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Quesam

Quesam is a cutting-edge B2B SaaS platform that captures the essence of employee sentiment through a single, daily engagement question.

★ 2.7 average rating

Freemium • ProprietaryMacWindowsGoogle ChromeBy Sam Nadler / Jordan Metzner

About Quesam

Quesam is a cutting-edge AI-powered platform designed to revolutionize employee engagement by providing daily, insightful feedback tailored to enhance workplace morale and connectivity. By presenting just one thought-provoking question each day, Quesam seamlessly integrates into your team's workflow, making feedback collection a non-disruptive and engaging experience. This tool is particularly beneficial for remote and hybrid workforces, offering real-time insights into employee satisfaction (eSAT), net promoter scores (eNPS), and early warning signs (EWS) to address potential issues before they escalate. With its intuitive design and easy integration across various operating systems, Quesam fosters a culture of transparency and open communication, empowering teams to achieve higher levels of collaboration and productivity. Whether you're a small team or a large enterprise, Quesam adapts to your needs, providing the insights necessary to cultivate a loyal and committed workforce.

Key Features

  • ✓AI-Powered
  • ✓Employee Engagement
  • ✓Employee Performance Management
  • ✓Remote Work

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Frequently asked questions

What is Quesam?

Quesam is a cutting-edge B2B SaaS platform that captures the essence of employee sentiment through a single, daily engagement question. It is listed under the Freemium • Proprietary license model in the SaaS Lenz directory.

Is Quesam free to use?

Quesam is listed as Freemium • Proprietary in our directory. Pricing and plan details can change, so check the official website for current terms before committing.

What platforms does Quesam run on?

Quesam is available on Mac, Windows, Google Chrome, Software as a Service SaaS, Online, so you can use it across the devices your team already works with.

Who develops Quesam?

Quesam is developed by Sam Nadler / Jordan Metzner. You can find more background and documentation on the product's official website.