SmartRent, Inc. Public Market Comparables

Find the most relevant public market comparables for SmartRent, Inc., including EV/Revenue and EV/EBITDA multiples to help you make informed investment decisions.

Company Overview

SmartRent, Inc. is a leading provider of smart communities and smart operations solutions for the rental housing industry. Its end-to-end ecosystem automates operations, protects assets, reduces energy consumption, and enhances resident experiences. The company offers purpose-built software and hardware, along with end-to-end implementation and support.

Business Model

Subscription-based services for smart home and building technology, along with licensing and implementation fees. Provides an integrated platform for property owners, managers, and residents.

Target Customers

Property owners, managers, and residents in the multifamily rental housing industry.

Specific Focus

Smart home and building technology for the rental housing industry

Location

Scottsdale, Arizona

CEO

Daryl Stemm 

Industry

Software & services

Sub Sector

Software and Services, Real Estate Technology, Internet of Things (IoT)

3yr Revenue Growth

351%

Public Market Comparables

Below are the key valuation metrics for companies similar to SmartRent, Inc. in the Technology sector. These metrics can help you understand how the market values companies with similar business models and growth profiles.

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As a leading player in the Software & services industry within the Technology sector, SmartRent, Inc. operates in the specialized Software and Services, Real Estate Technology, Internet of Things (IoT) sub-sector. Understanding how SmartRent, Inc. compares to its public market comps is essential for accurate valuation and strategic decision-making.

Our comprehensive analysis includes detailed comparables (compsets) featuring similar companies in the Software and Services, Real Estate Technology, Internet of Things (IoT) space, with complete financial metrics, growth trajectories, and competitive positioning insights that go beyond the surface-level data shown above.

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