Platform · Reliance Digital

Reliance Digital Data Scraping Services

Structured around obtainability rather than headline price, because the competitive question here is usually whether it arrives, not what it costs.

Reliance Digital data scraping is the automated collection of publicly visible Reliance Digital data organised around fulfilment — pincode serviceability, store-level stock, delivery and installation windows, and assortment differences by catchment — alongside price and offer fields.

Reliance Digital's proposition rests on reach. That makes the interesting dataset one about where a product is genuinely obtainable and how fast, rather than one more national price series.

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reliancedigital_fulfilment.jsonl LIVE FEED

{"reliance_sku":"4910* redacted","model_number":"WM-70* redacted", "pincode":"400058","catchment_tier":"metro", "is_ranged":true, "serviceable":true,"in_stock":true, "delivery_window":"2-3 days", "installation_available":true, "installation_chargeable":false, "store_stock_state":"in_stock", "listed_price":32990.00} {"reliance_sku":"4910* redacted", "pincode":"442401","catchment_tier":"tier_3", "is_ranged":true, "serviceable":true,"in_stock":true, "delivery_window":"9-12 days", "installation_available":false, "store_stock_state":"unknown"}

2 of 912,400 sku-pincode rowspanel includes tier-2 and tier-3 · schema v2.1

Independence and trademarks. Actowiz Solutions is not affiliated with, endorsed by or connected to Reliance Digital or its owners. Reliance Digital and related marks belong to their respective owners, used here only to name the publicly accessible source this service collects from.

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Reliance Digital at a glance

How we handle Reliance Digital specifically

Platform-specific handling, not a generic retail template pointed at a different domain.

Platform: Reliance Digital online, with store-level data where exposed
Built around: Fulfilment — serviceability, windows, installation
Geography: Pincode panel on your list, including tier-2 and tier-3
Assortment: Range differences by catchment, not a national list
Stock: Store-level state kept separate from shippability
Offers: Exchange, EMI and bank offers captured, aligned with Croma fields
Refresh: Daily standard; sub-daily on festive windows
Region: India

Platform specifics

What makes Reliance Digital data different

These are the reasons a Reliance Digital dataset needs its own handling rather than a shared retail schema.

Obtainability is the question, not price

For most electronics categories in India the national price gap between major retailers is narrow. What differs is whether a product can actually be got, where, and how quickly.

Serviceable but out of stock means the pincode is covered and the product is not there.
Not serviceable means the pincode is not covered at all, which is a network decision rather than a supply one.
Serviceable with a long window means it arrives, eventually, which for a replacement purchase is frequently the same as unavailable.
Serviceable but not installable means a television or appliance cannot complete its purchase journey.

These four states are distinct and each requires a different response. We keep them as separate fields rather than collapsing them into an availability flag, which would make all four look identical.

Assortment differs by catchment, and that is the finding

Range is not uniform across the network. A model ranged in metro catchments may be absent from tier-2 and tier-3 ones, and the reverse also happens where regional demand differs.

Collecting from a national catalogue view produces a range list that describes no actual catchment. We collect per pincode across a panel that deliberately includes tier-2 and tier-3 locations, because the metro-only view is the one already visible to everyone and the gap outside it is where the commercial question sits.

For brands, the useful output is usually a coverage map: in how many sampled catchments is your model listed, in stock, and installable — three different numbers that are routinely reported as one.

Delivery and installation windows are the real service measure

A stated delivery window is a commitment a retailer publishes and can be held to. Tracking it over time and across catchments produces a service-level series that is genuinely comparable between retailers, in a way stock flags are not.

We capture the stated delivery window and installation availability separately, per pincode, and record whether installation is included or chargeable where that is displayed. For large appliances this pair of fields frequently explains a share gap that price data cannot.

Offer fields aligned with Croma, deliberately

Reliance Digital and Croma compete directly, and clients almost always want them side by side.

The offer fields here — exchange value, no-cost EMI, bank offers, bundles — use the same names, the same conditionality structure and the same offer-path approach as our Croma collection, so the two can be compared without a reconciliation step.

The emphasis differs because the datasets answer different first questions: Croma collection is built around offer-stack complexity, this one around network reach. But the fields are aligned so a client taking both gets one comparable dataset rather than two that need joining.

Scope

What we collect on Reliance Digital, and what we do not

The right column matters more than the left. Anyone can list fields; the limits are what tell you whether the dataset will hold up.

✅ What we collect

pincode on every record, across a panel including tier-2 and tier-3
serviceable, in_stock, delivery_window and installation_available as four separate fields
Store-level stock state where the platform exposes it
Assortment per catchment, so range gaps outside metros are visible
Stated delivery window, tracked over time as a service-level series
Installation availability and whether it is included or chargeable
Listed price and MRP captured separately
Exchange, no-cost EMI and bank offer fields aligned with our Croma schema
effective_price per offer_path, with the path recorded
Reliance SKU, brand model number and EAN retained together
Rating, review count and review velocity

❌ What we do not, and why

Customer identities or any personal data
Anything behind a login, including cart-stage or account-specific pricing
Actual exchange quotes requiring device entry
Store-level stock where the platform does not expose it; absence is recorded as unknown, not as zero
Extended warranty or service quotes configured per order
Internal cost, margin or vendor terms

Core Reliance Digital fields

The full dictionary is agreed during scoping. These are the fields specific to this platform.

