diff --git a/CLAUDE.md b/CLAUDE.md
index 6344ab9..4a04885 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -50,9 +50,10 @@ plans/             # LinkedIn post drafts
     - **Basel Institute on Governance** — `baselgovernance.org/about/careers`. Each vacancy is a linked PDF, so there's no HTML description to language-check. The `rounded-3xl` card class is what separates vacancy tiles from the annual-report PDF link.
     - These boards use UN-flavoured titles ("Information Management Officer", "ICT Specialist") that `SOFTWARE_TITLE_RE` alone drops, so `INTL_TECH_RE` widens the net **for these sources only**. Boards this small can afford the noise; missing a rare opening can't.
   - **itjobs.ch** is swept Switzerland-wide (no `location` param) — the board is small, ~210 jobs over 7 pages, and locking it to Basel returned only ~9. It 404s one page past the end instead of serving an empty list. Each item embeds its full `description`, so the DE/FR check runs in-process via `isEnglishDescription` rather than costing a page fetch per job. Use `job_location.name` for location — it's the English form; the bare `location` field is German.
-- **`index.ts`** — orchestrator: loads existing IDs from `results/jobs.csv`, calls `fetchJobs`, calls `isEnglishContent` for each new job, appends survivors to CSV.
+- **`index.ts`** — orchestrator: loads existing IDs from `results/jobs.csv`, calls `fetchJobs`, calls `isEnglishContent` for each new job, appends survivors to CSV. Writes both `search` (the query/source that found the job) and `location` (the posting's own location, as parsed off its card by `fetch.ts`/`fetch-other.ts` — no extra page fetch) to the CSV. Migrates old CSVs on startup: adds `source` if missing, then `location` (backfilled `""` for rows written before the column existed).
 - **`recheck.ts`** — calls `fetchJobs(..., { raw: true })` to bypass `SOFTWARE_TITLE_RE`, then lists every new job that *would* be filtered out and prints word-frequency suggestions.
 - **`daily.ts`** — the notification layer on top of `index.ts`. Snapshots the CSV's links, shells out to `bun fetch`, then diffs to find what's new. Survivors are filtered through `matchesProfile` and grouped by area (Basel / Remote / Zürich / Bern) so the message scans on a phone. `results/sent.txt` is written **only after a successful send**, so a Telegram failure retries next run instead of silently losing jobs. A non-zero exit from `bun fetch` sends a failure notice rather than failing quietly.
+  - The area grouping matches against the CSV's `location` column (the posting's real location) first, falling back to `search` (the query/source label) only when `location` is empty — i.e. for rows written before the `location` column existed. This fixed two real mislabels: a LinkedIn "Bern" sweep can surface a job actually based in Lausanne (search label ≠ real location), and `fetch-other.ts` sources (job-room.ch, itjobs.ch, stellen-basel.ch, datacareer.ch) write the source name into `search` instead of a city, which used to dump their jobs into "⚪️ Other" regardless of where they actually were.
 - **`profile.ts`** — `matchesProfile(title, company, minScore = 4)`. Hard rejects run first (Microsoft stack, Java/C++/SAP, life-science, non-software functions, blocked companies Jobgether and ALLPS), then `SIGNALS` scores stack and seniority terms from `cv/polo.md`. This is a **second, stricter gate than the fetch filters**: `fetch.ts` decides what lands in the CSV, `profile.ts` decides what's worth a phone buzz. Widen `SOFTWARE_TITLE_RE` to catch more in the CSV; tune `SIGNALS`/`minScore` to change what gets sent.
 - **`telegram.ts`** — reads `.env` directly (no dotenv dep). Accepts `TELEGRAM_BOT` or `TELEGRAM_TOKEN` for the token. Splits at 3900 chars on line boundaries (Telegram hard-caps at 4096) and sleeps 400 ms between parts to stay under the rate limit. Messages are HTML — run titles/companies through `escapeHtml`.
 
@@ -150,6 +151,8 @@ Read `cv/polo.md` for the full profile. Key signals:
 
 Links use just the job ID as anchor text: `[4192954199](https://www.linkedin.com/jobs/view/4192954199/)`
 
+Some employers (Optiml, LocalBini seen repeatedly) repost the same role under a new job ID every few weeks rather than keeping one listing open. When several rows share the same title + company, show only the most recent job ID and drop the older duplicates from the table — they're the same opening, not new leads.
+
 ## Workflow: "find jobs in X city / remote / custom search"
 
 1. Write a temp script in `scripts/` with the right `SearchConfig` (city, workType, custom keywords).
diff --git a/daily.ts b/daily.ts
index 402e018..545dc64 100644
--- a/daily.ts
+++ b/daily.ts
@@ -11,7 +11,7 @@ const SENT = "./results/sent.txt"; // links already pushed — never resend
 const dry = process.argv.includes("--dry-run");
 const resend = process.argv.includes("--resend");
 
