Customer sentiment - and risk - are hidden in the emails in your CRM | MarTech

"Much of the genAI email discussion is centered on the use of GenAI to produce better targeted, personalized mass email campaigns, with the aim of improving the effectiveness of outbound campaigns. In this article, I'm going to dig into genAI use cases for inbound emails captured in the CRM. These messages include one-to-one messages and one-to-many reply-all emails. I am assuming here that the organization integrated its team's individual inboxes with the CRM, as is common among today's marketing, sales and customer teams."

"Every email that goes out or comes in is tracked and stored as part of the activity record. As a result, what were unstructured, scattered email conversations are now part of that business' central repository of data, and can be analyzed using a CRM's embedded AI and natural language processing (NLP). This allows us to move the discussion from tracking outbound engagement metrics, like opens and clicks, to instead analyzing the content and sentiment of the emails in the CRM,"

GenAI usage for email often centers on generating personalized outbound campaigns, but inbound CRM-captured emails offer rich insights. One-to-one and reply-all messages become activity records when teams integrate individual inboxes with the CRM. Those previously unstructured conversations become a centralized data repository available for CRM-embedded AI and NLP analysis. Analysis can include sentiment scoring, intent classification, and response-to-content assessment. The focus moves from traditional outbound metrics like opens and clicks to conversational insights revealing how customers feel and what they need. Leading CRMs increasingly offer these capabilities, reshaping martech and marketing operations.

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