Indian enterprises now buy web data the way they buy any other critical input: through procurement, legal review and an information-security questionnaire. Marketplace prices from Amazon.in and Flipkart, quick-commerce shelf data from Blinkit, Zepto and Swiggy Instamart, and restaurant data from Zomato and Swiggy all feed pricing, category and strategy decisions. The question reviewers ask first is simple: does this data carry personal data, and can the provider prove it does not?
Short answer: Web data vendor due diligence in India means checking that a provider collects only public business data (products, prices, stock, ranks, aggregate ratings), excludes personal fields by design, and backs this with a written data inventory, NDA, clear usage rights, retention rules, security controls, an SLA and an audit trail. The DPDP Act 2023 makes this review a board-level topic.
This guide explains the Digital Personal Data Protection Act and the DPDP Rules in plain words, shows where the line sits between public business data and personal data, and gives procurement and legal teams a ready checklist. It is not legal advice – speak to your counsel about your specific use case.
In our recent inquiries from India, enterprise buyers raise the same three topics before they agree to a trial: who owns and may use the delivered data, whether an NDA is in place, and whether any personal data could end up in the feed. That is a healthy sign. It means web data has moved from an analyst's side project into formal vendor onboarding.
The people involved usually include:
The Digital Personal Data Protection Act, 2023 (Act No. 22 of 2023) governs the processing of digital personal data – any data about an individual who can be identified by or in relation to that data. Organisations that decide why and how personal data is processed are "Data Fiduciaries"; vendors that process it on their behalf are "Data Processors". The individual is the "Data Principal".
The DPDP Rules, 2025 were notified by MeitY as G.S.R. 846(E) dated 13 November 2025 and announced in a PIB release. They apply in phases:
| Phase (per Rule 1 of the DPDP Rules 2025) | What comes into force | What it means for web data buyers |
|---|---|---|
| On publication – November 2025 | Rules 1, 2 and 17–21 (definitions and the Data Protection Board of India set-up) | The regulator exists; the clock on compliance has started. |
| One year after publication – November 2026 | Rule 4 (Consent Managers) | Mostly relevant to consumer-facing businesses, not to public business data feeds. |
| Eighteen months after publication – May 2027 | Rules 3 and 5–16, 22, 23 (notice, security safeguards, breach intimation, retention, children's data, Significant Data Fiduciaries and more) | Vendor contracts should already reflect security, breach and retention duties. |
In early 2026 MeitY consulted industry on shortening the 18-month window to 12 months (S.S. Rana & Co., February 2026). Check the latest gazette notifications with your counsel before you fix internal deadlines.
Three points matter most to a web data buyer:
Two older rules also appear in enterprise questionnaires. The IT Act 2000 remains India's core cyber law, and the CERT-In Directions of 28 April 2022 require covered entities to report specified cyber incidents within 6 hours and to keep ICT system logs for a rolling 180 days within India. Ask your provider how its incident and logging practices line up with these.
Most enterprise use cases – price monitoring, digital shelf analytics, assortment tracking, restaurant and menu intelligence, travel rate shopping – need no personal data at all. Risk only appears in a few specific fields. The table below is a practical starting point for your data inventory review.
In-body image 1: public-business-vs-personal-data-india.png – alt 'Table of web data types and their personal-data risk under India's DPDP Act'.
| Data type | Personal data risk | How a provider should handle it |
|---|---|---|
| Product listings – title, brand, pack size, MRP, images, category | None – product information | Collect; document source URL and timestamp. |
| Selling price, discount, coupons, bank offers | None – commercial terms | Collect; record the pincode or city used for the check. |
| Availability / out-of-stock by pincode or dark store | None – the pincode is a query location, not a person | Collect; use neutral test locations, never customer addresses. |
| Search rank and sponsored placements | None | Collect per keyword, platform and location. |
| Ratings and review counts | None – aggregate figures | Collect as numbers. |
| Review text | Medium – may contain reviewer names, profile links or details people write about themselves | Exclude reviewer names, IDs and photos; deliver de-identified text or aggregated themes only if the use case needs it. |
| Marketplace seller name | Low to medium – some sellers are sole proprietors | Keep the public business display name only; never phone numbers, personal emails or home addresses. |
| Restaurant listings – name, cuisine, menu, prices, rating, area | Low – business information | Collect business fields; exclude owner names and personal contact numbers. |
| Hotel and flight prices on OTAs such as MakeMyTrip | None – public rates | Collect rates, room or fare type, dates and taxes as displayed. |
| User profiles, customer photos, phone numbers, emails | High – personal data | Do not collect. A reputable provider will decline this scope. |
Coverage questions and compliance questions go together: the more platforms in scope, the more important a consistent field policy becomes.
