Vol. 01 — AI Citation IndexAugust 2026
Citation/Research

Who does AI cite when people ask? We measure it — industry by industry.

US Real Estate / Markets / Los Angeles

Los Angeles, CA

AI Citation Index · Metro edition № 001 · July 2026

National index →

412 prompts anchored in LA County — from ‘is Silver Lake good for families’ to ‘typical down payment in Los Angeles’ — each run five times on five AI engines. Los Angeles is the most neighborhood-driven market we track.

412

Local prompts

Locally-sourced corpus

10,300

Answer runs

5 per prompt per platform

27,914

Citation events

±1.5 pp

95% confidence margin

01

The sources AI trusts in Los Angeles

Blended citation share — top 15 cover 67% of events

Zillowzillow.com13.1%
Redditreddit.com8.9%
Redfinredfin.com8.2%
Realtor.comrealtor.com7.5%
LA Timeslatimes.com6.9%
YouTubeyoutube.com3.4%
Homes.comhomes.com3.1%
Apartments.comapartments.com2.8%
LAistlaist.com2.6%
Curbedcurbed.com2.2%
The Agencytheagencyre.com1.9%
RentCaferentcafe.com1.7%
City of LAlacity.org1.5%
Rodeo Realtyrodeore.com1.2%
Douglas Ellimanelliman.com1.1%

Linked sources have national profiles. The LA tail is long — 1,274 unique domains cited vs 1,912 nationally.

02

The local players

Brokerage & agent segment — 4,186 citation events

#BrokerageSegment citation shareΔ Jun
1The Agencytheagencyre.com
8.4%
+0.9 pp
2Compasscompass.com
7.1%
+0.3 pp
3Rodeo Realtyrodeore.com
4.2%
+0.2 pp
4Douglas Ellimanelliman.com
3.8%
+0.6 pp
5Hilton & Hylandhiltonhyland.com
3.1%
-0.1 pp
6Coldwell Bankercoldwellbanker.com
2.7%
-0.2 pp
7Sotheby's Int'l Realtysothebysrealty.com
2.4%
8Keller Williamskw.com
1.8%
+0.1 pp
9Berkshire Hathaway HSbhhscalifornia.com
1.5%
-0.1 pp
10eXp Realtyexprealty.com
1.2%
+0.4 pp

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03

What Angelenos ask AI

Share of local prompt corpus by intent

412local prompts
  • Neighborhood & lifestyle31%
  • Relocation & moving22%
  • Buying & financing18%
  • Market data & sentiment15%
  • Agent & professional finding14%

More than half of LA prompts are about where to live, not how to buy — neighborhood character, safety, commute, schools. That intent shape is why local media and Reddit out-muscle the portals here, and why city-level content underperforms.

The agent-finding segment (14%) is the most commercially valuable slice — and the least served by brokerage websites. It resolves to profiles and reviews, not domains.

04

Los Angeles vs the national baseline

Citation share by source class

Local media & neighborhood press11.5% / 2.8%
Community & video12.3% / 8.9%
Portals & marketplaces29.4% / 33.2%
Local brokerages4.2% / 2.1%
Government & civic1.4% / 3.5%
Los Angeles National baseline

Read the gaps as opportunity: local media at 4× the national share means AI engines are hungry for LA-specific authority. Local brokerages doubling their national share means the same. The sources AI can't find locally, it invents nationally.

05

Findings

July 2026

  1. Finding 01

    The unit of citation is the neighborhood, not the city

    Prompts naming a specific neighborhood — Silver Lake, Highland Park, Manhattan Beach — draw 2.6× more local sources than city-level prompts, which resolve to portals. In LA, a brand that only exists at city level barely exists at all.

  2. Finding 02

    Local media punches far above its weight

    latimes.com, laist.com and curbed.com together capture 11.5% of LA citation events — four times the local-media share we measure nationally. Housing-crisis and tenant-rights coverage is the engine, and the Curbed LA archive shows evergreen local content has a citation half-life of years.

  3. Finding 03

    Brokerages win through profiles, not websites

    Agent-finding prompts ('best realtor in Pasadena') resolve to Yelp, Google, Reddit and portal agent pages 78% of the time; a brokerage's own domain appears in just 6% of those answers. Visibility flows through platforms — which makes profile and review presence the actual battleground.

  4. Finding 04

    The portal tax is lower here

    Portals take 29.4% of LA citations versus 33.2% nationally. LA's fragmented geography pulls answers toward local media, community threads and neighborhood-level data. That fragmentation is the opening for every local player in this index.

06

Method & reuse

The Los Angeles corpus was built from LA-County query demand — neighborhood names, relocation patterns, rent-control and wildfire-insurance questions included. Same protocol as the national index: frozen prompts, five runs per platform, deterministic extraction, ±1.5 pp at 95% confidence.

Methodology →

Underlying dataset

citations.csv27,914 rows

prompts.csv412 rows

domains.parquet1,912 domains

methodology.pdf14 pages

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