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A brand/enterprise client needing one flagship, cross-category q-commerce benchmark unifying shelf share, pricing, availability, discount depth, and dark-store variance across platforms and cities.

Report
India Q-Commerce State-of-Shelf
Region
India — multi-city
Scope
Multi-category, multi-platform
5
Signals Unified
Multi-Category
Coverage
Cross-Platform
& Multi-City
Recurring
Benchmark

Key Takeaways

Actowiz built a flagship India Q-Commerce State-of-Shelf benchmark that unifies five signals — digital shelf share, ₹-normalized pricing, out-of-stock rate, real discount depth (MRP vs selling), and dark-store assortment variance — across multiple categories, platforms, and cities. Rather than a single-category snapshot, it consolidates the same measurement discipline used in Actowiz's per-category studies into one recurring, comparable index. The result is a single source of truth for how brands actually perform on the q-commerce shelf — by category, platform, and geography — that pricing, distribution, and category teams can act on together.

What did the client need?

The client needed to stop looking at q-commerce performance one metric and one category at a time. Shelf share, pricing, availability, discounting, and distribution variance were each measured in isolation — but the real picture only emerges when they sit together, comparably, across categories, platforms, and cities.

Actowiz built a flagship State-of-Shelf benchmark that unifies five signals into one recurring index: digital shelf share, ₹-normalized pricing, out-of-stock rate, real discount depth (MRP vs selling), and dark-store assortment variance — consolidating the discipline of its per-category studies into a single source of truth.

What made this hard?

  • Signal fragmentation. Shelf share, price, OOS, discounts, and distribution variance lived in separate views and had to be unified comparably.
  • Cross-category normalization. Very different categories had to be measured on a consistent framework.
  • Multi-platform + multi-city. Platforms and cities each vary, demanding geo-accurate, comparable capture.
  • ₹-normalization across categories. Value metrics (₹/litre, ₹/wash, ₹/kg, ₹/unit) had to roll up into one benchmark.
  • Recurring consistency. As a benchmark, it had to be repeatable and trend-stable over time.

How did Actowiz solve it?

Actowiz consolidated its per-category measurement pipelines into one flagship, cross-category benchmark engine.

Approach
  • Unified signal model. Shelf share, pricing, OOS, discount depth, and dark-store variance computed on one framework.
  • Cross-category normalization. Category-appropriate ₹ metrics rolled up into comparable indices.
  • Geo-accurate capture. Platform × city × pincode capture for local truth.
  • Benchmark indexing. Signals combined into a State-of-Shelf index per brand/category/platform.
  • Recurring delivery. Repeatable cycle with dashboards and structured data for trend tracking.
Data Attributes Extracted
Attribute Description
Category / Brand / SKU Product hierarchy
Platform / City / Pincode Geo context
Shelf Share SKU count / share of listings
Normalized Price ₹/litre, ₹/kg, ₹/wash, ₹/unit (per category)
OOS % Out-of-stock rate
Discount Depth % Real MRP-vs-selling gap
Assortment Variance Dark-store coverage % vs baseline
Scrape Date Cycle date

What were the results?

  • One source of truth. All five shelf signals in one comparable, recurring benchmark.
  • Cross-team alignment. Pricing, distribution, and category teams working off the same index.
  • Category + geography cuts. Performance sliced by category, platform, and city.
  • Trend tracking. Movement over time across every signal, not one-off snapshots.
  • Flagship asset. A benchmark that consolidates and showcases the full measurement suite.

Project at a Glance

Metric Value
Report India Q-Commerce State-of-Shelf
Region India — multi-city
Scope Multi-category, multi-platform
Signals Shelf share, pricing, OOS, discount depth, dark-store variance
Granularity Category × platform × city × pincode
Cadence Recurring benchmark
Output State-of-Shelf index + dashboards + dataset

Client Feedback

"Every team was arguing off a different metric. The State-of-Shelf benchmark put shelf share, price, availability, discounts, and distribution variance in one place — now we all read from the same source of truth."

— VP Category & Revenue, Enterprise Brand

Frequently Asked Questions

Q: What is the State-of-Shelf benchmark?

A: A recurring, cross-category q-commerce index unifying five signals — shelf share, ₹-normalized pricing, out-of-stock rate, real discount depth, and dark-store assortment variance.

Q: Which signals does it combine?

A: Digital shelf share, normalized pricing, OOS %, MRP-vs-selling discount depth, and dark-store assortment variance.

Q: How is it comparable across categories?

A: Each category uses its appropriate ₹ metric, then rolls up into consistent indices for cross-category comparison.

Q: What granularity does it cover?

A: Category, brand, and SKU across platform, city, and pincode.

Q: How often is it produced?

A: On a recurring cadence, so every signal can be tracked as a trend over time.

Need a flagship q-commerce State-of-Shelf benchmark?

Actowiz Solutions builds unified, cross-category q-commerce benchmarks with rigorous QA. Visit actowizsolutions.com to discuss your data requirement.

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