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People.ai
Overview
HQ Location
United States
Year Founded
2016
Company Type
Private
Revenue
$10-100m
Employees
201 - 1,000
Website
Twitter Handle
Company Description
People.ai is an AI and data platform transforming how go-to-market teams improve their sales productivity and win rates via the most comprehensive data foundation and Generative AI capabilities. With People.ai’s SalesAI platform, teams can unlock the value of their data to automate many strategic sales activities, including account planning, deal inspection, content generation, account enablement, and even forecasting. Companies such as Verizon, IBM Red Hat, Snowflake, Zoom, and Palo Alto Networks rely on People.ai’s enterprise-grade, patented AI technology.
IoT Snapshot
People.ai is a provider of Industrial IoT testing and certification, and training services, and also active in the cement, and oil and gas industries.
Use Cases
Functional Areas
Industries
Services
Technology Stack
People.ai’s Technology Stack maps People.ai’s participation in the IoT Technology stack.
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Devices Layer
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Edge Layer
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Cloud Layer
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Application Layer
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Supporting Technologies
Technological Capability:
None
Minor
Moderate
Strong
Case Studies.
Case Study
Boosting Sales Productivity through Data Automation: A Pluralsight Case Study
Pluralsight, a technology workforce development company, was grappling with lower growth than anticipated due to issues surrounding rep productivity. Despite having access to data on win rates and pipeline coverage, the company struggled to identify the behaviors that led to consistent, predictable revenue. Two key challenges stood in the way of Pluralsight’s growth targets: the quality of CRM data and inconsistent execution from their reps. The data in Salesforce, their 'single source of truth', was often biased or incorrect due to human error in data input. As the company rapidly expanded its sales force, rep productivity declined, leading to longer ramp times, lower pipeline generation, and lower billings and ARR growth than expected. The company had several hypotheses for these challenges but lacked concrete sales engagement data to validate them.
