This dataset of 289,870 people sampled across TikTok, X, and Reddit reveals statistics of employee engagement in 2024 to find out whether employees consider themselves engaged, why they were engaged, what would make them more engaged, and to learn more about their demographics.

This dataset comes from the Biennial City of Tempe Employee Survey questions related to employee engagement. Survey respondents are asked to rate their level of agreement on a scale of 5 to 1, where 5 means "Strongly Agree" and 1 means "Strongly Disagree".This dataset includes responses to the following statements: Overall, I am satisfied with the level of employee engagement in my Department. I have been mentored at work. Overall, how satisfied are you with your current job? Participation in the survey is voluntary and confidential.This page provides data for the Employee Engagement performance measure. The performance measure dashboard is available at 2.13 Employee Engagement.Additional Information Source: Community Attitude Survey Contact:  Wydale Holmes Contact E-Mail:  wydale_holmes@tempe.govData Source Type:  ExcelPreparation Method:  Data received from vendor (Community Survey)Publish Frequency:  AnnualPublish Method:  ManualData Dictionary

Employee engagement in the world increased from 2011 to 2020, but dropped slightly the next years. It stood at ** percent in 2022 and 2023. It was at its highest in 2020 when it reached ** percent.

Global employee engagement increased steadily from 2009 to 2023, but was still at only ** percent. A lack of involvement and enthusiasm of workers at their workplace can cost companies trillions of dollars in lost income.

The Employee Engagement Index (EEI) assesses the critical conditions conducive for employee engagement (e.g., effective leadership, work which provides meaning to employees). The index is comprised of three subfactors: Leaders Lead, Supervisors, and Intrinsic Work Experience.

Of the G20 countries, employees in the ************* had the highest levels of engagement at work in 2023. Meanwhile, employees in ***** felt the lowest levels of workplace engagement. A lack of employee engagement can lead to companies worldwide losing trillions of dollars each year.

Employee Engagement Enterprise Performance Indicator Data

Employee engagement data from an employee survey conducted by Pierce County and completed voluntarily by employees. Numeric responses correspond with the following answers: 0=N/A, 1=Strongly Disagree, 2=Disagree, 3=Agree, 4=Strongly Agree.

In 2022, employee engagement across all world regions dropped. Asia Pacific and Sub-Saharan Africa had the highest scores at ** percent, whereas Europe had the lowest at ** percent, with Middle East and North Africa following at ** percent.

This dataset provides processed and normalized/standardized indices for the management tool group focused on 'Talent & Employee Engagement', including concepts like Employee Engagement Surveys/Systems and Corporate Codes of Ethics. Derived from five distinct raw data sources, these indices are specifically designed for comparative longitudinal analysis, enabling the examination of trends and relationships across different empirical domains (web search, literature, academic publishing, and executive adoption). The data presented here represent transformed versions of the original source data, aimed at achieving metric comparability. Users requiring the unprocessed source data should consult the corresponding Talent/Engagement dataset in the Management Tool Source Data (Raw Extracts) Dataverse. Data Files and Processing Methodologies: Google Trends File (Prefix: GT_): Normalized Relative Search Interest (RSI) Input Data: Native monthly RSI values from Google Trends (Jan 2004 - Jan 2025) for the query "corporate code of ethics" + "employee engagement" + "employee engagement management". Processing: None. Utilizes the original base-100 normalized Google Trends index. Output Metric: Monthly Normalized RSI (Base 100). Frequency: Monthly. Google Books Ngram Viewer File (Prefix: GB_): Normalized Relative Frequency Input Data: Annual relative frequency values from Google Books Ngram Viewer (1950-2022, English corpus, no smoothing) for the query Corporate Code of Ethics+Employee Engagement Programs+Employee Engagement Surveys+Employee Engagement. Processing: Annual relative frequency series normalized (peak year = 100). Output Metric: Annual Normalized Relative Frequency Index (Base 100). Frequency: Annual. Crossref.org File (Prefix: CR_): Normalized Relative Publication Share Index Input Data: Absolute monthly publication counts matching Engagement/Ethics-related keywords [("corporate code of ethics" OR ...) AND (...) - see raw data for full query] in titles/abstracts (1950-2025), alongside total monthly Crossref publications. Deduplicated via DOIs. Processing: Monthly relative share calculated (Engage/Ethics Count / Total Count). Monthly relative share series normalized (peak month's share = 100). Output Metric: Monthly Normalized Relative Publication Share Index (Base 100). Frequency: Monthly. Bain & Co. Survey - Usability File (Prefix: BU_): Normalized Usability Index Input Data: Original usability percentages (%) from Bain surveys for specific years: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Processing: Semantic Grouping: Data points across related names treated as a single conceptual series representing Talent/Engagement focus. Normalization: Combined series normalized relative to its historical peak (Max % = 100). Output Metric: Biennial Estimated Normalized Usability Index (Base 100 relative to historical peak). Frequency: Biennial (Approx.). Bain & Co. Survey - Satisfaction File (Prefix: BS_): Standardized Satisfaction Index Input Data: Original average satisfaction scores (1-5 scale) from Bain surveys for specific years (same names/years as Usability). Processing: Semantic Grouping: Data points treated as a single conceptual series. Standardization (Z-scores): Using Z = (X - 3.0) / 0.891609. Index Scale Transformation: Index = 50 + (Z * 22). Output Metric: Biennial Standardized Satisfaction Index (Center=50, Range?[1,100]). Frequency: Biennial (Approx.). File Naming Convention: Files generally follow the pattern: PREFIX_Tool_Processed.csv or similar, where the PREFIX indicates the data source (GT_, GB_, CR_, BU_, BS_). Consult the parent Dataverse description (Management Tool Comparative Indices) for general context and the methodological disclaimer. For original extraction details (specific keywords, URLs, etc.), refer to the corresponding Talent/Engagement dataset in the Raw Extracts Dataverse. Comprehensive project documentation provides full details on all processing steps.

