diff --git a/duplicate_checker.py b/duplicate_checker.py
index 05de2aab..a57a4ad5 100644
--- a/duplicate_checker.py
+++ b/duplicate_checker.py
@@ -1,4 +1,4 @@
-# duplicate_checker.py (v2.5 - Final Hybrid Approach)
+# duplicate_checker.py (v2.2 - Multi-Key Blocking & optimiertes Scoring)
 
 import logging
 import pandas as pd
@@ -7,19 +7,11 @@ from config import Config
 from helpers import normalize_company_name, simple_normalize_url
 from google_sheet_handler import GoogleSheetHandler
 from collections import defaultdict
-import time
 
 # --- Konfiguration ---
 CRM_SHEET_NAME = "CRM_Accounts"
 MATCHING_SHEET_NAME = "Matching_Accounts"
-SCORE_THRESHOLD = 85 # Zeigt nur Treffer an, die diesen Score erreichen oder übertreffen
-
-# Erweiterte Liste von generischen Wörtern, die für das Blocking ignoriert werden
-BLOCKING_STOP_WORDS = {
-    'gmbh', 'ag', 'co', 'kg', 'se', 'holding', 'gruppe', 'industries', 'systems', 'technik', 'service', 
-    'services', 'solutions', 'management', 'international', 'und', 'germany', 'deutschland', 'gbr', 
-    'mbh', 'company', 'limited', 'logistics', 'construction', 'products', 'group'
-}
+SCORE_THRESHOLD = 85 # Etwas höherer Schwellenwert für bessere Präzision
 
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
@@ -30,9 +22,9 @@ def calculate_similarity_details(record1, record2):
     if record1.get('normalized_domain') and record1['normalized_domain'] != 'k.a.' and record1['normalized_domain'] == record2.get('normalized_domain'):
         scores['domain'] = 100
     
+    # Höhere Gewichtung für den Namen, da die Website oft fehlt
     if record1.get('normalized_name') and record2.get('normalized_name'):
-        # Wir verwenden token_sort_ratio für eine gute Balance zwischen Wortreihenfolge und Inhalt
-        scores['name'] = round(fuzz.token_sort_ratio(record1['normalized_name'], record2['normalized_name']) * 0.85)
+        scores['name'] = round(fuzz.token_set_ratio(record1['normalized_name'], record2['normalized_name']) * 0.85)
 
     if record1.get('CRM Ort') and record1['CRM Ort'] == record2.get('CRM Ort'):
         if record1.get('CRM Land') and record1['CRM Land'] == record2.get('CRM Land'):
@@ -42,18 +34,28 @@ def calculate_similarity_details(record1, record2):
     return {'total': total_score, 'details': scores}
 
 def create_blocking_keys(name):
-    """Erstellt Blocking Keys aus allen signifikanten Wörtern eines Namens."""
+    """Erstellt mehrere Blocking Keys für einen Namen, um die Sensitivität zu erhöhen."""
     if not name:
         return []
-    # Filtere Stop-Wörter und sehr kurze Wörter (z.B. '&') aus der Wortliste
-    significant_words = {word for word in name.split() if word not in BLOCKING_STOP_WORDS and len(word) > 2}
-    return list(significant_words)
+    
+    words = name.split()
+    keys = set()
+    
+    # 1. Erstes Wort
+    if len(words) > 0:
+        keys.add(words[0])
+    # 2. Zweites Wort (falls vorhanden)
+    if len(words) > 1:
+        keys.add(words[1])
+    # 3. Erste 4 Buchstaben des ersten Wortes
+    if len(words) > 0 and len(words[0]) >= 4:
+        keys.add(words[0][:4])
+        
+    return list(keys)
 
 def main():
-    start_time = time.time()
-    logging.info("Starte den Duplikats-Check (v2.5 - Final Hybrid Approach)...")
+    logging.info("Starte den Duplikats-Check (v2.2 mit Multi-Key Blocking)...")
     
-    # ... (Initialisierung und Laden der Daten bleibt gleich) ...
     try:
         sheet_handler = GoogleSheetHandler()
     except Exception as e:
@@ -79,8 +81,7 @@ def main():
 
     logging.info("Erstelle Index für CRM-Daten zur Beschleunigung...")
     crm_index = defaultdict(list)
-    crm_records = crm_df.to_dict('records')
-    for record in crm_records:
+    for record in crm_df.to_dict('records'):
         for key in record['block_keys']:
             crm_index[key].append(record)
     
@@ -98,7 +99,9 @@ def main():
             for crm_record in crm_index.get(key, []):
                 candidate_pool[crm_record['CRM Name']] = crm_record
         
-        # Brute-Force-Vergleich innerhalb des intelligenten Blocks
+        if not candidate_pool:
+            logging.debug("  -> Keine Kandidaten im Index gefunden.")
+        
         for crm_record in candidate_pool.values():
             score_info = calculate_similarity_details(match_record, crm_record)
             if score_info['total'] > best_score_info['total']:
@@ -126,8 +129,5 @@ def main():
     else:
         logging.error("FEHLER beim Schreiben der Ergebnisse ins Google Sheet.")
 
-    end_time = time.time()
-    logging.info(f"Gesamtdauer des Duplikats-Checks: {end_time - start_time:.2f} Sekunden.")
-
 if __name__ == "__main__":
     main()
\ No newline at end of file