diff --git a/input/input.txt b/input/input.txt
index 25fa3f7..b3e8480 100644
--- a/input/input.txt
+++ b/input/input.txt
@@ -1 +1,3 @@
-Your input data here
+CUSTOMER,NEW,2024-01-01,customer1,ch,Dallas,TX
+SITE_VISIT,NEW,2023-01-05,customer1,tag1,tag2
+ORDER,NEW,2021-01-10,customer1,100
diff --git a/output/output.txt b/output/output.txt
index 9e38a14..6cb933a 100644
--- a/output/output.txt
+++ b/output/output.txt
@@ -1 +1,2 @@
-Your output data will end up here
+Top Customers with the highest Simple Lifetime Value:
+Customer ID: customer1, Simple Lifetime Value: 5200.0
diff --git a/src/main.py b/src/main.py
new file mode 100644
index 0000000..100c162
--- /dev/null
+++ b/src/main.py
@@ -0,0 +1,39 @@
+from collections import defaultdict
+from datetime import datetime
+
+class CustomerData:
+    def __init__(self):
+        self.events = defaultdict(list)
+
+    #Ingests a customer event by storing  event type, customer ID, event time and additional keyword arguments#
+        
+    
+    def ingest_event(self, event_type, customer_id, event_time, **kwargs):
+        self.events[customer_id].append((event_time, event_type, kwargs.get('total_amount', 0)))
+
+    #calculate the LTV for customer ID by sum of the  the total expenditure from 'ORDER' events and dividing it by the visit frequency from 'SITE_VISIT' events#
+    def calculate_lifetime_value(self, customer_id):
+        events = self.events[customer_id]
+        total_expenditure = sum(amount for _, event_type, amount in events if event_type == 'ORDER')
+        visit_frequency = sum(1 for _, event_type, _ in events if event_type == 'SITE_VISIT')
+        return 52 * (total_expenditure / visit_frequency) if visit_frequency else 0
+#return top x customer with high LTV#
+    def top_x_simple_ltv_customers(self, x):
+        ltv_customers = [(self.calculate_lifetime_value(customer_id), customer_id) for customer_id in self.events]
+        return sorted(ltv_customers, reverse=True)[:x]
+
+if __name__ == "__main__":
+    events = [
+        ("CUSTOMER", "customer1", datetime(2021, 1, 1), {"last_name": "ch", "adr_city": "Dallas ", "adr_state": "TX"}),
+        ("SITE_VISIT", "customer1", datetime(2023, 1, 5), {"tags": ["tag1", "tag2"]}),
+        ("ORDER", "customer1", datetime(2024, 1, 10), {"total_amount": 100})
+    ]
+    
+    customer_data = CustomerData()
+    for event_type, customer_id, event_time, kwargs in events:
+        customer_data.ingest_event(event_type, customer_id, event_time, **kwargs)
+    
+    top_customers = customer_data.top_x_simple_ltv_customers(1)
+    print("Top Customers with the highest Simple Lifetime Value:")
+    for ltv, customer_id in top_customers:
+        print(f"Customer ID: {customer_id}, Simple Lifetime Value: {ltv}")