Outreach. has filed a patent for a workflow management system utilizing sentiment analysis to determine the effectiveness of Outreach strategies. The system uses a trained machine learning model to analyze electronic communication data and predict actions with positive reply rates. GlobalData’s report on Outreach gives a 360-degree view of the company including its patenting strategy. Buy the report here.
According to GlobalData’s company profile on Outreach, Location-based IM was a key innovation area identified from patents. Outreach's grant share as of January 2024 was 37%. Grant share is based on the ratio of number of grants to total number of patents.
Workflow management system using sentiment analysis for email communication
A recently filed patent (Publication Number: US20240020481A1) outlines a system and method for determining the intent of email communications between a user and a prospect. The patent describes a non-transitory computer-readable medium with stored instructions that, when executed by a processor, can detect electronic communications, determine sentiment categories using machine learning models trained on historical interaction data, and predict actions based on the sentiment category to elicit positive replies from prospects. The system also includes a second machine learning model trained on existing templates labeled with pre-determined sentiment categories to further refine action predictions based on reply rates associated with each category.
Furthermore, the patent details the generation of training data for each template, including determining language, selecting potential categories, and identifying primary sentiment categories. The sentiment categories encompass positive sentiments, objections, referrals, and other intents, with examples provided for each category. The system also utilizes metadata from email headers and recommendation models to suggest templates based on prior emails and customer responses. Overall, the patent aims to enhance email communication strategies by leveraging machine learning models to predict prospect responses and optimize user actions for positive outcomes.
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