Enterprise Account Executive at Enterpret

New York, New York, United States

Enterpret Logo
Not SpecifiedCompensation
N/AExperience Level
N/AJob Type
Not SpecifiedVisa
N/AIndustries

Requirements

  • 7+ years of experience in enterprise software sales, with a proven track record of closing new logos in high-growth SaaS environments
  • Strong prospecting and pipeline generation skills; comfortable leading outbound efforts
  • Deep experience in consultative and complex sales, ideally with multi-stakeholder enterprise buyers
  • Demonstrated ability to run full-cycle deals, from discovery to negotiation and close
  • Familiarity with AI, analytics, or data-driven technologies, and the ability to articulate business impact
  • Proficiency with sales tools including Salesforce (SFDC), Gong, and Outreach
  • Exceptional communication, presentation, and negotiation skills across executive and technical audiences
  • Comfortable operating in high-growth, high-ambiguity environments where you help shape process as you sell

Responsibilities

  • Drive new logo acquisition within the enterprise segment, owning the full sales cycle from prospecting through close
  • Build and manage a healthy pipeline through a combination of outbound efforts and inbound leads
  • Execute a consultative, Challenger-style sales approach, uncovering customer needs and reframing business challenges through the lens of Customer Intelligence
  • Apply Force Management value selling frameworks to position Enterpret’s Customer Intelligence platform effectively
  • Collaborate with Pre-Sales to deliver compelling demos, proposals, and business cases that clearly articulate Enterpret’s value
  • Negotiate contracts, handle complex buying processes, and manage multi-stakeholder deals with precision
  • Maintain accurate forecasting and pipeline hygiene within Salesforce (SFDC) and other core systems
  • Provide customer and market feedback to influence go-to-market and product strategy

Skills

Enterpret

Transforms customer feedback into actionable insights

About Enterpret

Enterpret specializes in turning customer feedback into actionable insights that help product companies grow. The platform uses adaptive AI models to unify and categorize feedback from various sources, allowing teams to gain precise insights that inform product development. It features a user-friendly interface with easy-to-build dashboards and automated summaries, making it accessible for non-technical users. A standout feature is its semantic search, which helps users understand the intent behind customer feedback. Enterpret's Custom Unified Feedback Taxonomy structures unstructured feedback and adapts over time, ensuring insights remain relevant. The company differentiates itself by providing dedicated data auditors and customer success managers to keep the platform effective. The goal is to empower product teams to prioritize and build products that truly resonate with their customers.

San Francisco, CaliforniaHeadquarters
2020Year Founded
$24.4MTotal Funding
SERIES_ACompany Stage
Data & Analytics, Consumer Software, AI & Machine LearningIndustries
11-50Employees

Benefits

Health Insurance
Dental Insurance
Vision Insurance
401(k) Retirement Plan
401(k) Company Match
Paid Vacation
Parental Leave

Risks

Increased competition from established players like Medallia and Qualtrics.
Dependence on key clients like Canva, Notion, and Monday.com poses a risk.
Challenges in scaling operations while maintaining service quality post-Series A funding.

Differentiation

Enterpret uses adaptive AI models for precise customer feedback insights.
The platform features a Custom Unified Feedback Taxonomy for structured feedback analysis.
Enterpret offers a user-friendly interface with semantic search for non-technical users.

Upsides

Enterpret raised $20.8M in Series A to scale operations and deploy no-code AI agents.
Integration with LLMs enhances semantic search capabilities for nuanced feedback understanding.
Partnerships with platforms like Census enable seamless data integration and analytics.

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