scholarly360/salestech_sales_qualification_framework_bant

---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 7416
num_examples: 100
- name: test
num_bytes: 1884
num_examples: 26
download_size: 6977
dataset_size: 9300
tags:
- salestech
- sales
---
# Dataset Card for "salestech_sales_qualification_framework_bant"

---
license: apache-2.0
---

# Dataset Card for Dataset Name

## Dataset Description

- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**

### Dataset Summary

The BANT technique is a sales qualifying framework that considers a prospect's budget, internal influence/ability to buy, need for the product, and timeframe for making a purchase when determining whether to pursue a sale.

Because it aids in lead qualification during the discovery call, BANT plays a vital role in the sales process. The sales team may acquire precise information from the prospect about their budget, stakeholders, need, and timescale immediately, rather than waiting days or weeks for leads to be qualified using a score determined from the prospect's behaviour and engagement with marketing and sales materials.

Budget - The prospect's financial capacity to invest in your solution.

Authority - Who has the final say in this transaction? Who gets to make the final call?

Need – Does the potential customer really need my product? Do all members of the team require this?

Timeline -How long will it be before the potential customer makes a decision?

### Supported Tasks and Leaderboards

N.A.

### Languages

ENGLISH

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

There are 2 columns:
text: text
label : label (one of four from BANT)

### Data Splits

N.A.

## Dataset Creation

### Curation Rationale

Prospectus text mining

### Source Data

#### Initial Data Collection and Normalization

[More Information Needed]

#### Who are the source language producers?

[More Information Needed]

### Annotations

#### Annotation process

[More Information Needed]

#### Who are the annotators?

[More Information Needed]

### Personal and Sensitive Information

[More Information Needed]

## Considerations for Using the Data

### Social Impact of Dataset

This will help SaleTech to better qualify leads.

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

[More Information Needed]

## Additional Information

### Dataset Curators

[More Information Needed]

### Licensing Information

[More Information Needed]

### Citation Information

### Contributions

Made by Author [Scholarly360](https://github.com/Scholarly360) .

原始信息汇总

数据集概述

数据集名称

"salestech_sales_qualification_framework_bant"

数据集描述

该数据集基于BANT销售资格框架，用于评估潜在客户的预算、内部影响力/购买能力、产品需求和购买时间框架，以决定是否进行销售跟进。

数据集结构

• 数据字段:
  • text: 文本信息
  • label: 标签（BANT框架中的四个类别之一）

数据分割

• 训练集:
  • 示例数量: 100
  • 字节数: 7416
• 测试集:
  • 示例数量: 26
  • 字节数: 1884

数据集大小

• 下载大小: 6977字节
• 数据集大小: 9300字节

语言

英语

数据集用途

帮助SaleTech更有效地资格化潜在客户。