The Employee Satisfaction Survey dataset is a comprehensive collection of information regarding employees within a company. It includes essential details such as employee identification numbers, self-reported satisfaction levels, performance evaluations, project involvement, work hours, tenure with the company, work accidents, promotions received in the last 5 years, departmental affiliations, and salary levels. This dataset offers valuable insights into the factors influencing employee satisfaction and can be used to analyze and understand various aspects of the workplace environment.

This statistic shows the results of a survey, conducted annually from 2002 to 2012, among American employees regarding their engagement in the workplace. In 2012, 18 percent of respondents stated they were deliberately not engaged in their work, while 30 percent stated they were.

In 2021, almost ** percent of professionals worldwide revealed that employee in their organization are highly engaged in delivering customer experience (CX). During the survey, **** percent of customers rated organizations' CX capability seven out of ten (7/10).

This dataset contains raw, unprocessed data files pertaining to the management tool group focused on 'Talent & Employee Engagement', including concepts like Employee Engagement Surveys/Systems and Corporate Codes of Ethics. The data originates from five distinct sources, each reflecting different facets of the tool's prominence and usage over time. Files preserve the original metrics and temporal granularity before any comparative normalization or harmonization. Data Sources & File Details: Google Trends File (Prefix: GT_): Metric: Relative Search Interest (RSI) Index (0-100 scale). Keywords Used: "corporate code of ethics" + "employee engagement" + "employee engagement management" Time Period: January 2004 - January 2025 (Native Monthly Resolution). Scope: Global Web Search, broad categorization. Extraction Date: Data extracted January 2025. Notes: Index relative to peak interest within the period for these terms. Reflects public/professional search interest trends. Based on probabilistic sampling. Source URL: Google Trends Query Google Books Ngram Viewer File (Prefix: GB_): Metric: Annual Relative Frequency (% of total n-grams in the corpus). Keywords Used: Corporate Code of Ethics+Employee Engagement Programs+Employee Engagement Surveys+Employee Engagement Time Period: 1950 - 2022 (Annual Resolution). Corpus: English. Parameters: Case Insensitive OFF, Smoothing 0. Extraction Date: Data extracted January 2025. Notes: Reflects term usage frequency in Google's digitized book corpus. Subject to corpus limitations (English bias, coverage). Source URL: Ngram Viewer Query Crossref.org File (Prefix: CR_): Metric: Absolute count of publications per month matching keywords. Keywords Used: ("corporate code of ethics" OR "employee engagement" OR "employee engagement programs" OR "employee engagement surveys") AND ("human resources" OR "management" OR "organizational" OR "culture" OR "development" OR "performance") Time Period: 1950 - 2025 (Queried for monthly counts based on publication date metadata). Search Fields: Title, Abstract. Extraction Date: Data extracted January 2025. Notes: Reflects volume of relevant academic publications indexed by Crossref. Deduplicated using DOIs; records without DOIs omitted. Source URL: Crossref Search Query Bain & Co. Survey - Usability File (Prefix: BU_): Metric: Original Percentage (%) of executives reporting tool usage. Tool Names/Years Included: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 2003, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2002/708; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Bain & Co. Survey - Satisfaction File (Prefix: BS_): Metric: Original Average Satisfaction Score (Scale 0-5). Tool Names/Years Included: Corporate Code of Ethics (2002); Employee Engagement Surveys (2012, 2014); Employee Engagement Systems (2017, 2022). Respondent Profile: CEOs, CFOs, COOs, other senior leaders; global, multi-sector. Source: Bain & Company Management Tools & Trends publications (Rigby D., Bilodeau B., Ronan C. et al., various years: 2003, 2013, 2015, 2017, 2023). Data Compilation Period: July 2024 - January 2025. Notes: Data points correspond to specific survey years. Sample sizes: 2002/708; 2012/1208; 2014/1067; 2017/1268; 2022/1068. Reflects subjective executive perception of utility. File Naming Convention: Files generally follow the pattern: PREFIX_Tool.csv, where the PREFIX indicates the data source: GT_: Google Trends GB_: Google Books Ngram CR_: Crossref.org (Count Data for this Raw Dataset) BU_: Bain & Company Survey (Usability) BS_: Bain & Company Survey (Satisfaction) The essential identification comes from the PREFIX and the Tool Name segment. This dataset resides within the 'Management Tool Source Data (Raw Extracts)' Dataverse.

