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Determining the quality of B2C sales leads from online chats

Author

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  • Good, Valerie
  • Bhattacharya, Abhi
  • Hochstein, Bryan W.
  • Voorhees, Clay M.

Abstract

Firms increasingly rely on online chat interfaces to generate sales leads. Yet, little is known about which leads are worth pursuing. We address this gap through a qualitative survey of sales managers and a predictive text analysis of online chats in the auto industry. We then replicate these findings in another high-involvement B2C purchase context (furniture). Based on signaling theory, we demonstrate how textual cues from online conversations can help B2C salespeople as they aim to qualify leads. Specifically, we identify conversational patterns, phrases, and words that predict downstream purchase and profit outcomes. Our findings highlight a new lead qualification framework summarized by the acronym MINITS—Mode of contact, Immediacy, Need, Interest, Time spent chatting, and Specificity—which together explain meaningful variance in sales outcomes. This research contributes to scholarship and practice by first demonstrating that language in online chats signals buyer intent and second by equipping managers with a scalable, data-driven method to prioritize high-quality leads.

Suggested Citation

  • Good, Valerie & Bhattacharya, Abhi & Hochstein, Bryan W. & Voorhees, Clay M., 2026. "Determining the quality of B2C sales leads from online chats," International Journal of Research in Marketing, Elsevier, vol. 43(2), pages 383-403.
    • Handle: RePEc:eee:ijrema:v:43:y:2026:i:2:p:383-403
    DOI: 10.1016/j.ijresmar.2025.07.001
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