Web scraping compliance for enterprises comes down to five things your reviewers must be able to sign off: the data is publicly available, personal data is excluded or lawfully handled, your intended use (internal analysis, display, caching, resale) fits the source's rights, retention and security are documented, and both sides are bound by an NDA and, where needed, a DPA.
Those five points come straight from the written questions we receive. In recent enterprise inquiries – from consulting firms, FMCG and beverage multinationals, large retailers and travel companies – procurement, legal and information-security teams asked before any trial: Can we display product titles and images in our app? Can we cache the data? Is it public data only? How long do you keep it? Will you sign our NDA and complete our security questionnaire?
This guide walks through each question, what reviewers are really checking, and the evidence a credible web data vendor should hand over. Use it as a due-diligence checklist whether you work with Actowiz or anyone else.
For a large company, buying web data is a third-party risk decision, not just a data decision. The data may flow into pricing systems, investor reports, customer-facing apps or AI models, so several teams must approve the vendor.
Good web scraping compliance for enterprises is therefore a shared file of answers, not one signature. Settling these questions in writing before a pilot avoids the common pattern where a successful trial stalls for weeks in legal review.
These are the questions that appear most often in enterprise security questionnaires and contract redlines we receive. The table shows what each reviewer is really checking and the evidence to request.
| # | Question reviewers ask | What they are really checking | Evidence to request |
|---|---|---|---|
| 1 | Is this public data only? | No logins, paywalls or private areas bypassed | Written scope: sources, pages, fields; statement on logged-out collection |
| 2 | Is any personal data collected? | GDPR / UK GDPR / CCPA / DPDP exposure | Field list showing no personal data, or a PII-filtering and minimisation note |
| 3 | Can we display titles, prices and images? | Copyright, trademarks and site terms | Usage-rights discussion with your counsel; vendor's position in writing |
| 4 | Can we cache or store history? | Database rights, retention limits | Agreed retention period and archive format |
| 5 | Can we resell or redistribute the data? | Licence scope | Contract clause defining permitted use |
| 6 | How long does the vendor keep our data? | Retention and deletion | Retention policy; deletion on request / at contract end |
| 7 | Will you sign our NDA and DPA? | Confidentiality of requirements and outputs | Signed mutual NDA; DPA if personal data is in scope |
| 8 | Which security controls and certifications do you have? | Vendor security posture | Certificate copies with scope and expiry; questionnaire answers |
| 9 | Where is the data processed and stored? | Data residency, sub-processors | Hosting regions and sub-processor list |
| 10 | What happens if a source changes or objects? | Continuity and takedown handling | SLA, change process, takedown / opt-out procedure |
"Public data" means information any visitor can see without logging in, paying, or getting around a technical barrier. For most enterprise projects – product prices, availability, ratings counts, menu items, hotel rates, store locations – that is exactly the data needed.
A defensible public-data scope usually includes these commitments:
Actowiz's position: we collect publicly available business data – prices, catalogues, availability, listings – and we do not take on projects to collect personal data of private individuals. Our privacy policy states that our systems "actively discourage and filter out the harvesting of Personally Identifiable Information (PII)".
Within web scraping compliance for enterprises, usage rights are the question legal teams care about most and the one vendors answer least clearly. The key point: a data vendor can deliver data, but it cannot grant rights it does not own. Product images, descriptions and logos usually belong to the brand, retailer or photographer; facts such as a price or a stock status are treated differently from creative content in most legal systems.
In the EU, collections of data can also be protected by the sui generis database right under Directive 96/9/EC, which can restrict extracting or re-using a substantial part of a database (https://eur-lex.europa.eu/eli/dir/1996/9/oj). Site terms of use add a contractual layer. That is why the intended use matters as much as the collection method.
| Intended use | Typical reviewer concern | Practical approach to discuss with counsel |
|---|---|---|
| Internal analytics and dashboards | Lowest-risk use; data stays inside the company | Most enterprise price, assortment and availability projects sit here |
| Displaying product titles and prices in an app | Site terms; database rights in the EU | Display factual fields; link back to the source; avoid copying full catalogues wholesale |
| Displaying product images | Copyright in photographs; trademarks | Use image URLs or brand-supplied/licensed assets; get counsel sign-off. Actowiz does not supply licensed image datasets or IP indemnity for images |
| Caching and keeping price history | Retention, database right | Agree retention period; store derived metrics rather than full page copies where possible |
| Reselling or redistributing raw data | Licence scope, database right | Usually needs a specific legal review; derived insights carry less risk than raw dumps |
| Training AI / ML models | Copyright, personal data, emerging AI rules | Exclude personal data; document sources; follow regulator guidance such as the UK ICO's generative AI consultation response |
Our practical advice to buyers is to state the intended use in the statement of work. It lets both sides design the dataset around it – for example, delivering image URLs instead of image files, or weekly derived price indices instead of full raw history.
If no personal data is collected, GDPR largely falls away for the dataset itself. Most price, catalogue and availability projects are designed that way. When personal data is unavoidable – for example, the public name of a business owner on a listing – reviewers will look at three things.
Security reviewers want evidence, not adjectives. These are the items to ask any vendor for, with Actowiz's current position.
Enterprise reviewers often ask whether web scraping is legal. The honest answer is that it depends on what is collected, how, where, and what you do with it. A few reference points are widely cited:
Web scraping compliance for enterprises should not slow a project down. We aim to make the compliance review as short as the technical pilot. A typical enterprise onboarding runs like this:
Collecting publicly available, non-personal business data is common practice, and in hiQ v. LinkedIn the US Ninth Circuit held that scraping public pages was unlikely to breach the CFAA. But legality depends on the source's terms, the data collected, the country and your use. Have your counsel review your specific use case; this guide is not legal advice.
Factual fields such as titles and prices are lower risk than images, which are usually protected by copyright. Many buyers display factual data with a link back and use brand-licensed images. Confirm your display plan with legal counsel before launch.
No, not by default. We collect public business data such as prices, catalogues and availability, and we do not collect personal data of private individuals. Where a public business contact is unavoidable, it is excluded unless your counsel approves a lawful basis.
Yes. We sign mutual NDAs before detailed requirements are shared, and our privacy policy states that DPAs are offered to enterprise clients.
Our privacy policy states that we do not keep long-term repositories of client-extracted data; output is delivered to you when each workflow finishes.
Our privacy policy states ISO 27001 certification for information security management.
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