-type Row = { fetched: string; posted: string; search: string; title: string; company: string; link: string; source: string };
+type Row = { fetched: string; posted: string; search: string; title: string; company: string; link: string; source: string; location: string };
 
 function parse(text: string): Row[] {
   return text
@@ -20,7 +20,7 @@ function parse(text: string): Row[] {
     .filter(Boolean)
     .map((l) => {
       const c = l.replace(/^"|"$/g, "").split('","');
-      return { fetched: c[0], posted: c[1], search: c[2], title: c[3], company: c[4], link: c[5], source: c[6] };
+      return { fetched: c[0], posted: c[1], search: c[2], title: c[3], company: c[4], link: c[5], source: c[6], location: c[7] ?? "" };
     });
 }
 
@@ -60,13 +60,20 @@ if (!matched.length) {
   process.exit(0);
 }
 
-// Group by area so the message scans quickly on a phone.
+// Group by area so the message scans quickly on a phone. Match against the
+// posting's own location first — `search` is just the query that found it,
+// and recruiters/multi-site companies often post under a different area than
+// the job actually sits in (e.g. a "Bern" LinkedIn sweep surfacing a Lausanne
+// posting). Fall back to `search` only when no location was captured (rows
+// written before the location column existed).
 const area = (r: Row) => {
+  const loc = r.location.toLowerCase();
   const s = r.search.toLowerCase();
-  if (s.includes("remote")) return "🌍 Remote";
-  if (s.includes("basel")) return "🟢 Basel";
-  if (s.includes("zürich") || s.includes("zurich")) return "🔵 Zürich";
-  if (s.includes("bern")) return "🟣 Bern";
+  const text = loc || s;
+  if (s.includes("remote") || loc.includes("remote")) return "🌍 Remote";
+  if (text.includes("basel")) return "🟢 Basel";
+  if (text.includes("zürich") || text.includes("zurich")) return "🔵 Zürich";
+  if (text.includes("bern")) return "🟣 Bern";
   return "⚪️ Other";
 };
 const order = ["🟢 Basel", "🌍 Remote", "🔵 Zürich", "🟣 Bern", "⚪️ Other"];
diff --git a/index.ts b/index.ts
index ccfed76..0357580 100644
--- a/index.ts
+++ b/index.ts
@@ -5,16 +5,19 @@ import { fetchDataCareer, fetchStellenBasel, fetchItJobsCh, fetchJobRoom, fetchB
 
 const CSV = "./results/jobs.csv";
 const OLD_HEADER = "date_found,posted_at,search,title,company,link";
-const HEADER = "date_found,posted_at,search,title,company,link,source";
+const HEADER_NO_LOCATION = "date_found,posted_at,search,title,company,link,source";
+const HEADER = "date_found,posted_at,search,title,company,link,source,location";
 
-// Migrate CSV: add source column if the old header is present
+// Migrate CSV: add source column if the old header is present, then location
+// (the posting's real location, as parsed off its own card — distinct from
+// `search`, which is just the query that found it. See CLAUDE.md.)
 const csvExists = await Bun.file(CSV).exists();
 if (csvExists) {
   const raw = await Bun.file(CSV).text();
   if (raw.startsWith(OLD_HEADER + "\n") || raw === OLD_HEADER) {
     const lines = raw.split("\n");
     const migrated = [
-      HEADER,
+      HEADER_NO_LOCATION,
       ...lines.slice(1).map((l) => (l.trim() ? l + ',"linkedin.com"' : "")),
     ]
       .join("\n")
@@ -22,6 +25,20 @@ if (csvExists) {
     await Bun.write(CSV, migrated);
   }
 }
+{
+  const raw = await Bun.file(CSV).text().catch(() => "");
+  if (raw.startsWith(HEADER_NO_LOCATION + "\n") || raw === HEADER_NO_LOCATION) {
+    const lines = raw.split("\n");
+    const migrated = [
+      HEADER,
+      // Unknown for pre-existing rows — daily.ts falls back to `search` when empty.
+      ...lines.slice(1).map((l) => (l.trim() ? l + ',""' : "")),
+    ]
+      .join("\n")
+      .replace(/\n+$/, "") + "\n";
+    await Bun.write(CSV, migrated);
+  }
+}
 
 // Load existing links for deduplication
 const existingLinks = new Set<string>();
@@ -68,7 +85,7 @@ for (const config of searches) {
       console.log("ok");
       existingLinks.add(job.link);
       newRows.push(
-        [date, job.postedAt, config.label, job.title, job.company, job.link, "linkedin.com"]
+        [date, job.postedAt, config.label, job.title, job.company, job.link, "linkedin.com", job.location]
           .map(csvCell)
           .join(",")
       );
@@ -117,7 +134,7 @@ for (const { label, fetch: fetchFn } of extraSources) {
       }
       existingLinks.add(job.link);
       newRows.push(
-        [date, job.postedAt, job.search, job.title, job.company, job.link, job.source]
+        [date, job.postedAt, job.search, job.title, job.company, job.link, job.source, job.location]
           .map(csvCell)
           .join(",")
       );