Structured data on optimal survey frequencies, question counts, and timing recommendations for different types of employee surveys including engagement surveys, pulse surveys, and specialized surveys.

This page provides information for the Employee Engagement performance measure.

See "About" for field info. Dataset shows engagement level of city of Las Vegas employees based on questions from annual employee engagement survey.

Employee Engagement Software Market Outlook

According to our latest research, the global employee engagement software market size reached USD 1.82 billion in 2024, reflecting growing demand for digital workplace solutions across sectors. The market is expected to expand at a CAGR of 11.4% from 2025 to 2033, with projections indicating a value of USD 4.33 billion by 2033. This sustained growth is primarily driven by the increasing need for organizations to foster employee satisfaction, productivity, and retention in a rapidly evolving hybrid and remote work environment.

One of the primary growth factors for the employee engagement software market is the widespread adoption of remote and hybrid work models. As organizations across the globe continue to adapt to flexible work arrangements, there is a heightened need for digital platforms that can seamlessly connect, engage, and motivate employees regardless of their physical location. This shift has led to a surge in demand for solutions that facilitate real-time communication, collaborative project management, and timely feedback, all of which are essential for maintaining high levels of employee engagement. Additionally, the increasing focus on employee well-being, mental health, and work-life balance has prompted companies to invest in tools that can monitor engagement levels, identify areas for improvement, and proactively address workforce concerns, further propelling market expansion.

Another significant driver of the employee engagement software market is the growing emphasis on data-driven decision-making within human resources departments. Modern employee engagement platforms are equipped with advanced analytics and reporting features that enable organizations to collect, analyze, and interpret employee feedback and engagement metrics in real time. This capability empowers HR leaders to make informed decisions regarding talent management, organizational development, and employee retention strategies. By leveraging actionable insights generated by these platforms, companies can tailor their engagement initiatives, optimize workplace culture, and drive measurable improvements in productivity and satisfaction. The integration of artificial intelligence and machine learning further enhances these solutions, enabling predictive analytics and personalized engagement recommendations.

Moreover, the rising importance of employee recognition, rewards, and continuous feedback in contemporary workplace culture is fueling the adoption of engagement platforms. Organizations are increasingly recognizing the value of acknowledging employee contributions, fostering a sense of belonging, and building a positive work environment. Employee engagement software provides a centralized platform for managing recognition programs, facilitating peer-to-peer appreciation, and delivering timely feedback, all of which contribute to higher morale and lower turnover rates. This trend is particularly pronounced in competitive industries where talent retention is critical to business success. As a result, the market is witnessing robust growth across various sectors, including BFSI, healthcare, IT, and manufacturing.

In the context of employee engagement, the rise of the Employee Retention Platform is becoming increasingly significant. These platforms are designed to help organizations retain their top talent by creating a more engaging and satisfying work environment. By leveraging data analytics and feedback mechanisms, Employee Retention Platforms provide insights into employee satisfaction and areas that require attention. This proactive approach allows companies to address potential issues before they lead to turnover, thereby maintaining a stable and motivated workforce. As organizations continue to navigate the challenges of hybrid and remote work models, the role of Employee Retention Platforms becomes even more crucial in ensuring that employees feel valued and connected to their workplace.

