Capturing the requirement as structured data — not a note — is what makes matching and follow-ups work.
Example
A captured requirement
After a ten-minute call, a telecaller records: buy, 3 BHK, budget ₹1.4–1.6 crore, carpet area at least 1,200 sq ft, Baner or Balewadi in Pune, ready to move or possession within 12 months, loan pre-approved, decision with spouse. Each field is structured, so the system can match it against listings and units instead of someone rereading call notes.
Figures are illustrative, not market rates.
Questions about Requirement
What fields make a good requirement?
Transaction type, budget range, BHK, minimum carpet area, preferred localities, possession or move-in date, property type, and constraints such as floor, facing, parking or pet-friendliness. Financing status and who decides are also worth capturing early.
How does a requirement help matching?
When the requirement is stored as structured fields rather than free text, new listings and units can be compared with it automatically. A buyer looking for a 3 BHK under ₹1.6 crore in Baner can be alerted the moment a match is listed.
How often should a requirement be updated?
Whenever the buyer’s answers change — after visits, a budget change or a new preferred area. Requirements drift as buyers see the market, and an outdated requirement sends the wrong properties and wastes visits.
Reviewed