# Salesforce Deal Intelligence

> Research your open deals with external data. Identify buying signals, surface risks, and update opportunities with actionable intelligence.

Source: https://cotera.co/solutions/sales/salesforce-deal-intelligence

---

- **Team:** Sales
- **Tools:** Salesforce, Apollo, LinkedIn
- **Difficulty:** advanced
- **Setup time:** 15 min
- **Time saved:** 3-4 hrs/week

## How it works
1. **External Research** — Pulls company data from Apollo and LinkedIn for each deal
2. **Signal Detection** — Identifies buying signals (hiring, funding) and risk signals (layoffs, leadership changes)
3. **Opportunity Updates** — Writes intelligence notes and next steps directly into Salesforce
4. **Priority Matrix** — Ranks deals by signal strength so you know where to focus

## Example requests
- Research my top 5 open deals and add intelligence notes to each opportunity
- Check if any of my Negotiation-stage accounts have had layoffs or leadership changes
- Pull buying signals for the Acme Corp deal — they just raised funding and I want to update the opportunity

## Prompt

```markdown
## Task

Enrich open Salesforce deals with external intelligence. For each opportunity, use @Salesforce/Find Account by Name to pull the account, research the company via @Apollo/Enrich Company and @LinkedIn/Get Company Insights, identify buying signals (hiring, funding, tech stack changes), and use @Salesforce/Update Objects to update the opportunity with research notes and recommended next steps.

**Example:** Research my top 5 open deals and add intelligence notes to each opportunity in Salesforce.

## Input

The user will provide either:
1. Specific deal or account names to research
2. A segment of deals (e.g., "all deals in Negotiation stage", "deals closing this quarter")
3. A contact email to look up the associated deals

**Example:** "Research the Acme Corp and Beta Inc deals — pull external data and update the opportunities with intelligence notes"

## Context

### Workflow

1. Use @Salesforce/Find Account by Name to pull the account and associated opportunities
2. Use @Salesforce/Find Contact by Email to identify key contacts on the deal (if provided)
3. Use @Apollo/Enrich Company to get company data: funding, headcount, tech stack, recent news
4. Use @LinkedIn/Get Company Insights to get headcount trends, hiring activity, and department growth
5. Analyze the enrichment data for buying signals relevant to the deal
6. Use @Salesforce/Update Objects to update the opportunity with:
   - Research notes / intelligence summary
   - Recommended next steps based on findings
   - Updated description or custom fields

### Buying Signals to Identify

**Strong Signals:**
- Recent funding round (new budget available)
- Hiring for roles related to your product
- Tech stack changes or new tool adoption
- Leadership changes (new CXO = new priorities)
- Headcount growth (scaling = more need)

**Risk Signals:**
- Layoffs or headcount decline
- Leadership departures
- Funding drought (no recent raise in 2+ years for startups)
- Competitor adoption signals

### What to Update on the Opportunity

- Description or custom "Intelligence Notes" field
- Next Steps with specific, actionable recommendations
- Stage adjustment if warranted (e.g., move to "At Risk" if layoffs detected)
- Close Date adjustment if timing signals suggest urgency or delay

## Output

**Deal Intelligence Report**

**Deals Researched:** [count]
**Buying Signals Found:** [count]
**Risk Signals Found:** [count]
**Opportunities Updated:** [count]

---

**Deal: [Account Name] — [Opportunity Name]**

**Company Overview:**
- Industry: [industry]
- Employees: [count] ([trend: growing/declining])
- Last Funding: [round] — [amount] ([date])
- Tech Stack: [relevant technologies]

**Buying Signals:**
- [Signal 1: e.g., "Hiring 3 data engineers — suggests investment in data infrastructure"]
- [Signal 2: e.g., "Series B closed 2 months ago — fresh budget available"]
- [Signal 3: e.g., "New VP Engineering hired — likely evaluating tools"]

**Risk Signals:**
- [Risk 1: e.g., "Headcount down 8% QoQ — possible budget tightening"]

**Recommended Next Steps:**
1. [Specific action: e.g., "Reference their new data engineering hires in follow-up — position around team scaling"]
2. [Specific action: e.g., "Ask about timeline given recent funding — budget likely allocated this quarter"]

**Salesforce Updates Made:**
- Description: Updated with intelligence summary
- Next Steps: Updated with recommendations
- [Other fields updated]

---

*Repeat for each deal researched*

---

**Priority Matrix:**

| Deal | Buying Signals | Risk Signals | Priority |
|------|---------------|-------------|----------|
| [Acme Corp] | 3 | 0 | High |
| [Beta Inc] | 1 | 2 | Medium |
| [Gamma LLC] | 0 | 1 | Low |
```

## Related reading
- [Salesforce AI in 2026: What Einstein Does, What It Doesn](https://cotera.co/articles/salesforce-ai-automation-guide.md)
- [Gong Alternative: What If Revenue Intelligence Didn](https://cotera.co/articles/gong-alternative-ai-revenue-intelligence.md)
- [Salesloft Competitor Guide: What Sales Teams Actually Need in 2026](https://cotera.co/articles/salesloft-competitor-comparison.md)