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[2602.17017] Sales Research Agent and Sales Research Bench
Summary
The paper presents the Sales Research Agent, an AI tool in Microsoft Dynamics 365 Sales, designed to provide insights from live CRM data. It introduces the Sales Research Bench, a benchmark for evaluating AI systems based on quality metrics.
Why It Matters
As enterprises increasingly rely on AI for sales insights, the need for transparent and repeatable quality assessments becomes critical. This research addresses that gap by offering a benchmark that allows organizations to evaluate AI solutions effectively, ensuring better decision-making in sales strategies.
Key Takeaways
- The Sales Research Agent connects to live CRM data to provide actionable insights.
- The Sales Research Bench evaluates AI systems on eight critical quality dimensions.
- In tests, the Sales Research Agent outperformed notable AI models, indicating its effectiveness.
- The benchmark provides a repeatable method for enterprises to compare AI solutions.
- This research highlights the importance of transparency and explainability in AI applications.
Computer Science > Artificial Intelligence arXiv:2602.17017 (cs) [Submitted on 1 Dec 2025] Title:Sales Research Agent and Sales Research Bench Authors:Deepanjan Bhol View a PDF of the paper titled Sales Research Agent and Sales Research Bench, by Deepanjan Bhol View PDF HTML (experimental) Abstract:Enterprises increasingly need AI systems that can answer sales-leader questions over live, customized CRM data, but most available models do not expose transparent, repeatable evidence of quality. This paper describes the Sales Research Agent in Microsoft Dynamics 365 Sales, an AI-first application that connects to live CRM and related data, reasons over complex schemas, and produces decision-ready insights through text and chart outputs. To make quality observable, we introduce the Sales Research Bench, a purpose-built benchmark that scores systems on eight customer-weighted dimensions, including text and chart groundedness, relevance, explainability, schema accuracy, and chart quality. In a 200-question run on a customized enterprise schema on October 19, 2025, the Sales Research Agent outperformed Claude Sonnet 4.5 by 13 points and ChatGPT-5 by 24.1 points on the 100-point composite score, giving customers a repeatable way to compare AI solutions. Comments: Subjects: Artificial Intelligence (cs.AI) Cite as: arXiv:2602.17017 [cs.AI] (or arXiv:2602.17017v1 [cs.AI] for this version) https://doi.org/10.48550/arXiv.2602.17017 Focus to learn more arXiv-issued DOI via DataCite (...
