A request for 1,000 square metres is a starting point. It does not explain how the space needs to work.

According to Joe Sokolic, founder and CEO of Sokolic Property Group, property matching becomes more valuable when the business captures the operational reasoning behind a brief.

“Floor area tells us how much space someone thinks they need. The conversation tells us what that space must enable,” he says.

A warehouse requirement might involve a particular stock flow, vehicle type or loading pattern. An office search could be shaped by recruitment, staff commuting or collaboration needs. Two businesses asking for the same size in the same area may need very different premises.

Sokolic proposes organising requirements into three groups: essential conditions, preferences and points requiring clarification.

That structure gives an AI-assisted matching process something meaningful to evaluate. It also makes the resulting shortlist easier for a broker to challenge.

A property might meet the location and size criteria but have unverified power capacity. The correct output is a possible match with an unresolved question. Missing information should never silently become a positive answer.

“I want a system to show me why it has recommended a property and where the evidence is incomplete,” says Sokolic.

Rejection reasons can improve future searches too, provided they are captured accurately and checked for continuing relevance. A budget objection made months ago may no longer apply.

The human conversation remains central because requirements develop as clients understand their options.

“A good shortlist should reflect the business behind the brief. That is the standard against which we should judge intelligent matching.”

Continue the conversation

Want to discuss your property requirements, explore the ideas in this article, or arrange a media interview with Joe Sokolic? Contact the Sokolic Property Group marketing team.

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