How to Score Pricing Intelligence Data Quality
A vendor-neutral framework — the CPAS score (Coverage, Precision, Accuracy, Staleness) — for evaluating pricing intelligence data from any provider, including Product Data Scrape, Bright Data, Oxylabs, or in-house pipelines.
Why Data Quality Needs a Standardized Score
Every pricing intelligence vendor claims "the best data" — but there's no standardized way to verify it. This whitepaper introduces CPAS: a vendor-neutral scoring framework covering Coverage, Precision, Accuracy, and Staleness. Use it to evaluate any vendor objectively before signing a contract.
Why This Matters Now
In 2026, pricing intelligence spending crosses $1.8B globally. Yet 68% of enterprise buyers report they can't objectively compare vendors on data quality — leading to buyer's remorse and $200K+ mistakes.
The Four Dimensions of Data Quality
CPAS breaks pricing intelligence data quality into four measurable dimensions, each scored 0-100. Composite CPAS score is the weighted average.
Coverage (25%)
What % of your target SKUs are actually captured across the promised marketplaces? Target: 95%+. Miss this and your competitive intel has blind spots.
Precision (25%)
When variants exist (500g vs 1kg pack), does the vendor match to the correct variant? Target: 98%+. Cross-variant confusion breaks pricing benchmarks.
Accuracy (30%)
When data is captured, is the value correct? Test with random spot-checks weekly. Target: 99%+. Anything less means bad decisions.
Staleness (20%)
How old is the "latest" data point? For pricing, staleness over 4 hours is unacceptable. Target: median < 90 min.
What Data Quality Scoring Actually Returns
Every Product Data Scrape Data Quality API call returns structured JSON. Here's what a live response looks like:
// Product Data Scrape — Data Quality Report API
// GET /v1/quality-report?vendor=self&window=30d
{
"vendor": "product_data_scrape",
"reporting_period": "2026-03-15 to 2026-04-15",
"cpas_score": {
"composite": 94.2,
"coverage": 96.8,
"precision": 98.4,
"accuracy": 99.1,
"staleness": 89.3
},
"test_stats": {
"skus_tested": 2400,
"variants_checked": 8940,
"median_staleness_min": 42
},
"tier": "production_ready"
}
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