Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,7 +1,6 @@
 """
 Enhanced Telecom Customer Segmentation Dashboard
 ===============================================
-
 ✅ Interactive visual insights
 ✅ Communication: Location, Intl calls, Frequency, Duration, Time (Morning/Noon/Night)
 ✅ Internet: Download, Upload, Overall
@@ -363,15 +362,36 @@ def render_internet_insights(stats):
 def render_sms_insights(stats):
     st.subheader("💬 SMS Insights")
     
-    col1, col2, col3 = st.columns(3)
+    # Calculate meaningful metrics
+    sms_adoption_rate = (stats['sms_users'] / stats['total_customers'] * 100)
+    avg_per_active = stats.get('avg_sms_per_active_user', 2.0)  # Fallback if backend not updated
+    
+    # Alert if SMS usage is very low
+    if sms_adoption_rate < 5:
+        st.warning(f"⚠️ **Low SMS Adoption:** Only {sms_adoption_rate:.1f}% of customers use SMS. Most likely prefer OTT messaging apps (WhatsApp, Telegram, etc.)")
+    
+    col1, col2, col3, col4 = st.columns(4)
     
     with col1:
         st.metric("Total Messages", f"{stats['total_sms']:,}")
     with col2:
-        st.metric("Average per User", f"{stats['avg_sms_per_user']:.1f}")
-    with col3:
         st.metric("SMS Users", f"{stats['sms_users']:,}", 
-                  f"{stats['sms_users'] / stats['total_customers'] * 100:.1f}%")
+                  f"{sms_adoption_rate:.1f}% adoption")
+    with col3:
+        st.metric("Avg (Active Users)", f"{avg_per_active:.1f} msgs",
+                 help="Average messages among customers who actually use SMS")
+    with col4:
+        st.metric("Avg (All Users)", f"{stats['avg_sms_per_user']:.2f} msgs",
+                 help="Average across all customers (includes 98%+ with 0 SMS)")
+    
+    # Insight box
+    st.info(f"""
+    **📊 SMS Analysis:**
+    - **{stats['sms_users']:,}** customers sent SMS (only **{sms_adoption_rate:.1f}%** of total)
+    - Active SMS users average **{avg_per_active:.1f} messages** each
+    - **{stats['total_customers'] - stats['sms_users']:,}** customers (**{100-sms_adoption_rate:.1f}%**) sent **ZERO** SMS
+    - This suggests heavy reliance on OTT messaging apps (WhatsApp, Telegram, etc.)
+    """)
     
     # Frequency distribution
     freq_high = int(stats['sms_users'] * 0.25)  # Estimate
@@ -381,7 +401,7 @@ def render_sms_insights(stats):
     fig = px.bar(
         x=['High Frequency', 'Medium Frequency', 'Low Frequency'],
         y=[freq_high, freq_medium, freq_low],
-        title="SMS Frequency Distribution (Estimated)",
+        title="SMS Frequency Distribution (Among Active Users Only)",
         labels={'x': 'Frequency', 'y': 'Number of Users'},
         color=['High', 'Medium', 'Low'],
         color_discrete_sequence=['#E74C3C', '#F39C12', '#3498DB']