{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-11481685","patent":{"patent_number":"US-11481685","title":"Machine-learning model for determining post-visit phone call propensity","assignee":null,"inventors":[],"filing_date":"2020-11-11T00:00:00.000Z","publication_date":"2022-10-25T00:00:00.000Z","cpc_codes":["G06N","G06N","G06N","G06N","G06Q","G06Q","G06Q","H04L","H04L","H04L","H04M","H04M","H04M","H04M","H04M","H04M"],"num_claims":20,"abstract":"Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity after some customer visits to a web site of an entity and a second percentage of call propensity source data that correspond to absence of post-visit phone calls to the customer service after other customer visits to the website. A machine-learning model is trained based on a plurality of features in at least a portion of the call propensity source data to generate a trained machine-learning model. The trained machine-learning model is applied to multiple features included in at least one of corresponding website activity data and corresponding activity error data of a customer to generate a probability score that measures a likelihood of the customer calling the customer service regarding an issue that is unresolved via the website."},"analysis":{"summary":null,"layman_explanation":null,"technical_analysis":null,"business_analysis":null,"faqs":null,"topics":[],"tech_cluster":null},"seo":{"title":"Machine-learning model for determining post-visit phone call propensity","description":"Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity afte","keywords":[]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-11481685","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-11481685","citation_suggestion":"Patentable. \"Machine-learning model for determining post-visit phone call propensity\" (US-11481685). https://patentable.app/patents/US-11481685","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-11481685","json":"https://patentable.app/api/llm-context/US-11481685","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-31T01:34:26.528Z"}