FB/IG Audience Reach (manual)

What It Is

The Meta Marketing API Reach Estimate endpoint returns the estimated monthly active audience size for any geographic area — how many Facebook/Instagram users are active in that location, optionally filtered by age, gender, and interests.

This gives us real online population per area, not census headcounts. For a digital marketing pitch, “there are 45,000 active social media users in your area aged 25-54” is far stronger than “the census population is 62,000”.

API Details

Endpoint

GET /act_{AD_ACCOUNT_ID}/reachestimate

Key Parameters

Parameter	Description
targeting_spec.geo_locations	Country, region, city (by key), or coordinates + radius
targeting_spec.age_min / age_max	Age range filter (default 18-65+)
targeting_spec.genders	1=male, 2=female
targeting_spec.interests	Interest targeting (e.g. home improvement, legal services)
optimize_for	IMPRESSIONS (recommended for audience sizing)

Example: Audience size for Cork city (15km radius)

curl -G \
  --data-urlencode 'targeting_spec={
    "geo_locations": {
      "cities": [{"key": "{CORK_KEY}", "radius": 15, "distance_unit": "kilometer"}]
    },
    "age_min": 25,
    "age_max": 54
  }' \
  -d 'optimize_for=IMPRESSIONS' \
  -d 'access_token={TOKEN}' \
  https://graph.facebook.com/v25.0/act_{AD_ACCOUNT_ID}/reachestimate

Response

{
  "data": {
    "users_lower_bound": 142000,
    "users_upper_bound": 167000,
    "estimate_dau": 95000,
    "estimate_mau": 155000,
    "estimate_mau_lower_bound": 142000,
    "estimate_mau_upper_bound": 167000
  }
}

Getting Irish City Keys

Use the Targeting Search API to look up city keys:

curl -G \
  -d 'type=adgeolocation' \
  -d 'location_types=["city"]' \
  -d 'q=Cork' \
  -d 'country_code=IE' \
  -d 'access_token={TOKEN}' \
  https://graph.facebook.com/v25.0/search

Returns city keys like {"key": "1005423", "name": "Cork", "region": "County Cork", ...}.

What You Need

1. Meta Business Account with an ad account (any existing FCR ad account works)
2. System User Token with ads_read permission (doesn’t need ads_management — we’re only reading estimates, not creating ads)
3. Approved Facebook App — create via developers.facebook.com, request ads_read in App Review

Cost: Free. The Reach Estimate API has no per-call cost. Rate limits are generous (200 calls per hour per ad account).

Data Collection Strategy

Phase 1: County-Level Baseline

Query once for each of the 26 Irish counties:

• Total audience (18-65+)
• By age bracket: 18-24, 25-34, 35-44, 45-54, 55-64, 65+
• By gender: male, female

That’s 26 counties × 8 age/gender combos = 208 API calls (well within rate limits).

Phase 2: Town-Level for Key Markets

For the ~150 towns/cities already in our area intelligence data:

• Total audience with 10km radius
• Age 25-54 (primary commercial audience)

~150 API calls.

Phase 3 (Optional): Interest-Based Audiences

For top FCR categories (Electrician, Plumber, Solicitor, etc.), query interest-based audiences per county:

• “Home improvement” interests in Cork
• “Legal services” interests in Dublin
• “Auto repair” interests in Galway

This shows the prospect how many people in their area are actively interested in their category.

Integration Architecture

BQ Table

CREATE TABLE `listingmanager-1529856313699.fcr_operations.facebook_reach_estimates` (
  location_type STRING,        -- 'county' or 'city'
  location_name STRING,        -- 'Cork', 'Dublin', 'Naas'
  location_key STRING,         -- Meta city/region key
  radius_km INT64,             -- NULL for county, 10-15 for city
  segment STRING,              -- 'all', 'male_25_34', 'female_35_44', 'interest_home_improvement'
  estimate_mau INT64,          -- Monthly active users (midpoint)
  estimate_mau_lower INT64,
  estimate_mau_upper INT64,
  estimate_dau INT64,          -- Daily active users
  collected_date DATE,
  latitude FLOAT64,            -- For city-level (join to map)
  longitude FLOAT64
);

Data Collection Script

New script: data/map/pull_facebook_reach.py (or .js)

• Reads Meta API token from env
• Loops through counties + towns
• Queries Reach Estimate API for each segment
• Outputs NDJSON for BQ load (or calls dashboard-bq-execute INSERT)

S3 / Map Data

New file: facebook_reach.json — uploaded to S3 alongside existing area data.

