> ## Documentation Index > Fetch the complete documentation index at: https://developers.investorlift.com/llms.txt > Use this file to discover all available pages before exploring further. # Who should I call? > Rank the investors around a house you have under contract and read the reasons behind each score. You have 7522 E Cholla St, Scottsdale under contract at \$410,000 and it needs a major rehab. Ask for ranked buyers within two miles: ```bash curl theme={null} curl "https://api.investorlift.com/v1/buyers/match?lat=33.476917&lng=-111.920385&radius_miles=2&subject_asking_price=410000&subject_condition=MAJOR_REHAB&subject_segment=SFR" \ -H "Authorization: Bearer $GM_API_KEY" ``` ```javascript Node.js theme={null} const params = new URLSearchParams({ lat: "33.476917", lng: "-111.920385", radius_miles: "2", subject_asking_price: "410000", subject_condition: "MAJOR_REHAB", subject_segment: "SFR", }); const res = await fetch(`https://api.investorlift.com/v1/buyers/match?${params}`, { headers: { Authorization: `Bearer ${process.env.GM_API_KEY}` }, }); if (!res.ok) throw new Error(`${res.status} ${await res.text()}`); const body = await res.json(); ``` ```python Python theme={null} import os import requests r = requests.get( "https://api.investorlift.com/v1/buyers/match", params={ "lat": 33.476917, "lng": -111.920385, "radius_miles": 2, "subject_asking_price": 410000, "subject_condition": "MAJOR_REHAB", "subject_segment": "SFR", }, headers={"Authorization": f"Bearer {os.environ['GM_API_KEY']}"}, timeout=30, ) r.raise_for_status() body = r.json() ``` ## The score and the reasons The first thing to read on a row is why it scored what it did. Here is one, ranked 14th of the 5,813 investors scored in this radius: ```json theme={null} { "investor": { "id": "inv_0a20a550f33b", "name": "ZAK VENTURES LLC", "scale": "large", "n_deals": 775 }, "score": 0.8291, "gate": 1, "reasons": [ { "factor": "proximity", "weight": 0.3, "value": 0.8185, "detail": "12 purchases (12 parcels) within 2 mi, nearest 0.10 mi" }, { "factor": "recency", "weight": 0.25, "value": 0.9886, "detail": "last bought 7 days before the data's end date (2026-08-12); 81 purchase events in 24 months" }, { "factor": "price_fit", "weight": 0.2, "value": 0.4586, "detail": "$410k is above their 5-year band $210k-$289k (238 priced purchases)" }, { "factor": "strategy", "weight": 0.1, "value": 1, "detail": "FLIPPER (STRONG); subject is MAJOR_REHAB" }, { "factor": "segment", "weight": 0.05, "value": 0.894, "detail": "89% of their deals are SFR" }, { "factor": "wholesale_buyer", "weight": 0.1, "value": 1, "detail": "bought 36 wholesale contracts since 2021, last 2026-07" } ] } ``` 0 to 1, best first. `gate` times the weighted sum of the reason values, rounded to four decimals. Compare scores only within one response. The sentence to show a user. The API already writes it for a person: no ids, no internal names. This buyer is very close, very active, a flipper and a documented wholesale buyer. But \$410k is above what they usually pay, so `price_fit` is only 0.46. The [endpoint page](/api-reference/endpoints/buyers-match) has every factor, and says how the API rescales the weights when it cannot score one factor. ## The proof and the contact ```json theme={null} { "in_radius": { "n_events": 12, "n_parcels": 12, "n_flips": 3, "volume": 3119500, "nearest_distance_miles": 0.1 }, "sample_deals": [ { "id": "deal_4fd125ba9e27079bcdbe2d4968e313d8", "kind": "flip", "address_short": "7412 E Cambridge Ave", "bought_on": "2017-05-16", "bought_price": 242500, "sold_on": "2017-07-13", "sold_price": 282500, "gross_profit": 40000, "distance_miles": 0.1 } ], "contact": { "primary_address": { "street": "7522 E SAGUARO LN", "city": "SCOTTSDALE", "state": "AZ", "zip": "85257", "kind": "HOUSE", "is_generic": false }, "person_members": [{ "name": "RIVERA DANA", "name_order": "surname_first", "given": "DANA", "surname": "RIVERA" }], "skip_trace_targets": [{ "given": "DANA", "surname": "RIVERA", "address": { "street": "7522 E SAGUARO LN", "city": "SCOTTSDALE", "state": "AZ", "zip": "85257" }, "basis": "person_home" }] }, "contact_redacted": false } ``` What they did **inside your radius**, after your filters. The `investor` block beside it is their whole-market profile, so it is normal when the two numbers differ. Up to five of their nearest deals here. Proof to show the user. A person paired with an address, best first: "send these to a skip-trace vendor in this order". This host does not serve it: the whole block is null and `contact_redacted` is `true`. 5,813 here: the whole radius, not the page. ## Things you can change * **Leave out the subject facts** and the ranking is proximity, recency and documented wholesale buying only. * **Send `subject_arv=560000`** instead of the asking price, or with it. The API uses each flipper's own buy-to-resale ratio to convert an after-repair value into the price that flipper is likely to pay. * **Tune the weights per request** with `w_price_fit=0.4`. The effective weights come back in `meta.weights`. * **Narrow the field**: `active_within_months=12` drops anyone with no purchase in the last year. `buys_wholesale=true` keeps only investors with a documented purchase from a wholesaler. `investor_kind_exclude=WHOLESALER` removes the competition. ```bash curl theme={null} curl "https://api.investorlift.com/v1/buyers/match?lat=33.476917&lng=-111.920385&radius_miles=2&subject_arv=560000&subject_condition=MAJOR_REHAB&w_price_fit=0.4&active_within_months=12&buys_wholesale=true&investor_kind_exclude=WHOLESALER" \ -H "Authorization: Bearer $GM_API_KEY" ``` ```javascript Node.js theme={null} const params = new URLSearchParams({ lat: "33.476917", lng: "-111.920385", radius_miles: "2", subject_arv: "560000", subject_condition: "MAJOR_REHAB", w_price_fit: "0.4", active_within_months: "12", buys_wholesale: "true", investor_kind_exclude: "WHOLESALER", }); const res = await fetch(`https://api.investorlift.com/v1/buyers/match?${params}`, { headers: { Authorization: `Bearer ${process.env.GM_API_KEY}` }, }); if (!res.ok) throw new Error(`${res.status} ${await res.text()}`); const body = await res.json(); ``` ```python Python theme={null} import os import requests r = requests.get( "https://api.investorlift.com/v1/buyers/match", params={ "lat": 33.476917, "lng": -111.920385, "radius_miles": 2, "subject_arv": 560000, "subject_condition": "MAJOR_REHAB", "w_price_fit": 0.4, "active_within_months": 12, "buys_wholesale": "true", "investor_kind_exclude": "WHOLESALER", }, headers={"Authorization": f"Bearer {os.environ['GM_API_KEY']}"}, timeout=30, ) r.raise_for_status() body = r.json() ``` `w_activity=1` multiplies every score by the probability that the buyer buys again soon. It is off by default. See [Same buyer, cash right now](/guides/walkthroughs/same-buyer). ## Related topics - [Introduction](/index.md) - [Who is this lender?](/guides/walkthroughs/profile-a-lender.md) - [Top buyers in a place](/guides/walkthroughs/top-buyers.md) - [Errors](/guides/concepts/errors.md) - [Connecting a client](/mcp/connect.md)