| Platform | Typical enterprise data | Personal-data note |
|---|---|---|
| Amazon.in, Flipkart | Prices, discounts, bank offers, Buy Box seller, ratings, search rank | Seller display names only; exclude reviewer identities. |
| Blinkit, Zepto, Swiggy Instamart, BigBasket | Pincode-level price, availability, pack size, search rank, delivery time shown | Use test locations; no customer or delivery-partner data. |
| Zomato, Swiggy (food delivery) | Restaurant listings, menus, item prices, offers, ratings | Business fields only; exclude reviewer and owner personal details. |
| MakeMyTrip | Hotel and flight prices, availability, taxes and fees as displayed | Public rates only; no traveller data. |
For platform-specific detail, see our pages on quick-commerce data collection and Flipkart and Amazon India marketplace intelligence. Collection is limited to publicly visible pages, respects site terms and never involves logging in to accounts.
Use this table in your RFP or vendor questionnaire. Ask for evidence, not just a yes.
In-body image 2: web-data-vendor-checklist-india.png – alt 'Enterprise checklist for vetting a web data provider in India'.
| Area | What to ask | Good evidence |
|---|---|---|
| Data inventory | Which fields will you deliver, from which sources? | Field list with definitions, sample file, source list |
| Personal-data exclusion | Which fields are excluded, and how is that enforced? | Written exclusion list; QA rule that blocks personal fields |
| Collection method | Public pages only? Any logins or bypassing access controls? | Written statement: public pages only, no logins |
| Usage rights | What may we do with the data – internal use, client reports, models? | Usage clause in the MSA or order form |
| NDA and confidentiality | Will you sign our NDA before scoping? | Signed mutual NDA; your use case kept confidential |
| Retention and deletion | How long do you keep raw and delivered data? | Retention schedule; deletion on request or at contract end |
| Security | Encryption, access control, logging, backups? | Security summary mapped to Rule 6 themes |
| Incidents | How and how fast will you tell us about an incident? | Notification clause and named contact |
| Data location | Where is data stored and delivered? | Option to deliver into your own cloud bucket in the region you choose |
| SLA and QA | Freshness, delivery time, accuracy checks, re-runs? | SLA document; QA report on a sample |
| Audit trail | Can we trace each record to source and time? | source_url and captured_at on every row; crawl logs |
| Sub-processors and exit | Who else touches the data? What happens at exit? | Sub-processor list; exit and hand-over clause |
For the law from the data-team side, read our India DPDP Act and web scraping compliance guide and the GDPR, CCPA and DPDP ethical scraping checklist.
Actowiz Solutions delivers managed web data feeds, APIs and Actowiz Metrics dashboards for Indian brands, retailers, BFSI and consulting teams. For enterprise projects in India we typically provide:
No. The Act governs personal data. Public business data such as product prices, availability, search rank and aggregate ratings is not personal data. Confirm your specific use case with your counsel.
Section 3(c)(ii) excludes personal data made public by the individual or by someone legally required to publish it. Advisers read this narrowly, so reputable providers simply exclude personal fields.
Most obligations, including security safeguards and breach intimation, apply 18 months after the Rules were notified in November 2025, i.e. around May 2027. MeitY has consulted on shortening this, so check the latest gazette.
Only if it processes personal data on your behalf. If the feed contains no personal data, DPDP processor duties are largely not engaged, but security, NDA and contract terms still matter.
Ask your provider. A practical option is delivery straight into your own cloud bucket or warehouse in the region you choose.
An NDA, a field-level data inventory, usage-rights terms, a security summary and a sample on your own products or locations.
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