Enterprise Web Scraping RFP Checklist (QA, SLAs, Compliance)

Download the complete, enterprise-ready RFP checklist (Excel format), including scoring columns, vendor response fields, and proof-point requirements you can use immediately with procurement and legal.

Enterprise_Web_Scraping_RFP_Checklist_Ficstar.xlsx

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Asking the right questions

In vendor evaluations, I often hear three requests in the first five minutes: pricing wants competitor prices, procurement wants security documentation, and engineering wants to know how we detect site changes before bad data hits production.

They’re all right. 

If you’re buying competitive pricing intelligence, you’re not buying “scraping.” You’re buying decision-grade data delivered on a cadence your business can trust, with an audit trail, clear service levels, and a compliance posture your legal team can review.

This article is built to be copy/paste-ready for an enterprise RFP, while still being practical enough that a pricing manager can use it the same day. It’s also written to help your procurement, legal, and engineering teams align on shared definitions before the first vendor pitch.

I’ll anchor the checklist around Ficstar’s internal definition of data quality, because in competitive pricing, how vendors define quality is usually where deals succeed or fail.

Who this checklist is for 

This checklist is for enterprise teams who rely on external web data to price, monitor, and compete, especially when pricing is dynamic, geo-dependent, or channel-specific.

Set Your Success Criteria First

Before you ask vendors anything, I recommend aligning internally on a few definitions. Otherwise, you’ll get confident-sounding answers that don’t match what your business actually needs.

1. Accuracy

Does the dataset match what a real user would see on the website in a defined scenario?Scenario examples: specific ZIP/postal code, desktop vs. mobile, pickup vs. delivery, selected variant, quantity, and whether fees/shipping are included.

2. Completeness

Did we capture all required records, and do we know exactly what’s missing and why?Mature vendors don’t just deliver rows; they deliver coverage accounting (what was captured, what failed, what was out-of-stock/unavailable, what was blocked).

3. Freshness / cadence

Is the data captured and delivered on the schedule the business needs (and can you prove it)?This includes timestamps, late-delivery handling, and the ability to run ad-hoc crawls for promotions (e.g., holiday pricing).

4. Reliability

Can you count on the pipeline to work repeatedly, with monitoring, incident response, and predictable change management?This is where SLAs, MTTD/MTTR, regression tests, and reporting matter.

Ficstar’s 5-pillar data quality model

When we evaluate our own work, we define “data quality” as five pillars:

1. Completeness: required records captured)

2. Accurate as on the website: matches what a user would see in the defined scenario)

3. Correct format / no malformations: schema-valid, clean types, normalized)

4. Detect changes and validate: catch site changes quickly; re-validate outputs)

5. Fulfills specs/requirements: agreed business rules and edge cases)

These pillars aren’t theory. They’re the practical backbone of high-scale pricing pipelines, including projects where teams monitor tens of thousands of SKUs across many competitors and locations.

Good read: What Clean Data Means in Enterprise Web Scraping?

RFP Checklist (copy/paste section)

Below is the structured framework your RFP should cover. The full downloadable version includes detailed questions, scoring fields, and proof-point requirements.

1) Data Scope & Coverage (Completeness)

Define:

• Sources, domains, channels (web, mobile, apps, APIs)

• Locations (ZIP/store/region)

• Cadence (daily, hourly, promo-triggered)

Vendors should clearly explain how they measure coverage, validate expected record counts, prevent duplicates, and report failure reasons per record.

2) Ground Truth & Validation (Accuracy as on Website)

Define what “price truth” means:

• List vs. sale vs. member vs. net

• Fees/shipping included or not

• Login state, region, quantity, variant

Vendors must explain how they quantify accuracy, their sampling methodology, audit artifacts (screenshots/cache/HTML), and how they validate cart/checkout pricing.

3) Formatting & Schema QA (No Malformations)

Require:

• Published schema

• Automated validation before delivery

• Integrity checks (duplicates, nulls, invalid values)

• Version control for schema changes

Your ingestion pipeline should never break because of avoidable formatting issues.

4) Change Detection & Regression Testing

Every website changes. Ask:

• How site changes are detected

• MTTD and MTTR targets

• Regression testing vs. prior deliveries

• Anomaly detection thresholds

• Evidence storage for debugging

You’re evaluating resilience, not just extraction capability.

5) Requirements Management (Spec Governance)

Look for:

• Written specs per source

• Defined approval workflows

• Edge-case handling (variants, bundles, sellers)

• Post-incident prevention updates

• Product matching methodology

This is what separates a managed partner from a scraping vendor.

6) SLAs & Reliability

Require clarity on:

• Delivery times and timezones

• Missed-delivery handling

• Incident response commitments

• Peak-period readiness

• Reporting cadence

Late data is often as damaging as inaccurate data.

7) Compliance & Legal Process

You’re not asking for legal opinions. You’re asking for:

• Documented compliance process

• Source review workflow

• Audit trail of decisions

• Defined controls and governance

Your counsel evaluates risk. The vendor provides process transparency.

8) Security & Access Controls

Confirm:

• Encryption (in transit + at rest)

• Role-based access

• Audit logging

• Credential handling

• Security incident procedures

Public data becomes sensitive once it informs pricing strategy.

