Premium real estate: lead qualification

A premium real estate agency with a stream of requests from paid ads and social media. The properties are expensive, the deal cycle is long, and the ad traffic came in mixed: alongside real buyers wrote the curious, renters and people for whom the property was out of budget. Several agents sorted every request by hand in chat. As a result, the most expensive time of the specialists went to conversations that almost never ended in a viewing.

We broke down the funnel from request to viewing and saw the bottleneck right at the start. Only a small share of requests reached a viewing, and the first reply sometimes took a client several hours, because the agent was busy at a meeting or with another client. During that time interest cooled and the person went to whoever answered faster. Meanwhile, agents could not tell a hot lead from a random one until they had already spent time on it.

We needed not just an autoresponder but fast qualification at the entry. The assistant should itself, and in a living tone, clarify budget, the district of interest, property type and purchase timeline, and then understand whether the request is on target. Hot requests must go to the agent at once and flagged as priority, while off-target ones are closed gently, without burning the specialists time and without scaring the person off with a dry form.

We built an assistant on WhatsApp that meets every ad lead within seconds. It asks a short, polite chain of questions, recognizes the client free-form wording and, based on the answers, matches the request against the property base. If the parameters fit and the person is ready to deal within a foreseeable term, the request is flagged as hot and goes to the agent along with a card: budget, district, matching options and the whole dialog history. Off-target requests are closed gently, and the contact is kept in the base for the future so the agent does not return to them.

The launch took about four weeks. First, together with the head of sales, we described the criteria of a target request: budget thresholds, priority districts, property types and signs of readiness to deal. Then we linked the assistant to the property base and the CRM so the card would reach the right agent immediately. Separately, we tuned the tone of the questions so they sounded like a talk with a consultant, not an interrogation. After a trial on part of the ad traffic, we rolled the assistant out to the whole request flow.

After launch, the share of viewings that really lead to a deal grew noticeably, because mostly prepared clients now reach the agent. Time to first contact dropped from several hours to a couple of minutes, and requests stopped cooling in the queue. Agents were relieved of sorting random requests and focused on what brings commission: viewings, negotiations and deal support. The ad budget started working more efficiently, since not a single paid lead is left without a fast reply.