How Actowiz built a flagship, cross-category q-commerce benchmark — unifying digital shelf share, ₹-normalized pricing, out-of-stock rate, real discount depth, and dark-store assortment variance — into one recurring State-of-Shelf view across platforms and cities.
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.
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.
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.
Actowiz consolidated its per-category measurement pipelines into one flagship, cross-category benchmark engine.
| 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 |
| 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 |
"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
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.
A: Digital shelf share, normalized pricing, OOS %, MRP-vs-selling discount depth, and dark-store assortment variance.
A: Each category uses its appropriate ₹ metric, then rolls up into consistent indices for cross-category comparison.
A: Category, brand, and SKU across platform, city, and pincode.
A: On a recurring cadence, so every signal can be tracked as a trend over time.
Actowiz Solutions builds unified, cross-category q-commerce benchmarks with rigorous QA. Visit actowizsolutions.com to discuss your data requirement.
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