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> For other versions, use one of these documentation indexes:
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> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://docs.workflows.com/llms.txt.
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# Close More Deals

![Mind Reasoner](/_fern-img/466e07efd0202b28f29ec8dda3be88918c85104c2652efceb8ff717127f861ca.webp)

> **The Paradigm Shift**
>
> **Stop guessing.** Create a customer mind from 1 conversation. Predict exactly how they'll think, feel, and respond—before your next meeting.
>
> **Result:** Win significantly more deals with accurate customer prediction.

---

## Why You Lose Deals

#### The Problem

**You walk into meetings blind:**

* Will they care about ROI or features?
* Which objections will they raise?
* Does your pitch resonate with them?
* What do they actually need to hear?

You're guessing. And losing deals because of it.

#### The Solution

**Walk in knowing:**

* Exactly what this customer cares about
* Which objections they'll raise
* How they'll respond to your pitch
* What will make them say yes

No more guessing. Just winning.

---

## How It Works

#### 1. Create Customer Mind

Upload 1 conversation transcript (call, meeting, email)

**Training:** 5-15 minutes

**Result:** Digital twin that thinks and responds like your customer

#### 2. Predict Their Response

Ask the customer mind any question:

* "What objections will you raise to \$200K pricing?"
* "Which pain points matter most to you?"
* "How will you respond if I position it this way?"

**Result:** Know exactly what they'll say before the meeting

#### 3. Close the Deal

Enter meetings fully prepared:

* Right messaging for THIS customer
* Responses to objections ready
* Proof points that resonate

**Result:** Win significantly more deals

---

## What You Can Predict

#### [Customer Objections](/workflow-sales-predict-responses)

Know which objections THIS customer will raise

**Predict:**

* Price concerns: real or negotiation tactic?
* Feature gaps: do they actually care?
* Risk concerns: what proof do they need?
* Timeline objections: real or brush-off?

**Outcome:** Dramatically higher win rate with objection prediction

#### [Pain Points](/workflow-sales-predict-responses)

Uncover hidden pain they won't volunteer

**Predict:**

* What they care about (not what they say)
* Which questions will unlock them
* Real priorities vs. stated priorities
* What will create urgency

**Outcome:** Close significantly more discovery calls than industry average

#### [Stakeholder Priorities](/workflow-sales-win-complex-deals)

Know what EACH decision-maker cares about

**Predict:**

* CFO: ROI timeline and risk concerns
* CTO: Integration and security worries
* VP Ops: Adoption and change management fears
* Who will champion vs. block

**Outcome:** Successfully navigate complex multi-stakeholder deals

#### [Competitive Positioning](/workflow-sales-win-complex-deals)

Know which messaging resonates with THIS buyer

**Predict:**

* Price vs. value: what matters more?
* Feature gaps: which ones matter to them?
* Risk vs. innovation: their buying style
* What proof points will convince them

**Outcome:** Win significantly more competitive deals

---

## Quick Start

#### 1. Get Access

Set up MCP Server (5 minutes, no coding):

[MCP Quick Start →](/mcp-quickstart)

#### 2. Create First Customer Mind

In Claude:

```bash
> "Create a mind for [Customer Name] at [Company]
using /path/to/transcript.vtt"
```

Wait 5-15 minutes for training

#### 3. Predict and Win

```bash
> "I'm presenting $200K pricing tomorrow.
What objections will you raise?"
```

Get predictions. Prepare responses. Close the deal.

---

## Implementation

#### MCP (No Code)

**Use Mind Reasoner through Claude Code**

No coding. Just natural conversation in Claude.

**You:**

```bash
> Create a customer mind for Sarah Chen, CFO at TechCorp,
using /Documents/calls/techcorp-cfo.vtt
```

**Mind Reasoner:**

```
✓ Created mind: "Sarah Chen - CFO TechCorp"
✓ Training... (~10 min)
```

**You:**

```bash
> I'm presenting tomorrow. What objections will Sarah raise
about our $400K pricing?
```

**Mind Reasoner:**

```
Based on Sarah's decision-making patterns:

She'll raise 3 objections:

1. ROI Timeline: "How fast will we see return?"
   Why: Conservative with large investments
   What she needs: 12-month payback with proof

2. Budget Authority: "This is 2x what we budgeted"
   Why: Needs CEO approval above $200K
   What she needs: Executive one-pager

3. Risk: "What if it doesn't work?"
   Why: Got burned by previous vendor
   What she needs: Customer references who switched
```

[See All MCP Tools →](/mcp-tools)

#### Direct API

**Build customer prediction into your workflow**

```javascript
const API_BASE = 'https://api.reasoner.com/api/mindsim';

// 1. Create and train customer mind
const { id: mindId } = await fetch(`${API_BASE}/minds`, {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${API_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    name: 'Sarah Chen - CFO TechCorp'
  })
}).then(r => r.json());

// Upload transcript and train (5-15 min)
// See API Quick Start for full workflow

// 2. Predict customer objections
const prediction = await fetch(`${API_BASE}/simulate`, {
  method: 'POST',
  headers: {
    'Authorization': `Bearer ${API_KEY}`,
    'Content-Type': 'application/json'
  },
  body: JSON.stringify({
    mindId,
    scenario: {
      message: "I'm presenting $400K pricing. What objections will you raise?"
    }
  })
}).then(r => r.json());

console.log('Predicted objections:', prediction.message);
```

[Full API Documentation →](/api-quick-start)

---

## Next Steps

#### [Predict Customer Responses](/workflow-sales-predict-responses)

Learn how to predict objections and pain points before every meeting

#### [Win Complex Deals](/workflow-sales-win-complex-deals)

Navigate enterprise deals and competitive situations with customer prediction

#### [MCP Quick Start](/mcp-quickstart)

Set up in 5 minutes. No coding required.

#### [API Quick Start](/api-quick-start)

Build customer prediction into your CRM

> **Info**
>
> Questions? Email [support@reasoner.com](mailto:support@reasoner.com)