Spot2 – Schedule + Smart Projects

Scheduling a Visit with Smart Projects + Data Intelligence

In the traditional process of searching for commercial spaces, scheduling a visit was just the first step. However, for many companies—especially in sectors like industrial, logistics, and corporate—the decision-making process involves much more: comparative analysis, environmental studies, strategic expansion vision, and predictive data.

To support these types of decisions, I designed and built the “Projects + Intelligence” system within Spot2: a workflow that transforms each requirement or visit into an active project, with suggested spaces automatically and a contextual intelligence module based on the type of space.

Strategic Objective

Transform the scheduling of visits into the entry point for a consultative and data-driven process that not only makes it easier to find spaces but also closes more complex deals thanks to the power of automated personalization and precise contextual information.

This addresses two things simultaneously:

Enhances the commercial efficiency of Spot2 for large accounts.
Turns the platform into a source of comparable real estate insights that reinforce business decisions.

For the end customer:

Transform a simple visit into a guided and personalized process with intelligent data

Facilitate investment and expansion decisions backed by concrete environmental data

Allow for comparisons of alternatives using objective criteria (logistics, accessibility, surroundings)

For Spot2:

Increase the conversion rate from visits to closures

Strengthen relationships with large accounts (industrial/logistics/retail)

Standardize how complex requirements and prospects are processed

Success Metrics

North Star Metric

% of visits that generate an active project + use of the data intelligence module

(direct indicator of deep engagement)

Complementary KPIs:

Selection rate of suggested spaces vs. manual exploration (>60%)
Average evaluation time per project (>3 sessions)
% of agents who use insights in conversations with clients (>70%)
Closing rate of spaces managed from projects vs. traditional channels (+25%)

Research & Insights

Methodology applied by me

Shadowing and interviews with Spot2 agents and external brokers.
Mapping of current processes from scheduling to closing.
Exploration with real industrial companies about what data is critical to decide.
Benchmark with Real Estate Intelligence tools (CBRE MarketView, VTS, Procore).

Key findings

Companies with large investments do not make decisions without environmental data (logistics infrastructure, workforce, mobility).
Agents spent hours putting together ad hoc «market studies» without tools.
Each sector (industrial, offices, retail) has completely different evaluation criteria.
Most users do not want to fill out complex forms but respond well to intelligent and personalized suggestions.
Agents required a central tool to track progress, compare, and move prospects.

Product Design - UX / UI

Flow designed

User schedules a visit or leaves a requirement.
A project is automatically generated with their criteria (size, sector, area, budget…).
AI system recommends spaces that match (created in conjunction with the Data team).
User selects spaces they are interested in.
The Data Intelligence module is unlocked for each space:
- Shows personalized data by sector:
  - Industrial: proximity to ports, roads, workforce, logistics parks.
  - Offices: road access, transportation, amenities, population density.
  - Retail: pedestrian flow, competition, income per area, etc.
User can compare spaces in a map view + smart table.
Agent manages the project from an internal Kanban, advancing prospect phases.

Visual components

«Deck»-type selection module with cards.
Comparative view with map, filters, and responsive table.
Intuitive interface for brokers and companies with no learning curve.

Development

Stack

React + Next.js for project SPA.
Material UI for modular visual structure.
Leaflet.js map with custom layers per sector.
AI module with internal backend from the Data team.
State management with Context + Zustand.

Key developments made by me

Smart table with comparative features + visualization on the map.
Connection of the flow with the internal CRM system in Kanban (reusing SaaS base).
Conditional flags to show insights by sector.

Personal Role

I led the design of the complete flow, from UX to frontend.
I coordinated with Data Science to define matching criteria and insights by sector.
I built the key frontend components (comparator, deck, map, dynamic table).
I validated directly with end users (brokers, agents, and industrial clients).