Urban Links clears a hard stock frozen for a year in Bormes-les-Mimosas

In Bormes-les-Mimosas, Urban Links is developing a residence of 17 homes, with shops and services on the ground floor, right in the heart of the Le Pin district. Designed as an upmarket operation (architectural quality, refined materials, integration into the village fabric), the project deliberately kept price levels aligned with the local market rather than with the highest coastal standards.

After delivery, however, two homes remain unsold. The market has tightened: rising construction costs, higher interest rates, more selective buyers. Despite active sales support, the situation freezes.

For a city-building craftsman like Urban Links, used to precise operations in territories it knows well, this gap between the sales agents' discourse and the reality on the ground becomes a genuine risk-management concern.

In this context, Urban Links calls on Lycaon Data. The goal: not to produce yet another market study, but to obtain a scientific reading of actual demand and price sensitivity on this micro-segment.

Three questions guide the assignment:

• Are the listed prices consistent with the purchasing power of the buyers targeted in the Le Pin district?
• Do certain attributes of the remaining units (surface area, floor, orientation, outdoor spaces) penalize their liquidity compared with the rest of the development and with existing supply?
• At what price level does the probability of sale become maximal without needlessly eroding the margin?

Lycaon Data brings together several analytical building blocks on Bormes-les-Mimosas and the Le Pin district:

• Macro reading of the local market: median and high-end price levels, share of primary and secondary residences, liquidity by typology, apartment / house competition.
• Detailed analysis of the Town center / Le Pin sector: median prices around €5,900 to €6,000/m², supply structure, direct competition from houses in the €5,800 to €6,300/m² range.
• Econometric modeling of valuation criteria: impact of surface area, floor, outdoor spaces, brightness, parking, energy rating and view on the market price.
• Buyer price-acceptance probability curve:
  • fluid demand up to about €5,400/m²,
  • still liquid zone up to €5,800/m²,
  • beyond €6,000/m², demand thins out and marketing times lengthen,
  • from €6,800/m², very low acceptance probability and an ultra-selective market.

For the units concerned, the analysis shows that:

• some units are positioned at the upper limit, even above the price scope where demand is most active,
• competition is strong on premium units, notably from renovated older properties or houses offering larger surfaces for a comparable price level.

This finding runs counter to the initial intuition and to the sales feedback. But it rests on figures: probability of sale by price level, the link between price adjustment and depth of demand, exposure to competition on the units segment.

Once the diagnosis was made, Lycaon Data proposes an optimal pricing scenario for the last units, aligning each price with:

• its own characteristics (surface area, outdoor spaces, floor, view, brightness, parking),
• local purchasing power and the probability curve,
• the risk of tipping into a price zone where demand is too narrow and competition too strong.

The recommendations remain targeted: the point is not to slash prices, but to reposition the units in the price zone where one potential buyer in two is likely to step in, rather than staying in a zone where only one or two in ten can follow.

The decision means accepting a reasonable adjustment on the headline price to reduce a far more costly risk: several additional months of carrying costs, tied-up cash, and the damaged image of a stock that won't clear.

The effects of the decision are swift. In the days following the price update:

• a sale agreement is signed on one of the units,
• an option is placed on the second,
• the development emerges from more than a year of inertia, and the hard stock clears.

But the impact goes beyond the immediate operational level. The study becomes a structuring support to:

• arbitrate between the sometimes contradictory recommendations of sales agents,
• document the pricing strategy for partners,
• secure internal decisions in a turbulent market context.

For Urban Links, the value of this type of analysis extends well beyond the Bormes case. Emmanuel Pavy sees it as a global de-risking tool, useful at several levels:

• Banks: secure financing plans and credit committees by documenting the depth of demand, acceptable price levels and the likely pace of sales.
• Investors and asset managers: document cash-flow assumptions, adjust divestment strategies, choose between holding prices and accelerating asset rotation.
• Local authorities: show that the proposed product fits the reality of local demand, in terms of both price positioning and typologies, and that the development has every chance of finding buyers within reasonable timeframes.

In an environment where permits are becoming scarce, where regulatory and environmental constraints pile up and where business models are challenged, having a data-driven reading of demand and value becomes a strategic lever to:

• reduce risk on every operation,
• optimize the price / marketing-time trade-off,
• secure relationships with the financial and institutional ecosystem.

For Urban Links, this first collaboration paves the way for a more systematic use of data:

• Upstream, to size developments, adjust typologies and price levels right from the feasibility stage,
• During marketing, to adjust prices, reduce hard stock and secure pricing decisions,
• To support discussions with banks, investors and local authorities, to underpin the credibility of the choices.