{
  "counties": {
    "Cork": {
      "total_mau": 385000,
      "age_25_54_mau": 210000,
      "male_mau": 185000,
      "female_mau": 200000,
      "dau": 260000
    }
  },
  "cities": {
    "Cork": { "radius_km": 15, "total_mau": 155000, "age_25_54_mau": 88000 },
    "Naas": { "radius_km": 10, "total_mau": 32000, "age_25_54_mau": 18000 }
  }
}

Prospect-Intel Integration

Add to prospect-intel.js Phase 1 parallel calls (alongside existing area intelligence):

// Facebook reach estimate for the locality
internal("dashboard-bq-execute", {
  sql: `SELECT segment, estimate_mau, estimate_dau
    FROM \`${DS}.fcr_operations.facebook_reach_estimates\`
    WHERE LOWER(location_name) LIKE LOWER("%${countyEsc}%")
    AND location_type = 'county'`
}, env)

Add to response under areaIntelligence:

areaIntel.facebook_reach = {
  total_mau: 385000,
  age_25_54_mau: 210000,
  _note: "Monthly active Facebook/Instagram users in this area. Use for pitch: 'There are 210,000 active social media users aged 25-54 in Cork — that's your addressable digital audience.'"
};

Skill / Proposal Integration

In prospect proposals, add a section:

Digital Audience: {county}
- {total_mau} monthly active social media users
- {age_25_54_mau} aged 25-54 (primary commercial audience)
- That's {pct}% of the census population actively online

The ratio of Facebook MAU to census population is itself a powerful metric — it tells you how “digitally active” an area is.

Area Map Integration

Add Layer 7 to the Leaflet.js map: Digital Audience Density

• Overlay Facebook MAU at county level as a choropleth
• Or at town level as proportional circles
• Color by MAU-to-census ratio (digital penetration)

Refresh Schedule

Quarterly. Facebook audience sizes shift slowly — seasonal variation exists (summer dips, Q4 peaks) but month-to-month changes are small. Quarterly collection keeps it current without burning API calls.

This aligns with the existing area data refresh cadence:

• Census 2022: static
• Valuation/CRO: annual
• New builds: quarterly (NDQ07)
• Facebook reach: quarterly (new)

Comparison with Existing Data

Data Source	What It Measures	Granularity	Freshness
CSO Census 2022	Total population, demographics	Small Area (~100 HH)	Static (2022)
Pobal Index	Deprivation/affluence score	Electoral Division	Static (2022)
CRO Companies	Active businesses	County + NACE sector	Annual
Valuation Office	Commercial properties	Individual property	Annual
CSO New Builds	Housing completions	Eircode routing key	Quarterly
Facebook Reach	Active online users	County / City+radius	Quarterly

The Facebook data fills a gap none of the other sources cover: how many people in an area are reachable through digital channels. Census tells you who lives there. Facebook tells you who’s online there.

Implementation Steps

Step	Owner	Effort
1. Create Meta System User + get ads_read token	Cathal (Meta Business Manager)	30 min
2. Look up Irish city keys via Targeting Search API	Script	1 API call per town
3. Build pull_facebook_reach.py collection script	Claude	Medium
4. Create BQ table + initial load	Claude + BQ console	Small
5. Add facebook_reach.json to S3 pipeline	Claude	Small
6. Add to prospect-intel.js response	Claude	Small
7. Update prospect skill + Ro.am system prompt	Claude	Small
8. Add map layer (optional)	Claude	Medium

Blocker: Step 1 — need the Meta API token. Everything else is straightforward once the token exists.