How Mulmul turned high-intent traffic into revenue with AI-led lifecycle automation and live sales conversations

Mulmul’s digital presence was already strong — but its engagement model hadn’t kept pace with the sophistication of its customer base. Email, WhatsApp, and SMS were each run through separate tools, with no shared logic connecting them. The result was a brand experience that felt disjointed at exactly the moments it needed to feel most considered: when a luxury shopper was actively deciding whether to buy.

Underneath that fragmentation sat three compounding problems:

• High-intent traffic was going cold. Customers were signalling real purchase intent – browsing collections, viewing specific products like Kurta Sets, adding items to cart , but without always-on, behaviour-triggered engagement, that intent had no system to catch it before it decayed.
• A loyal base was underleveraged. Mulmul already had a 24% repeat-purchase rate, a strong signal of brand affinity but with no lifecycle-driven engine connecting past behaviour to future outreach, that loyalty wasn’t compounding into a predictable, repeatable revenue stream.
• Campaigns weren’t converting into conversations. Every campaign-led send was a one-way broadcast. There was no reliable path from “customer clicked a message” to “customer is now talking to a sales representative” , so interest generated by marketing routinely died before it reached a human who could close it.

Left unresolved, this meant Mulmul was leaving revenue on the table at every stage of the funnel , while also risking the one thing a luxury brand can least afford to compromise on: a consistent, considered customer experience across channels.

Mulmul’s fix wasn’t a single tool, it was connecting two purpose-built systems into one workflow: Netcore.ai to sense intent and orchestrate the right message at the right moment, and LimeChat as the conversational layer that turned that engineered intent into an actual, SLA-tracked sales conversation. Neither piece alone would have closed the loop, Netcore identified and triggered the moment; LimeChat made sure a real person picked it up.

Intent detection & journey orchestration – Netcore.ai

• Intent & affinity profiling: Netcore’s Agent moved Mulmul past basic demographic filters, segmenting shoppers by real-time browsing behaviour, product affinity, and order history.
• Funnel-triggered journeys: Browse → Item View → Cart Addition → Checkout paths triggered context-aware nudges at the exact moment buyers were most likely to convert.
• Location-based & exclusive drops: Geo-targeted pushes drove footfall to new retail locations (Khan Market, Chandigarh), while curated drops directed high-value cohorts to the VIP previews.
• Dynamic inbox experiences: AMP-powered interactive emails (in-box carousels, rich media) paired with Send Time Optimisation reached customers at their individual peak activity hours.
• WhatsApp campaigns that convert into conversations: Geo-targeted retail launches, festive previews, and app-exclusive drops sustained 85%+ delivery, routing interested customers straight into a live sales conversation.

Turning that intent into a sale – LimeChat

• Direct route from campaign to sales rep: Every campaign carried rich visuals and a dedicated response button. A single tap routed the customer straight into Mulmul’s sales team via LimeChat Helpdesk – the piece that converted expressed interest into a live, human sales conversation.
• One desk for campaigns and support: Campaign responses and everyday queries – sizing, stock, store timings, delivery, directions – landed in the same LimeChat Helpdesk queue, giving agents a single, unified view of the customer.
• SLA monitoring & prioritisation: Mulmul set first-response and resolution SLAs and tracked breaches, letting supervisors surface ageing conversations before they became lost sales.
• Higher volume, same headcount: WhatsApp support volume grew 12% quarter-on-quarter with no increase in agent headcount – LimeChat’s queue and SLA structure absorbed the growth.

Together, the two systems closed the loop end-to-end: Netcore decided who to reach and when; LimeChat made sure that moment turned into a conversation with a real person, tracked against a service standard, in the same queue as everyday support.

Synchronising automated outbound journeys with live conversational support moved the needle on both commercial and operational KPIs — outside of major sales events, on baseline performance alone.

The pattern across every metric is the same: intent that used to go cold now gets caught, routed, and closed — by an AI-orchestrated trigger on one side, and a real sales conversation with a tracked SLA on the other. That combination is what let Mulmul scale multi-channel revenue without scaling headcount, and turn one-time luxury shoppers into a genuinely repeatable customer base.