Foursquare vs Angi: 2026 Technical Comparison
Foursquare (BLD Score 83.5) targets the location / data market, while Angi (BLD Score 81.6) is built for the usa / home services audience — a difference that shapes which citation carries more weight for your entity. Angi holds the crawl-efficiency edge with faster indexation, so the right first listing comes down to your primary use case: category-specific authority versus raw discovery speed.
Technical Breakdown
| Metric | Foursquare | Angi |
|---|---|---|
| BLD Overall Score | 83.5/100 | 81.6/100 |
| Indexation Speed | 24 hrs | 24 hrs |
| Editorial Friction / Manual Vetting | Partial — hybrid review | Yes — strict manual vetting |
| Primary Target Industry | Location / Data | USA / Home Services |
| AEO Schema Readiness | 98/100 (Full JSON-LD) | 82/100 (Structured) |
| Listing Cost Model | Free / Premium | Paid |
| Knowledge Graph Linkage | High Node Authority | High Node Authority |
Which platform should you list on first?
Choose Foursquare if...
- Your business targets Location / Data — its audience matches that search intent directly.
- You prioritize schema/tech, where Foursquare scores highest.
- You want strong AEO schema readiness (98/100 (Full JSON-LD)) so generative engines parse your listing cleanly.
- You can invest the effort for a hybrid manual review to earn a higher-trust, harder-to-spam citation.
Choose Angi if...
- Your business targets USA / Home Services — its audience matches that search intent directly.
- You need fast citation pickup — Angi indexes in roughly 24 hrs.
- You can invest the effort for strict manual vetting to earn a higher-trust, harder-to-spam citation.
Our pick for most businesses
Foursquare (83.5/100)
The Multi-Node Strategy
In 2026, the strongest local SEO posture is not choosing one directory but stapling your entity across multiple high-trust nodes. Listing on both Foursquare and Angi creates two independent citations that corroborate the same Name, Address, and Phone data, and that redundancy is exactly what AI search engines look for when deciding whether a business entity is real and stable. Foursquare contributes schema/tech while Angi reinforces niche relevance, so the pair shores up each other's softer dimensions — traffic for Foursquare and nap sync for Angi. When Google and generative engines cross-reference these matching, structured citations, your Knowledge Graph node gains the confidence score that a single listing can never provide on its own.