From a regional perspective, North America currently dominates the employee engagement software market, accounting for the largest share in 2024, followed by Europe and Asia Pacific. The region's leadership is attributed to the presence of numerous technology-driven enterprises, early adoption of digital HR solutions, and a strong culture of innovation in workplace management. Howe

This page provides data for the Employee Engagement performance measure. The performance measure dashboard is available at 2.13 Employee Engagement.Additional InformationSource: paper and digital survey submissionsContact: Aaron PetersonContact E-Mail: Aaron_Peterson@tempe.govData Source Type: ExcelPreparation Method: NAPublish Frequency: biennial

Snapshot img

Employee Engagement Software Market Size 2024-2028

The employee engagement software market size is forecast to increase by USD 325.9 million, at a CAGR of 6.8% between 2023 and 2028.

The market is driven by the increasing need for workforce diversity management and the rising adoption of digital Human Resource (HR) technology. Companies are recognizing the importance of fostering an inclusive work environment and are turning to employee engagement software solutions to manage diversity initiatives, track progress, and promote equal opportunities. Additionally, the shift towards digital HR technology is gaining momentum, as organizations seek to streamline processes, enhance productivity, and improve employee experiences. However, this market also faces challenges.
Technical constraints, such as data security and privacy concerns, can hinder the adoption of employee engagement software. Moreover, poor customer service can negatively impact user experience and hinder the market's growth. To capitalize on opportunities and navigate these challenges effectively, companies must prioritize addressing these issues, ensuring robust data security measures and delivering exceptional customer service to maintain a competitive edge.

What will be the Size of the Employee Engagement Software Market during the forecast period?

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The market continues to evolve, with dynamic market activities shaping its landscape. Employee journey mapping tools enable organizations to track and optimize the employee experience, while productivity tracking software ensures efficient workflows. Integrated employee experience platforms offer mobile engagement, peer-to-peer feedback, goal setting, and performance review functionalities. Performance management systems, pulse survey software, and employee recognition programs foster continuous employee feedback and engagement. Knowledge sharing platforms, virtual recognition awards, and workplace collaboration tools promote a culture of innovation and learning. Culture building initiatives, HR analytics dashboards, and employee wellbeing platforms prioritize employee satisfaction and retention. Employee training platforms, team communication tools, talent management systems, and internal communications software streamline work processes and improve team coordination.
Engagement survey tools, employee onboarding systems, employee voice platforms, gamified engagement platforms, leadership development programs, and employee sentiment analysis tools further enhance the employee experience. These solutions adapt to the ever-changing needs of various sectors, ensuring a seamless and engaging employee journey. The integration of these tools fosters a productive and collaborative work environment, ultimately contributing to the overall success of an organization.

How is this Employee Engagement Software Industry segmented?

The employee engagement software industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2024-2028, as well as historical data from 2018-2022 for the following segments.

Deployment

  Cloud-based
  On-premises


Geography

  North America

    US


  Europe

    Germany
    UK


  APAC

    China
    Japan


  Rest of World (ROW)

By Deployment Insights

The cloud-based segment is estimated to witness significant growth during the forecast period.

Cloud-based employee engagement software is experiencing significant growth due to its ability to provide a unified platform for gathering, storing, and accessing employee data from anywhere in the world. This includes features such as productivity tracking, goal setting, performance reviews, peer-to-peer feedback, and employee recognition programs. The use of cloud technology enables enterprises to accommodate unique HR requirements, ensure better reliability, and improve visibility into employee engagement metrics. Cloud-based solutions also offer advantages in terms of cost and flexibility. Instead of large, one-time investments and periodic expenses for maintenance and updates associated with on-premises software, cloud-based applications require regular payments.

This business model allows enterprises to allocate resources more effectively and adapt to changing needs. Additionally, cloud-based employee engagement software supports various tools and platforms, such as pulse surveys, knowledge sharing, team communication, and talent management systems. These tools contribute to a more immersive and harmonious employee experience, fostering a culture of collaboration, continuous learning, and open communication. Moreover, cloud-based solutions facilitate culture building initiatives, employee wellbeing platforms, and employee sentiment analysis, all essential components of a successful engagemen