---
license: mit
task_categories:
- text-retrieval
- text-generation
language:
- en
tags:
- benchmark
- personalization
- b2b-sales
- deep-research
- agent-evaluation
pretty_name: "SDR-Bench: A Benchmark for Sales Development Representative Agents"
size_categories:
- 1K<n<10K
---

# SDR-Bench: A Benchmark for Sales Development Representative Agents

This dataset contains **6,279** verified business success stories from various corporate domains.
It was curated for the SDR-Bench paper. 
This dataset serves as a benchmark for evaluating AI agents on their ability to conduct deep research and generate targeted sales pitch points. The data is derived from real-world Customer Success Stories, where the "Ground Truth" consists of the actual value propositions and pain points solved for a specific customer.

## Files
- `data.jsonl`: **(Recommended)** Flattened version compatible with the Hugging Face Viewer. Contains 1 story per line.
- `raw_data.json`: Original nested structure (grouped by Domain).

## Data Fields (JSONL)
- `domain`: The company domain (e.g., `rothesay.com`).
- `industry`: Industry category.
- `story_url`: Verification URL of the success story.
- `customer_company`: The entity that achieved success.
- `seller_company`: The entity providing the product/service.
- `products`: List of products involved.
- `published_date`: Date verification found on the page.

## Citation
```bibtex
@misc{sdrbench2026,
  author = {Srivastava, Ashutosh and Yedlapati, Siddharth and Aggarwal, Vinay and Dixit, Shashwat and Singla, Yaman Kumar},
  title = {SDR-Bench: Benchmarking the Personalization Capabilities of Large Language Models},
  year = {2026},
  publisher = {Behavior in the Wild},
  howpublished = {\url{https://behavior-in-the-wild.github.io/SDR-Bench.html}},
}
```