CallTrackingMetrics is the only SaaS platform that uses call tracking and conversion intelligence to inform contact center automation--resulting in a more personalized customer experience. Find out which marketing campaigns are generating leads or conversions and use that data for automated call flows and to power your contact centre. Our phone, text, online, and live chat tools allow you to unify communications across your organization. CallTrackingMetrics is trusted by more than 100,000 users worldwide to manage communications for their sales, marketing, and service teams.
Call tracking features include reliable dynamic numbers insertion (DNI), for session-level attribution, local and toll-free tracking numbers, and omnichannelattribution across calls, texts and form fills.
Contact center features include a browser-based softphone and smart routing options.
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ADAudit Plus enhances the security and compliance of your Windows Server environment by delivering comprehensive insights into all operational activities. It offers a detailed overview of modifications made to Active Directory (AD) resources, encompassing AD objects and their respective attributes, group policies, and more. By conducting thorough AD audits, organizations can identify and mitigate insider threats, misuse of privileges, and other signs of potential security breaches, thereby bolstering their overall security framework. The tool enables users to monitor intricate details within AD, including entities such as users, computers, groups, organizational units (OUs), group policy objects (GPOs), schemas, and sites, along with their associated attributes. Furthermore, it tracks user management activities like the creation, deletion, password resets, and alterations in permissions, providing insights into the actions taken, the responsible individuals, the timing, and the originating locations. Additionally, it allows organizations to monitor the addition or removal of users from security and distribution groups, ensuring that access privileges are kept to the necessary minimum, which is critical for maintaining a secure environment. This level of oversight is vital for proactive security management and compliance adherence.
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OMNI 3D
OMNI 3D seismic survey design software allows users to craft optimal designs in both 2D and 3D for various types of surveys, including land, marine, ocean-bottom cable (OBC), transition zone, vertical seismic profile (VSP), and multicomponent surveys. The software comes equipped with advanced analysis modules that facilitate the examination of geometric effects, the identification of geometry artifacts, the generation of synthetic data, and the construction and ray tracing of both 2D and 3D geological models. Its advanced tools, user-friendly interface, and capability for managing multiple projects make OMNI 3D a vital resource that unites exploration and production asset teams with acquisition teams. As a result, OMNI 3D software has become the benchmark in the industry for geoscientists engaged in survey planning, design, quality control, and modeling on a global scale. Furthermore, it offers sophisticated analysis capabilities, including assessments of 3D geometry, synthetic data generation, quality estimates for traces leveraging 5D interpretation, AVO response analysis, subsurface horizon illumination with any survey geometry, and poststack time migration illumination utilizing Fresnel zone binning, thereby enhancing the overall effectiveness of seismic surveys. This comprehensive set of features ensures that users are equipped with the necessary tools to optimize their seismic survey designs efficiently.
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Paradise
Paradise employs advanced unsupervised machine learning alongside supervised deep learning techniques to enhance data interpretation and derive deeper insights. It creates specific attributes that help in extracting significant geological information, which can then be utilized for machine learning analyses. The system identifies attributes that exhibit the most variation and influence within a geological context. Additionally, it visualizes neural classes and their corresponding colors from Stratigraphic Analysis, which reveal the spatial distribution of different facies. Faults are detected automatically through a combination of deep learning and machine learning methods. Furthermore, it allows for a comparison between machine learning classification outcomes and other seismic attributes against traditional high-quality logs. Lastly, it generates both geometric and spectral decomposition attributes across a cluster of computing nodes, achieving results in a fraction of the time it would take on a single machine. This efficiency enhances the overall productivity of geoscientific research and analysis.
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