Data integration · Internal tools
Lead organization & prioritization
Deal Hunter
Combined source lists, removed duplicates and ranked opportunities against the client’s criteria.
Archived project- 01Source lists
- 02Normalize + match
- 03Apply client criteria
- 04Prioritized workspace
The problem
Lead data was scattered across lists. The client needed consistent records and a clear way to decide what to review first.
What I built
I built Deal Hunter to combine and match records, apply buying criteria and present prioritized leads in Google Sheets.
The result
Organized 2,934 property leads, with 6,092 closed-sale records supporting nearby-property valuation.
How it fit together
Source lists were normalized into one record shape, deduplicated and matched across sources. Deterministic buy-box rules ranked the results; closed-sale records supported nearby-property valuation as a separate step. Everything surfaced in Google Sheets, where the client already worked.
Normalization made source data comparable. Deduplication and cross-source matching linked records; deterministic rules drove ranking. Closed-sale comparisons supported valuation separately.
Decisions and tradeoffs
- Deterministic rules over a learned score.
- The ranking needs tuning by hand, but the client could read why a lead ranked where it did.
- Matching and ranking as separate steps.
- Slightly more code; either step could be checked on its own when a result looked wrong.
Explicit business rules made rankings explainable. Record matching and prioritization were separate steps.