Score Cold Leads via Web Research

Add the FutureSearch connector if you haven't already. Then upload investment_firms.csv and ask Claude:

Score each investment firm from 0-100 on their likelihood to purchase third-party research tools. High scores for fundamental/activist/short-sellers. Low scores for passive index funds and pure quant.

Results take about 2.5 minutes.

Go to futuresearch.ai/app, upload investment_firms.csv, and enter:

Score each investment firm from 0-100 on their likelihood to purchase third-party research tools. High scores for fundamental/activist/short-sellers. Low scores for passive index funds and pure quant.

The FutureSearch SDK's rank() performs web research on each row to score firms by a criterion that requires external knowledge.

pip install futuresearch
export FUTURESEARCH_API_KEY=your_key_here  # Get one at futuresearch.ai/app/api-key

import asyncio
import pandas as pd
from futuresearch import create_session
from futuresearch.ops import rank

firms_df = pd.read_csv("investment_firms.csv")

async def main():
    async with create_session(name="Research Tool Adoption Scoring") as session:
        result = await rank(
            session=session,
            task="""
                Score each investment firm from 0-100 on likelihood to purchase
                third-party research tools. High for fundamental/activist/short-sellers.
                Low for passive index funds and pure quant.
            """,
            input=firms_df,
            field_name="score",
        )
        return result.data

results = asyncio.run(main())