Over the past two decades, information security scientists have conducted in-depth research in the area of security analytics to counter cyber-attacks that have challenged the security postures of corporate networks and data. Learning from this research has immensely benefited security analytic tools and contributed to their maturity, thereby enabling many organizations to implement them. While adoption of these tools has increased, understanding factors that impact the successful implementation of these tools has lagged and such understanding is critical to the information security practice. The literature review revealed the lack of a validated survey instrument dedicated to security analytic tools, which can help in extracting implementation factors that security professionals would consider to be critical for success. The focus of this research study was to develop a survey instrument and use the developed instrument to identify factors that impact the successful implementation of any security analytic tool, including big data based tools. Delphi method was used to develop the instrument in Phase 1 with the help of security analytic tool experts located in the United States of America, and the same instrument was used to collect responses during Phase 2 from practitioners located in North America. The researcher used Delphi method for establishing content validity, exploratory factor analysis for establishing construct validity and Cronbach's alpha for testing reliability. The Delphi study started with 16 experts in the first round, ended with 11 experts providing consensus in the fourth round. An exploratory factor analysis study performed during Phase 2, involving a sample size of 206, identified seven factors that impacted the successful implementation of security analytic tools. These factors are: large-scale security event analysis, functional utilization, incident detection and correlation analysis, governance and chief information security officer metrics, log source and use case management, threat and operational intelligence, real-time attack and anomaly detection. By defining metrics for these factors, practitioners could use these factors as key performance indicators to assess the success of security analytic tool implementation. Exploring causal relationships among identified factors, such as threat intelligence and incident detection, will help in tuning security analytic tools and products.