AI Relationship Research Use Cases

Sales: Preparing for a Discovery Call

Persona: Jordan, Account Executive, mid-market software company

Goal: Understand the relationship network at a new opportunity account before a discovery call

Jordan has a discovery call in 48 hours with three people she has never met at Horizon Construction Partners. Before AI Relationship Research, she would spend two to three hours piecing together context from Google, the news, her CRM, and Slack. She opens the Opportunity record and clicks Generate Insights. AI Relationship Research scans the web, her CRM records, and internal call transcripts in the background. Within minutes, the relationship graph surfaces eight prioritized connections. Two stand out: a former colleague of one of the call attendees currently works at Jordan's company, and there is a shared investor between Horizon and one of her existing customers.

Jordan clicks the shared investor node, reads the relationship summary and its source citations, and identifies a path to a warm introduction through her colleague. She creates a Contact record for a newly discovered executive directly from the graph. Jordan enters her discovery call with a clear picture of the relationship network, a warm introduction already in motion, and tailored talking points, all in under 10 minutes.

Financial Services: Relationship Manager Meeting Preparation

Persona: Sarah, Relationship Manager, Community Bank

Goal: Research a key commercial account before a client meeting

Sarah has a meeting scheduled with Innovate Robotics. She opens the Account record to trigger AI Relationship Research. AI Relationship Research scans CRM records, public web content, and Data 360 documents including call transcripts and email archives.

The relationship graph surfaces the most important connections to Innovate. Sarah clicks into nodes and edges to read relationship descriptions, strength analysis, and source citations. She discovers Venture Kinetics, identified in a press release as Innovate's new R&D partner. She creates a Lead record for Venture Kinetics directly from the graph and notes down a question about potential funding needs for the partnership..

AI Relationship Research has also flagged a hidden match: Alex Carlson Jr., identified in a recent news article as the COO of a customer of Innovate, is also a Contact record in the bank's CRM linked to an existing customer. Sarah confirms the match and sees that the bank and Innovate share a relationship with Alex's firm, an overlap that opens new cross-sell opportunities. She clicks Ask to pass the full relationship graph to Agentforce and asks what the two most actionable opportunities are ahead of the meeting. She enters the meeting with a focused two-point strategy, a new Lead record already in the CRM, and a confirmed cross-relationship, all surfaced in under 10 minutes.

Marketing: Researching a Buying Group for Account Nurturing

Persona: Marcus, Account-Based Marketer, B2B software company

Goal: Identify and personalize outreach to decision-makers at a target account

Marcus is building a nurture campaign for Crestfield Logistics, a high-priority target account. Before he can personalize outreach, he needs to understand who the real decision-makers are and what their backgrounds look like. He opens the Account record and triggers AI Relationship Research.

The relationship graph surfaces key stakeholders and their connections. Marcus discovers that the VP of Operations previously worked at a company that is already a customer of his organization, a connection not visible anywhere in the CRM. He also sees that the CFO recently joined the board of an industry association that his company sponsors.

Marcus uses these insights to segment the buying group and tailor campaign messaging to each stakeholder's background and priorities. Instead of a generic nurture sequence, he launches a campaign with outreach that speaks directly to each stakeholder's context and identifies the warmest entry point for initial contact.