This thesis investigates how structured data-sharing can enhance dealmaking between developers and institutional investors in Dutch forward-purchase and turnkey residential transactions, with a specific focus on the negotiation corridor between a non-binding offer/letter of intent and the sale and purchase agreement. The research identifies that many inefficiencies arise not from limited transparency alone, but from fragmented information flows, incompatible data formats, conflated data streams, and the implicit accumulation of residual uncertainty, some of which persist even after due diligence and closing. Through a pragmatist approach—combining literature, semi-structured interviews, and internship observations—the study maps how data, uncertainty, and negotiation behaviour interact across triangulated developer–investor–operator relations. The resulting framework introduces phased and standardized data-exchange, segmentation of asset and mandate criteria, and residual uncertainty scoring that makes implicit assumptions explicit, negotiable, and defensible in pricing and contractual terms. The findings portray that disciplined sequencing of information, data segmentation, and clearer vocabulary, reduce valuation drift, limit re-trades, and improve negotiation efficiency, while preserving the strategic dynamics inherent to real estate negotiations. Ultimately, the study provides a realistic and scalable mechanism for aligning divergent approaches to risk, strengthening decision-making, and enhancing predictability in residential investment negotiations.