Industry: Market Intelligence & Infrastructure Research
Altman Solon and their strategic research teams requiring granular, ground-truth infrastructure data to model market penetration and competitive displacement.
Problem
Strategic consulting for the telecom sector often encounters a coverage-visibility gap: service availability cannot be verified efficiently through manual spot checks alone.
Data Fragmentation: Coverage information was distributed across 10+ provider portals with different interfaces and address-validation flows.
Scaling Challenge: The agreed scope covered 181,000+ postcodes across 10 ISPs, representing nearly 2 million potential data points.
Access Constraints: Provider sites apply rate limits and other access controls that must be respected in the collection design.
Data Fragmentation: Coverage information was distributed across 10+ provider portals with different interfaces and address-validation flows.
Scaling Challenge: The agreed scope covered 181,000+ postcodes across 10 ISPs, representing nearly 2 million potential data points.
Access Constraints: Provider sites apply rate limits and other access controls that must be respected in the collection design.
- Temporal Change: Infrastructure coverage changes over time, so the client needed a repeatable, governed update process.
Solution
A client-authorized infrastructure intelligence pipeline designed for large-scale data collection and status normalization within an agreed legal and technical scope.
Authorized Collection: Used documented APIs where available and permitted browser workflows only where authorized by the client and applicable terms.
Request Governance: Applied rate limits, controlled scheduling, session management, and logging appropriate to each approved source.
Priority Queueing: Processed high-priority providers first while scheduling the broader approved provider list.
Normalization: Converted permitted provider responses into a standardized Serviceability Matrix.
Authorized Collection: Used documented APIs where available and permitted browser workflows only where authorized by the client and applicable terms.
Request Governance: Applied rate limits, controlled scheduling, session management, and logging appropriate to each approved source.
Priority Queueing: Processed high-priority providers first while scheduling the broader approved provider list.
Normalization: Converted permitted provider responses into a standardized Serviceability Matrix.
- Compliance Boundary: Collection methods were required to follow the agreed scope and applicable robots.txt, Terms of Service, contractual restrictions, and data-protection requirements.
Tech Stack
- Automation: Headless Browser Orchestration (Playwright / Selenium)
- Backend: Python (Asynchronous Data Pipeline)
- Intelligence: Custom NLP for address-match verification and status classification
- Infrastructure: Distributed task queues with per-source rate limits and scheduling
- Delivery: Normalized JSON/CSV optimized for GIS and BI tool integration
Results
- Scale: Processed 1.8M+ data points across 181,000+ postcodes and 10 ISPs, delivering the priority providers first.
- Data-Driven Strategy: Replaced coverage estimates with data collected directly from provider availability checks.
- Repeatable Partnership: The modular code made quarterly refreshes of the dataset possible without a rebuild.
- Operational Intelligence: Standardized data from 10 ISPs into one format, so the client’s analysts no longer had to reconcile it by hand.