Users
Store ownership and account-level context.
A focused SaaS for local business intelligence
Mapspector is being built as a lightweight prospecting platform that helps users discover local businesses with visible digital growth opportunities.
What the product does
Mapspector starts with a simple idea: search a market by keyword and location, gather local business results, and highlight which businesses are the best outreach targets. Instead of dumping unstructured data into a spreadsheet, the platform is designed to turn those results into usable leads with scoring and reasoning.
The MVP currently demonstrates the core product structure, search workflow, and a sample lead output. This is the right stage to harden the data model and page flow before expanding into enrichment, job queues, exports, and provider switching.
Who it helps
- SEO and website agencies prospecting local businesses
- Outbound teams looking for warm-ish signals from public presence
- Operators building niche lead databases by city and category
- Anyone who wants repeatable, organized market searches instead of one-off scraping
Why the current architecture matters
The important MVP decision is separating the search request from the search execution. A search is the user’s saved intent. A search job is the actual run against a provider. This makes room for retries, multiple provider runs, historical comparisons, and future background workers.
Searches
Store the reusable query itself: what to search and where.
Search jobs
Store each run, its status, provider, and execution details.
Businesses
Store normalized business records that can be reused across searches.
Leads
Store search-specific opportunity outcomes and scores.
Exports later
Once this base is stable, exporting and scheduling become easier additions.