How Mazikien, a High-AOV Fashion Brand, Recovered ₹2.3L in Revenue in 1 Month Using Shop Pass and LimeChat

Mazikien is where Milan’s street-style design meets the soul of Bombay, crafted for women who dress with purpose. It is a non-seasonal, high-AOV women’s western wear label that attracts fashion-forward shoppers across age groups.

The Challenge

Despite strong traffic from paid campaigns, Mazikien noticed a gap in converting high-intent anonymous users, especially those dropping off from product, cart, or checkout pages. Their existing setup wasn’t capturing enough of this opportunity, leaving ROI on the table.

Their core challenges were:

• Mazikien’s website attracted substantial daily traffic—averaging around 3,000 unique visitors per day. However, a significant portion of these visitors dropped off before completing a purchase, resulting in a low final conversion rate.
• Additionally, like many brands in the industry, Mazikien faced limitations in retargeting potential customers. The standard benchmark allowed only about < 3% of total traffic to be identified and retargeted at the point of checkout. Given the volume of visitors, Mazikien recognized a major opportunity: they believed they could exceed industry norms and recapture far more of their lost audience.

The Solution: 

Shopflo introduced Shop Pass, enabling seamless logins that convert unknown visitors into known users, unlocking deeply personalized retargeting.

• Shop Pass uses behavioral signals to identify and understand users’ journeys who would have otherwise remained unknown.
  
• LimeChat then triggers smart conversations based on where the user has dropped off, showing them exclusive personalised offers.

This combination allowed Mazikien to deliver timely, targeted nudges that feel personal and relevant, driving users back to complete their purchases.

The Results

Within a month of the Shop Pass x LimeChat flows being live, 

• Mazikien achieved a significantly improved conversion rate on retargeted communications and recovered ₹2.3L in revenue in a month’s time. 
• The identified users also jumped to over 70k unique customers in the same span of time.