# MARASA

> MARASA builds Consumer Intelligence, on-demand consumer spending insights built on Canadian credit card transaction data. Retailers, marketers, product teams, e-commerce operators, and site selectors load a credit budget, ask a question in plain language about local spend, growth, or trade areas, and get the insight with the underlying data that backs it up. Pay per query instead of a six-figure annual data license. MARASA also builds Cap Books, the data infrastructure for commercial real estate asset managers.

## Primary product: Consumer Intelligence

- [MARASA Consumer Intelligence](https://marasa.ai/): On-demand Canadian consumer spending insight, priced per query with no annual data license. Built for retailers, marketers, product and growth teams, e-commerce operators, and retail site selectors who need real consumer spending intelligence without a long-term data contract.

### What the data covers

- Canadian credit card transaction data with continuous coverage from 2019 to 2026
- Every FSA (forward sortation area) and neighbourhood across Canada
- 350,000 merchant locations
- Roughly 3.5 billion transactions per year across 455 categories
- Major markets including Toronto, Montreal, Vancouver, Calgary, Edmonton, Ottawa, and Winnipeg, down to a specific corridor or intersection

### How pricing works

- Pay per query, no annual license. You load a credit budget, ask what you want, get the insight, and pay only for that query.
- Example queries range from about $5 for a local spend-and-growth question to roughly $50 for ranking the most underserved markets in Canada for a category.

### Questions Consumer Intelligence answers

- What do people within a short walk of a given intersection actually spend money on, and is it growing?
- Where do a location's customers come from, and how far do they travel to spend?
- Did a real-world event actually change spending in an area, and did the change stick?
- Is a category shifting online or in-store in a specific market?
- Which candidate locations should we rank highest for a new concept before signing a lease?
- Which markets in Canada are most underserved for a given retail category?

### How to query

- AI Assistants: Claude and any MCP-compatible client
- Productivity: Microsoft Excel
- Direct access: MARASA exposes an MCP server for Consumer Intelligence

## Second product: Cap Books

- [MARASA Cap Books](https://marasa.ai/cap-books): CRE data infrastructure for institutional and boutique asset managers managing office, retail, industrial, and multifamily portfolios in Canada and the US. Structures rent rolls, leases, proformas, budgets, Yardi exports, MRI reports, Hopem data, and Building Stack records into a single queryable database. Query NOI variance, lease expiry, vacancy, WALT, debt schedules, and CAPEX in plain language from Claude, Excel, or Power BI.

## Who MARASA is for

- Consumer Intelligence: retailers, restaurant and franchise operators, marketers, product and growth teams, e-commerce operators, real estate and retail site selectors, and investors who need Canadian consumer spending data on demand.
- Cap Books: institutional and boutique CRE asset managers, portfolio managers, and investment analysts running Yardi, MRI, Hopem, or Building Stack.

## Contact

- Request a demo: https://calendly.com/david-latortue-marasa/30min
- Email: hello@marasa.ai
- LinkedIn: https://www.linkedin.com/company/marasaintellections