The global Social Employee Recognition Systems Market is expected to be flourished by increased productivity. Social employee recognition systems empower organizations to recognize and celebrate employee achievements and milestones publicly. Social recognition improves employee engagement and productivity while also supporting communication across distributed teams. Recognition programs help make employees feel valued by appreciating their efforts and contributions. With social recognition systems, organizations can develop a culture of appreciation that cultivates loyalty and boost retention.
Social employee recognition software allows managers to acknowledge, thank, and praise employees through digital badges, rewards, and leaderboards visible on social platforms. This fosters competitiveness and encourages employees to work towards individual and team goals. Social recognition feeds motivate participation in challenges and gamify the workplace to increase engagement.
The global Social Employee Recognition Systems Market is estimated to be valued at US$ 1.12 billion in 2024 and is expected to exhibit a CAGR of 10% over the forecast period 2024 to 2031, as highlighted in a new report published by Coherent Market Insights.
Increased productivity is one of the key drivers of the social employee recognition systems market. When employees feel appreciated for their efforts, they are more motivated to work productively. Social recognition satisfies the basic human need for appreciation and impacts performance positively. It boosts employee satisfaction, reduces turnover, and enhances output. The other driver is improved communication in distributed teams. Social platforms break geographical barriers and allow organizations to recognize remote employees virtually. This strengthens bonds between on-site and off-site staff through public kudos and comments. Social engagement fosters collaboration even when teams are scattered.
The global social employee recognition systems market is segmented on the basis of offering into platforms and services. The platforms segment is dominating the market since most of the organizations are adopting employee recognition platforms to recognize and reward their employees. These platforms provide various features like creating and sharing rewards, gift cards, nomination forms, leaderboards etc. which help in remote employee engagement.
Political: The social employee recognition systems market is positively impacted by support for workplace employee engagement initiatives by various governments across the world.
Economic: Rising per capita incomes and spending on employee welfare programs are helping the growth of the market. Continuous shift towards non-monetary rewards is also aiding market expansion.
Social: Changing workplace culture trends focused more on employee satisfaction and recognition are driving demand. Recognition boosts employee morale and retention in organizations.
Technological: Advancements in cloud and mobile technologies have enabled the development of sophisticated employee recognition platforms. Platform providers are also integrating with HRIS, payroll and other systems for automated rewards.
The Global Social Employee Recognition Systems Market Size is expected to witness high growth over the forecast period of 2024 to 2031.
Regional analysis: North America region holds the largest share in the social employee recognition systems market led by U.S. and Canada. Organizations in these countries are increasingly focusing on employee engagement and retention through flexible rewards and recognition programs.
Key players operating in the social employee recognition systems market are GloboForce Ltd., Achievers Corporation, Kudos Inc., Madison, Vmware, Inc. Recognize Services Inc., Jive Communications, BI Worldwide. These key players are focused on developing innovative cloud-based platforms integrated with advanced analytics capabilities. They are also expanding into newer markets through partnerships and acquisitions.
1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it