> ## Documentation Index > Fetch the complete documentation index at: https://docs.tryprofound.com/llms.txt > Use this file to discover all available pages before exploring further. # Citation Share and volume over time > Build the daily owned-domain Citation Share line and the daily total citation volume — both from a single API call. The Citation Share tile has two views: a daily **share** line (your owned-domain Citation Share over time, with the previous-period overlay) and a daily **volume** count. Both come from the **same** API call — group by `["date", "root_domain"]`, request `count` and `citation_share`, then derive each series from the response. **Don't average daily rows to derive a period score** — they're computed differently. See [Conventions & gotchas](/cookbook/setup/conventions#don%E2%80%99t-average-daily-rows-to-get-a-period-score). ## How this example works 1. **Group by `["date", "root_domain"]`.** Each row is one (day, domain) pair with its own `count` and `citation_share`. 2. **Derive both series in one pass over the response**: * **Daily volume** = sum of `count` across all rows for each date. * **Daily owned-domain share** = sum of `citation_share` across rows whose `root_domain` is in your owned set, per date. (Per-AI-model averaged, same as the headline tile.) 3. **Repeat for the prior window** to get the overlay line. ```python Python theme={null} import os from datetime import date, timedelta from urllib.parse import urlparse from collections import defaultdict from profound import Profound client = Profound(api_key=os.environ["PROFOUND_API_KEY"]) # What to fetch — replace with your own values. CATEGORY_NAME = "" DAYS = 7 INCLUSIVE_END = date(2026, 5, 11) # the last day of your current window def normalize(host_or_url): """Strip scheme, www, and trailing slash so domains compare cleanly.""" p = urlparse(host_or_url if "://" in host_or_url else f"https://{host_or_url}") return (p.hostname or "").replace("www.", "").rstrip("/") def get_owned_domains(category_id): """All domains across assets flagged is_owned in the category.""" out = set() for a in client.organizations.categories.assets(category_id): if not a.is_owned: continue if a.website: out.add(normalize(a.website)) for d in a.alternate_domains or []: out.add(normalize(d)) return out def get_daily_citations(category_id, owned_domains, start, end): """One call → both daily volume and daily owned-domain share. Returns [(date, volume, owned_share), ...] sorted by date. """ res = client.reports.citations( category_id=category_id, start_date=start.isoformat(), end_date=end.isoformat(), metrics=["count", "citation_share"], dimensions=["date", "root_domain"], date_interval="day", filters=[{"field": "prompt_type", "operator": "is", "value": "visibility"}], pagination={"limit": 50000, "offset": 0}, ) m = res.info.query["metrics"] d = res.info.query["dimensions"] i_count = m.index("count") i_share = m.index("citation_share") i_date = d.index("date") i_domain = d.index("root_domain") volume_by_day = defaultdict(int) owned_share_by_day = defaultdict(float) for row in res.data: day = row.dimensions[i_date] domain = normalize(row.dimensions[i_domain]) volume_by_day[day] += int(row.metrics[i_count]) if domain in owned_domains: owned_share_by_day[day] += row.metrics[i_share] return sorted( ( (day, volume_by_day[day], owned_share_by_day[day]) for day in volume_by_day ), key=lambda p: p[0], ) def current_and_prior_windows(inclusive_end, days): """Two (start, end_exclusive) pairs of equal length, back-to-back.""" current = ( inclusive_end - timedelta(days=days - 1), inclusive_end + timedelta(days=1), # +1 day → exclusive end ) prior = (current[0] - timedelta(days=days), current[0]) return current, prior def find_category_id(name): """Return the UUID of the category whose name matches (case-insensitive).""" for c in client.organizations.categories.list(): if c.name.lower() == name.lower(): return c.id raise ValueError(f"No category named {name!r}") # Resolve name → ID, then run both windows. category_id = find_category_id(CATEGORY_NAME) owned = get_owned_domains(category_id) current, prior = current_and_prior_windows(INCLUSIVE_END, DAYS) current_rows = get_daily_citations(category_id, owned, *current) prior_rows = get_daily_citations(category_id, owned, *prior) print(f"{'Date':<12} {'Volume':>8} {'Owned share':>14}") print("Current period:") for day, volume, share in current_rows: print(f" {day:<10} {volume:>8} {share:>13.1%}") print("\nPrevious period:") for day, volume, share in prior_rows: print(f" {day:<10} {volume:>8} {share:>13.1%}") ``` ```bash curl theme={null} export PROFOUND_API_KEY=your_api_key_here # Current window curl -X POST "https://api.tryprofound.com/v1/reports/citations" \ -H "X-API-Key: $PROFOUND_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "category_id": "your-category-uuid", "start_date": "2026-05-05", "end_date": "2026-05-12", "metrics": ["count", "citation_share"], "dimensions": ["date", "root_domain"], "date_interval": "day", "filters": [{"field": "prompt_type", "operator": "is", "value": "visibility"}], "pagination": {"limit": 50000, "offset": 0} }' # Previous window — same body, prior dates. curl -X POST "https://api.tryprofound.com/v1/reports/citations" \ -H "X-API-Key: $PROFOUND_API_KEY" \ -H "Content-Type: application/json" \ -d '{ "category_id": "your-category-uuid", "start_date": "2026-04-28", "end_date": "2026-05-05", "metrics": ["count", "citation_share"], "dimensions": ["date", "root_domain"], "date_interval": "day", "filters": [{"field": "prompt_type", "operator": "is", "value": "visibility"}], "pagination": {"limit": 50000, "offset": 0} }' ``` ## Common follow-ups The single-number KPI above the chart, plus its period-over-period delta. Every cited domain ranked by share, with the per-row pp delta column.