Enterprise sales reps often struggle with the time-consuming task of researching prospects—manually combing through annual reports, news articles, and other sources to personalize outreach. This inefficiency leads to lower response rates and missed opportunities. An AI-powered research assistant could streamline this process by automating prospecting, summarizing key insights, and crafting tailored outreach, freeing reps to focus on closing deals.

How It Works

The tool would handle three core tasks:

• Prospecting: Analyzing a company's data to identify high-potential leads.
• Research: Scraping public sources (SEC filings, LinkedIn, news) to generate concise summaries of a prospect's business and pain points.
• Outreach: Drafting personalized emails or call scripts based on the prospect's context, such as recent earnings calls or industry trends.

It could integrate with existing CRMs like Salesforce and communication tools like Outlook, delivering insights via a dashboard or browser extension.

Why It Matters

Sales reps save hours per prospect while increasing close rates. Small teams without dedicated research staff benefit from AI scaling their efforts. Sales managers gain visibility into pipeline quality through AI-generated analytics. Prospects receive more relevant outreach, improving engagement.

Getting Started

One way to begin would be with a simple MVP—a web tool that generates a one-page summary of a prospect from their LinkedIn or company website. Early versions could rely on manual research (human-assisted) before transitioning to full automation. Later iterations could add CRM integration, automated lead suggestions, and call preparation prompts.

Key challenges include ensuring data accuracy (starting with structured sources like SEC filings) and building trust with sales teams (positioning the tool as an assistant, not a replacement). Over time, the AI could learn which research and outreach strategies work best, creating a competitive edge.