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README.md

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+---
+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
+@inproceedings{sdrbench2026,
+  title={SDR-Bench: Sales Development Representative Benchmark},
+  booktitle={Proceedings of the 43rd International Conference on Machine Learning},
+  year={2026}
+}
+```