Online clothing store with Quarticon – before vs after

🔴 BEFORE using Quarticon

A typical store without AI:

• Everyone sees the same homepage
• Product recommendations are generic:
  • “Best sellers”
  • “New arrivals”
• Search is basic:
  • Typo = bad results
  • “red dress” shows anything with “red” OR “dress”
• Marketing emails are mass-sent:
  • Same newsletter to all users

👉 Result:

• Lower engagement
• Customers leave without buying
• Missed sales opportunities

🟢 AFTER using Quarticon

Now the store uses AI from Quarticon.

Step 1: Customer behavior tracking

Let’s say a user:

• browses sneakers
• clicks on black Nike shoes
• adds one pair to cart but doesn’t buy

Quarticon collects this data in real time.

Step 2: AI personalization kicks in

Homepage changes

Next time the user visits:

• sees sneakers first, not random products
• gets “Recommended for you” based on browsing

Product recommendations

Instead of generic suggestions:

• “You may also like” shows:
  • similar sneakers
  • same brand or style
• “Others also bought” shows:
  • socks, shoe care items

Smarter search

User types: “nik shoes blk”

Quarticon understands:

• “nik” → Nike
• “blk” → black

👉 Shows correct products instantly

Automated email follow-up

Since the user abandoned their cart:

They automatically receive:

• a reminder email
• possibly a discount
• exact product they viewed

Real-time targeting

If the user hesitates:

• system may show:
  • “Only 2 left in stock”
  • limited-time offer

Final result

Compared to before, the store gets:

• ✅ Higher conversion rates (more purchases)
• ✅ Bigger cart value (people buy more items)
• ✅ Better user experience
• ✅ Less manual work for marketers