquid, bar
Metric	Price-per-wash (₹/wash)
Coverage	Multiple q-commerce platforms
Output	Benchmarking dataset

Client Feedback

“Comparing a powder pack to a liquid bottle never made sense until Actowiz put everything in price-per-wash. Suddenly the whole category lined up on one number we could actually act on.”

— Category Head, Home-Care FMCG Brand

Frequently Asked Questions

Q: What is price-per-wash?

A: Pack price divided by the number of washes a pack delivers — a comparable value metric across powder, liquid, and bar.

Q: Why not compare pack prices directly?

A: Formats are dosed differently and pack sizes vary, so pack price hides real value; ₹/wash normalizes it.

Q: How many brands were tracked?

A: The top 10 detergent companies, across their brands and sub-brands.

Q: How often is the data refreshed?

A: On a recurring cadence for ongoing price-per-wash benchmarking.

Need a custom data pipeline for your category?

Actowiz Solutions designs custom, large-scale scraping and market-intelligence pipelines with rigorous QA. Visit actowizsolutions.com to discuss your data requirement.

Real Results from Real Clients

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1 min

★★★★★

"Actowiz Solutions offered exceptional support with transparency and guidance throughout. Anna and Saga made the process easy for a non-technical user like me. Great service, fair pricing!"

Thomas Galido

Co-Founder / Head of Product at Upright Data Inc.

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2 min

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