Field	What it is on this platform
reliance_sku / model_number / ean	The three identifiers, retained together
pincode / catchment_tier	Delivery pincode and whether it is metro, tier-2 or tier-3
serviceable	Whether the pincode is covered at all
in_stock	Stock state, separate from serviceability
delivery_window	Stated delivery time for this pincode
installation_available / installation_chargeable	Installation state, separate from delivery
store_stock_state	Store-level availability where exposed, unknown where not
listed_price / mrp	As displayed, captured separately
exchange_value_max / emi_no_cost / bank_offer_value	Offer fields, aligned with the Croma schema
offer_path / effective_price	Which combination was assumed, and the price under it
is_ranged	Whether the model appears in this catchment's assortment at all
captured_at	IST timestamp at minute precision

Use cases

What teams do with Reliance Digital data

Coverage mapping by catchment

Listed, in stock and installable reported as three separate numbers across a pincode panel that includes tier-2 and tier-3, rather than as one national availability figure.

Service-level benchmarking

Stated delivery windows tracked over time and across catchments give a comparable service measure between retailers, which stock flags cannot provide.

Range-gap analysis outside metros

Per-catchment assortment reveals where a model is absent from the range entirely, which a national catalogue view hides completely.

Side-by-side comparison with Croma

Aligned offer fields and identical conditionality structure mean both retailers can be analysed as one dataset without a reconciliation step.

The 24-hour sample — run on your sources, not ours

Send us a Reliance Digital item or category list. We run real collection against it and return the output within 24 hours, with the platform-specific fields populated so you can check them yourself rather than take our word for it.

Real extraction from your actual sources
Returned inside two business days
Coverage and QA note included
You keep the data either way
No card, no trial clock
Named engineer on the call

Get my free sample Book a 20-min scoping call Reply within one business day. Reference calls available under NDA.

How we engage

Three ways to engage us

Same collection pipeline and QA underneath. The difference is who holds the schedule and how the data reaches you.

Managed service (most common)

We own the collection, the QA and the delivery. You receive clean data on a schedule and never touch a scraper.

Dedicated engineer assigned to your account
Site changes fixed by us, not reported to you
Scheduled delivery to your warehouse or S3
Named contact on Slack or email

Best fit: Teams who need the data, not the infrastructure.

API access

The same collection pipeline exposed as an authenticated REST endpoint your systems query directly.

On-demand and scheduled endpoints
Rate limits agreed to your load profile
Sandbox keys for integration testing
Versioned schema with deprecation notice

Best fit: Product and engineering teams building on live data.

One-time or project extraction

A defined pull for a specific question — market sizing, diligence, a pitch, a one-off audit.

Fixed scope agreed in writing upfront
Single delivery with full QA report
Methodology documented for your records
Converts to managed if you want continuity

Best fit: Research, strategy and diligence work with a deadline.

Pricing

Every engagement is quoted individually, because the honest answer depends on your scope: how many sources, how many records, how often, and how the data reaches you. We scope it with you, run a free pilot on your own sources, and then quote a fixed monthly figure — no per-request metering and no overage billing when volumes move. Request a quote and you will have a number after one call.

Reliance Digital is usually collected alongside its competitors

Almost nobody buys a single platform in isolation. Reliance Digital data becomes useful when it sits next to the competitor set on one schema, refreshed on one schedule, so a price index or availability comparison is genuinely like-for-like.

That is what consumer electronics data covers, and a Reliance Digital-only engagement can be expanded into it without rebuilding. If you already know you need several platforms, start there instead — it is the same pipeline and usually the better scoping conversation.

FAQ

Reliance Digital data scraping: frequently asked questions

Platform-specific questions, including what cannot be collected here.

Because the two datasets answer different first questions. Croma's pricing complexity sits in its offer stack, so that collection is built around exchange, EMI and bank offers. Reliance Digital's proposition rests on reach, so this one is built around serviceability, stock, delivery windows and installation.

The offer fields are deliberately aligned across both, so a client taking both gets one comparable dataset rather than two needing reconciliation.

They are separate states and both are recorded. Serviceable means the pincode is covered by the network; in stock means the product is actually there.

A pincode that is not serviceable at all is a network decision; serviceable but out of stock is a supply situation. Collapsing them into one availability flag makes both unreadable and sends the wrong team after the problem.

Yes, and the panel is built to include them deliberately. The metro view is already visible to everyone; the gap outside it is where the commercial question usually sits.

Range, stock and delivery windows all differ by catchment tier, so catchment tier is a field rather than an afterthought.

It is recorded as unknown rather than as zero. Treating an absent field as an absence of stock is one of the easiest ways to produce a dataset that quietly understates availability.

Yes. The stated delivery window is captured on every record, so it becomes a service-level series per catchment.

Because it is a published commitment rather than an inferred figure, it is one of the few genuinely comparable service measures available between Indian electronics retailers.

See real Reliance Digital data before you commit to anything

Send us an item or category list. We return the output within 24 hours with the platform-specific fields populated.

Get a free sample Talk to an engineer

Free pilot, no card, no obligation. If we cannot collect a field you need on this platform, the sample shows you that too.

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