9) Delivery & Integrations

Ensure support for:

• S3/SFTP/API/Warehouse

• Versioning and backfills

• Metadata per record

• Data lineage documentation

Operational clarity prevents downstream disputes.

10) Support & Escalation

Require:

• Named contacts

• Severity-based response targets

• Clear escalation path

• Structured incident workflow

• Proactive change communication

No black-box ticket queues.

11) Commercial Model

Demand transparency on:

• Pricing drivers

• Promo-run pricing

• What’s included vs. extra

• Scope expansion terms

Predictable cost structure matters more than lowest price.

12) Pilot Plan & Acceptance Criteria

A proper pilot should define:

• Scope

• Measurable acceptance criteria

• Validation method

• Timeline to production

If success isn’t measurable, it isn’t a pilot.

Vendor scoring rubric (how to compare providers)

Here’s a simple rubric procurement can run without ambiguity. Score each category 1–5, multiply by weight, and require “must-haves” for deal eligibility.

Category	Weight	What “5” looks like
Completeness	15%	Coverage accounting + error taxonomy + expected-count validation
Accurate as on website	15%	Scenario-defined truth + sampling + evidence artifacts (cache/screenshot)
No malformations (schema/format)	10%	Versioned schema + automated validation + integrity checks
Change detection & validation	15%	Regression tests + anomaly detection + measured MTTD/MTTR
Requirements management	10%	Written specs + change log + edge-case governance
SLAs & reliability	15%	Delivery SLA + incident workflow + reporting cadence
Compliance posture	10%	Documented process + review cadence + audit trail (counsel-friendly)
Security controls	5%	Encryption + access controls + audit logs
Support & escalation	5%	Named contacts + severity-based response times

Must-have gates (recommended)

• Written definition of accuracy and a sampling/audit plan

• Regression testing + anomaly detection

• Delivery SLA + escalation path

• Documented compliance process for counsel review

• Schema validation + integrity checks

6 Common vendor answers that should trigger follow-up questions

Vendors often answer RFPs with phrases that sound good but hide risk. Here are examples and the follow-ups I’d ask immediately:

1. Vague answer: “We ensure accuracy.”

   Follow-up: Define accuracy in your program. Is it field-level? Price vs. availability vs. fees? What sampling rate do you use, and what evidence do you store (cache/screenshot/HTML) for audits?

   
   

2. Vague answer: “We do QA.”

   Follow-up: What automated checks run pre-delivery (schema/type/duplicates)? What regression tests compare against prior runs? What percent is manually reviewed, and when do you do live-site spot checks?

   
   

3. Vague answer: “We detect changes quickly.”

   Follow-up: What are your MTTD/MTTR targets? Show an example of a change incident and how you prevented recurrence (new checks/spec update).

   
   

4. Vague answer: “We support geo pricing.”

   Follow-up: How do you select ZIPs/stores? How do you avoid false differences caused by session state, inventory, or shipping thresholds? How do you report location coverage?

   
   

5. Vague answer: “We can handle marketplaces.”

   Follow-up: Do you capture all sellers or just the top seller? How do you identify the lowest price vs. rank 1? How do you model fees, shipping, stock by seller?

   
   

6. Vague answer: “We’re compliant.”

   Follow-up: Describe your compliance process and controls (not legal conclusions). Who reviews new sources, what’s documented, and what’s the review cadence? We’ll validate with counsel.

Example RFP language

You can copy-paste these clauses directly into an RFP and let vendors mark “Comply / Partially / Does not comply.”

1) QA reporting clause

“Vendor will provide per-delivery QA reporting including: completeness metrics (expected vs. delivered counts by source/location), schema validation results, anomaly summaries (distribution shifts, missingness), and a record-level error taxonomy. Vendor will maintain evidence artifacts (e.g., cached pages or screenshots) for sampled validation.”

2) Change notification clause

“Vendor will notify Customer of detected source changes that materially impact data quality or delivery (e.g., DOM/API changes, anti-bot changes, flow changes) and provide an estimated recovery plan. Vendor will maintain a change log including detection time, remediation time, and prevention measures (new checks/spec updates).”

3) Delivery SLA clause

“Vendor will deliver datasets by [TIME] [TIMEZONE] on [CADENCE]. If delivery is missed, Vendor will (a) provide an incident report within [X] hours, (b) initiate rerun and remediation, and (c) provide service credits or other remedies as defined in the SLA.”

4) Incident response clause

“Vendor will support severity-based response targets, including named escalation contacts. Incident workflow will follow: identify → rerun → fix logic → prevent recurrence via updated checks/specs.”

5) Acceptance criteria clause (pilot)

“Pilot acceptance requires: (a) price-field accuracy ≥ [X]% under the defined scenario, verified by sampling with evidence; (b) completeness ≥ [Y]% for required records with documented reasons for gaps; (c) zero critical schema violations; (d) delivery punctuality ≥ [Z]%.”

Enterprise Web Scraping Done Right

Ready to submit an RFP for enterprise web scraping? Make sure your success criteria are clear, and your data partner is built for scale. Contact Ficstar today to request your free demo and see how a fully managed, SLA-backed data pipeline can deliver accuracy, completeness, freshness, and reliability you can trust.