Most large companies no longer want a one-off scrape. They want a dependable feed of prices, products, listings or reviews that lands in their warehouse every day, week or month for a full contract year – with someone accountable when a source changes.
Enterprise web data as a service is a managed, contracted supply of public web data: the provider builds and runs the collection, checks quality, watches for site changes and delivers clean files or an API on a fixed schedule, under a written SLA. You buy reliable, fresh, documented data, not scrapers to maintain.
This guide is written for data, strategy and procurement heads preparing an RFP or RFQ. It covers what a 12-month contract should include: delivery SLA, QA steps, uptime, change handling, service tiers, onboarding timeline, account management, security, usage rights, delivery formats and how to test a provider with a sample before you sign.
Data as a service (DaaS) means data is delivered on demand or on a schedule, while the supplier carries the cost of building and running the pipeline. For web data, that pipeline includes source discovery, extraction, anti-blocking, normalisation, QA, change monitoring and delivery.
The difference from a freelancer or a self-serve tool is accountability. A DaaS contract names what is delivered, when, at what quality, and what happens when it fails.
Who typically buys a recurring web data feed
In the RFPs we receive, the typical ask is a 12-month recurring feed across several countries and sources, with a clear SLA, named support and a sample before contract.
Use the table below as a checklist when writing or scoring an RFP. Each row is a question your provider should answer in writing.
| Contract element | What to ask for | Why it matters |
|---|---|---|
| Scope | Sources, countries, categories, fields, record volumes | Stops scope creep and unclear invoices |
| Cadence & freshness | Hourly / daily / weekly / monthly runs; delivery time window in your time zone | Data must arrive before the business uses it |
| Delivery SLA | % of deliveries on time per month, how it is measured and reported | The single best measure of reliability |
| Data quality | Field completeness and accuracy targets, QA method, sample audits | Prevents silent errors reaching dashboards |
| Change handling | Detection method, response time for broken sources, backfill policy | Websites change often; gaps are the main risk |
| Uptime (API feeds) | Monthly availability target, maintenance windows, status page | Only relevant if you pull data by API |
| Support | Named account manager, engineer, escalation path, business hours vs 24/7 | Who answers when something is wrong |
| Security | Certifications, access control, encryption, data retention | Required by most infosec reviews |
| Usage rights | Internal use, redistribution, use in client deliverables or AI models | Avoids legal surprises later |
| Change requests & exit | How new fields/sources are added; notice period; data hand-over | Keeps the contract flexible for 12 months |
Delivery SLA
A delivery SLA states what share of scheduled deliveries arrive on time and complete, measured each month. Ask how "on time" and "complete" are defined, and whether you receive a monthly SLA report.
Actowiz commitment: Confirm SLA with delivery team – enterprise-web-crawling-services.php currently states 99.5% on-schedule delivery measured monthly; confirm this applies to all recurring data feeds.
Uptime for API-based feeds
If you query data through an API rather than receiving files, uptime matters as much as delivery time. Ask for a monthly availability target, planned maintenance windows and a public or shared status page. Actowiz API uptime target.
How site changes are detected and fixed
Retailer and travel sites change layouts, add bot protection or move data behind new endpoints. In a recurring feed, the risk is not a crash – it is a run that "succeeds" with half the fields empty. Good change handling has four parts:
Quality assurance is where enterprise web data as a service providers differ most. Ask any vendor to show these steps on your own sample, not a demo dataset.
Accuracy target for your feed.
Enterprise feeds are usually priced on scope – number of sources, records, countries and refresh frequency – rather than on a fixed list price. The tiers below show how service levels typically grow with the contract. Exact pricing is quoted per project; see how to size a budget.
| Tier | Best for | Cadence | Support | Delivery |
|---|---|---|---|---|
| Pending | One team, a few sources, one or two countries | Weekly or daily | Shared support, business hours | CSV / JSON to S3 or SFTP |
| Pending | Several sources and countries, BI or warehouse use | Daily, some hourly | Named engineer + account manager | Files, API, warehouse loads |
| Pending | Multi-team, multi-region, annual contract | Hourly to monthly, mixed | Account manager, written SLA, escalation path Confirm 24/7 support scope | Any of the above + custom schema, Snowflake / BigQuery |
Annual contracts usually give better unit economics than month-to-month and allow capacity planning on both sides.
