How Shopertyy Turned Dormant Real Estate Leads Into Revenue with CallKaro AI

Situation

Shopertyy runs a real estate brokerage business powered by a team of calling agents dialling out roughly 55,000 minutes every month to connect with property leads. Like most high-volume outbound operations, Shopertyy faced a familiar bottleneck: when a lead's first call didn't connect, the lead quietly slipped into a dormant pile. With agents focused on fresh, incoming leads, nobody had the bandwidth to keep circling back to uncontacted or unresponsive numbers. Over time, this created a growing backlog of dormant leads real buyers and sellers who were never given a second chance to connect while the brokerage kept spending on human calling capacity at ₹20+ per minute. The core problem wasn't lead quality. It was capacity: limited number of agents simply couldn't re-dial an ever-expanding backlog without pulling focus away from active, working leads.

Task

Shopertyy needed a way to:

1. Reconnect with dormant leads at scale, without adding headcount or diverting agents from active pipelines.
2. Qualify each reconnected lead separating genuine interest (hot/warm) from dead ends (cold) so human agents only spent time where it counted.
3. Do this at a cost structure that made sense for leads that had already shown low initial engagement. The ask, in short: build a supporting layer that revives the backlog and hands agents only the leads worth their time.

Action

CallKaro AI deployed a voice AI calling agent purpose-built to sit alongside Shopertyy's human team as a dormant-lead reactivation layer: a. Systematic re-engagement: The AI agent worked through the backlog of dormant leads leads whose first call never connected dialling them back automatically and consistently, something the human team had no bandwidth to do. b. Natural, conversational qualification: On connect, the AI agent ran a structured qualification conversation, gauging property interest, budget signals, and intent. c. Hot / Warm / Cold segmentation: Every reconnected lead was tagged based on conversation outcome Hot (ready to engage), Warm (interested, needs nurturing), or Cold (not viable) and routed accordingly. d. Seamless handoff to human agents: Only Hot and Warm leads were passed to Shopertyy's calling agents for follow-up, so human effort was concentrated entirely on leads with demonstrated intent. e. Cost-efficient scale: The AI layer operated at roughly 75% cheaper than the cost of human calling making it economically viable to attempt every dormant lead, not just a hand-picked few.

Result

By introducing an AI-first reconnection layer ahead of the human team, Shopertyy was able to:

• Revive a previously abandoned lead pool dormant leads that would otherwise have gone permanently uncontacted were systematically reconnected.
• Cut the cost of lead reactivation from ₹20+/min to ₹5/min, freeing up budget to attempt the entire dormant backlog instead of a fraction of it.
• Sharpen agent focus by pre-qualifying leads into Hot/Warm/Cold, Shopertyy's agents spent their calling time only on leads with real buying or selling intent, rather than re-dialling cold or unresponsive numbers blind.
• Build a repeatable reactivation engine dormant leads are no longer a dead end; they now flow through a standing AI qualification layer before ever being written off.