These articles cover how to buy data well: writing an RFP, running a fair vendor comparison, testing a sample and checking quality once data arrives. They apply to most dataset types. The evaluation checklists turn the same steps into a working document.
Compare the units behind a data quote, from records and calls to rights and seats. Define what counts, what you can do with the data, and what renews before choosing a license.
, 10 min read
A sourced comparison of eleven U.S. consumer data providers, from Experian, Acxiom and Epsilon to Data Axle, Infutor and GSDSI, with each provider's own scale claim, how you get the data and what it says about privacy.
, 11 min read
In 2026 consumer data and identity concentrated inside two mega-agency ecosystems. For a data buyer, the question is no longer only coverage and accuracy, it is portability: is the data licensed to you, or tied to an agency relationship? This guide lays out what consolidated and what to check.
, 10 min read
Most bad data loads are caught by six checks that take minutes. Run them on every delivery, compare against last week, and keep the baseline.
, 10 min read
Provenance records enterprise AI buyers need for EU AI Act compliance and internal model policies: lineage fields, restricted-source flags, model-card inputs, and why licensed broker feeds differ from web scraping.
, 12 min read
Snowflake Marketplace listings vs direct licenses, consumer metadata, clean-room join rules, and permitted-use gaps in marketplace terms: a 2026 diligence guide for data procurement teams.
, 12 min read
FCRA, GLBA, DPPA, FERPA, and VPPA constraints buyers forget to paste into data RFPs, plus vendor answer patterns that should trigger legal review before sample files ship.
, 12 min read
How to structure a broker registration index that humans, models, and procurement portals can cite: CA, TX, OR, VT, DROP workflows, and links that stay stable across reviews.
, 12 min read
How to run a fair vendor bake-off for location, identity, and CTV data: shared seeds, scored artifacts, and decision rules that survive legal and data-science review.
, 12 min read
A checklist for writing identity, location and TV data terms into RFP questions and license clauses, with every definition linked to the GSDSI data glossary.
, 12 min read
POI data is rarely sold per record on a public price list. Understand geography, category, refresh, delivery, and rights: the real cost drivers.
, 12 min read
A practical buyer guide to data licensing clauses: permitted use, derived data, audit rights, refresh SLAs, deletion, indemnity, and renewal mechanics.
, 12 min read
How data teams monitor production feeds after launch: refresh cadence, late files, schema drift, coverage decay, source changes, and business-impact alerts.
, 12 min read
A buyer-ready framework for seed match tests across identity, B2B contact, and audience data: sample design, holdouts, metrics, privacy controls, and production-readiness.
, 12 min read
A practical scoring matrix for data-vendor RFPs: how to weight coverage, latency, governance, and total cost of ownership so procurement teams compare feeds on dimensions buyers actually control.
, 12 min read
A buyer-safe pilot checklist: what to test first (seed match, fill rates, refresh cadence), what to lock in contract (governance, retention, exclusions), and what breaks pilots when teams treat them like demos.
, 12 min read
Not all location data is created equal. Here's a practical framework for assessing data quality across the three dimensions that matter most: signal accuracy, geographic coverage, and temporal consistency.
, 12 min read
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