The right delivery method depends on who uses the data and how often. Most enterprise web data as a service programmes combine two: files for the warehouse and an API for applications.
| Method | Formats | Best for |
|---|---|---|
| Cloud storage (Amazon S3, Google Cloud Storage, Azure Blob) | CSV, JSON / JSONL, Parquet | Data lakes and scheduled warehouse loads |
| SFTP | CSV, XLSX, JSON | Teams with existing secure file transfer processes |
| REST API | JSON | Apps, pricing engines and on-demand look-ups |
| Data warehouse loads | Snowflake, BigQuery, Databricks tables | Analytics teams who want query-ready data |
| Webhooks / email notification | Run summary + file link | Triggering downstream jobs when data lands |
All formats and destinations above are listed on our enterprise web crawling. Ask for a written data dictionary with every field, type and example value; it should stay versioned for the life of the contract.
A realistic onboarding plan moves from requirement to stable production in a few weeks. The table shows a typical path; your plan depends on the number of sources and countries.
| Stage | What happens | Typical timing |
|---|---|---|
| 1. Scoping call | Sources, countries, fields, cadence, delivery method, usage | Week 0 |
| 2. Sample | Real records from your sources in your format | sample within 24 hours |
| 3. Data dictionary sign-off | Field list, matching rules, QA thresholds agreed | Pending |
| 4. Production build | Crawlers, QA rules, monitoring and delivery set up | enterprise crawling page states go-live in 5–10 business days |
| 5. Parallel run | First deliveries checked side by side with your team | 1–2 weeks |
| 6. Steady state | Scheduled delivery, monthly SLA report, quarterly review | Rest of the contract |
What a dedicated account manager does
Infosec and legal reviews often take longer than the technical pilot. Prepare the answers early.
Data from these feeds is meant to support pricing, assortment and market decisions. It is not legal advice; involve your own counsel for redistribution or AI-training use.
Building in-house makes sense for one or two stable sources and a team with spare engineering time. Once a programme spans many sources, countries and a 12-month horizon, maintenance, proxies, QA and on-call cover usually cost more than the extraction itself.
Buying enterprise web data as a service moves that work – and the accountability – to the provider. Score suppliers on the contract table above, ask for a sample on your own sources, and check how they report incidents. For a wider view of our services, see web scraping services (https://www.actowizsolutions.com/data-services.php).
It is a managed, contracted supply of public web data. The provider builds, runs, quality-checks and monitors the collection and delivers clean data on a fixed schedule under a written SLA, so your team uses data instead of maintaining scrapers.
Usually as the share of scheduled deliveries that arrive on time and complete in a calendar month. Ask how "complete" is defined (record counts, field fill-rates) and whether you get a monthly SLA report.
Automated checks flag drops in records or fields, engineers triage by severity, fix the extraction and backfill missed periods where the data is still available. You receive an incident note.
Yes. Annual contracts can cover any cadence from hourly to monthly, with scope, change-request and exit terms agreed upfront. [Confirm contract terms with sales]
CSV, JSON/JSONL, Parquet and XLSX, delivered to Amazon S3, Google Cloud Storage, Azure Blob, SFTP, Snowflake, BigQuery, Databricks or via REST API and webhooks.
Yes. We run a sample on your own sources and fields so you can test quality and format.
You can also reach us for all your mobile app scraping, data collection, web scraping, and instant data scraper service requirements!
Our web scraping expertise is relied on by 4,000+ global enterprises including Zomato, Tata Consumer, Subway, and Expedia — helping them turn web data into growth.
Watch how businesses like yours are using Actowiz data to drive growth.
From Zomato to Expedia — see why global leaders trust us with their data.
Backed by automation, data volume, and enterprise-grade scale — we help businesses from startups to Fortune 500s extract competitive insights across the USA, UK, UAE, and beyond.
We partner with agencies, system integrators, and technology platforms to deliver end-to-end solutions across the retail and digital shelf ecosystem.
Enterprise web data as a service: 12-month recurring feeds with delivery SLA, QA, site-change monitoring and API, S3 or SFTP delivery.
Sensitive Skin Skincare Product Data API helps brands track cleansers, serums, moisturizers, and sunscreens with structured product data.
German marketplace data report 2026: online retail size, Amazon.de, Otto, Kaufland and Zalando price signals, PAngV rules and peak seasons.
Whether you're a startup or a Fortune 500 — we have the right plan for your data needs.