Reston, VA (18 Oct 2018) — Reston, Virginia-based company, VOZIQ, announced today the release of a major update to its Predictive Text Analytics Platform with redesigned user interface, enhanced user experience, and operationalization features aimed at driving proactive customer churn prevention strategies within enterprise recurring revenue businesses.
VOZIQ’s customer retention solution blends data from multiple internal data sources in an enterprise, such as contact centers, marketing, financial, operational, field support and customer satisfaction surveys. This feed is unified into a single database to identify emerging customer risk. Built on AWS and high-performance ElasticSearch engine, the solution’s unique ability to apply NLP to large volumes of unstructured data and automatically detect churn signals from it results in producing not only better-performing predictive churn models but also helps businesses understand churn drivers using advanced text analytics on contact center call logs from all past interactions of every customer.
While speaking about the new release, Suresh Akula, co-founder and CTO of VOZIQ, said, “Customer retention in an enterprise is a complex process which requires optimizing multiple touchpoints across the customer lifecycle. While most companies optimize customer retention with either process improvements or a single predictive model, VOZIQ detects churn risk or retention opportunities at each stage of the life cycle, using multiple predictive models, each individually optimized to reduce churn risk during onboarding, servicing, and retention stages. These predictive models also help improve winback performance by reactivating some of the cancelled customers at very low cost.”
“In addition to improved predictive models, the redesigned solution now offers updated dashboards that make it easy for operational leaders to stay focused on the most important risks and opportunities with purpose-built dashboards to track churn drivers, disconnect reasons, renewals, Winback, NPS drivers, and retention team performance. The solution even automatically builds competitive intelligence by extracting competition names from contact center call logs,” Suresh further said.
The all-new user interface brings together the best of front-end technologies and modern design language to create an effortless user experience, especially for business users who need ease-of-use and a clean, intuitive interface.
Key features of the latest version include:
New predictive models: The application now incorporates the predictive intelligence from new machine learning models developed to address specific needs of the retention apparatus in a recurring revenue enterprise. The underlying predictive models are listed below:
- Predictive churn
- Predictive winback
- Predictive NPS
- Proactive offer optimization
Business user-friendly dashboards: In the updated version, the interactive dashboards and their arrangement in the application menu have been rethought to provide quicker access to the most important data and insights across the enterprise retention process. The 20+ new dashboards are grouped under these categories:
- Customer Experience
- Customer Retention
- Marketing Intelligence
- Retention Agent Performance
Redesigned scheduled reports: Redesigned daily, weekly, and monthly scheduled reports that blend customer and employee behaviors to improve retention performance have undergone a design makeover to facilitate quick identification of opportunities by various levels of operational leaders.
Speaking about the redesign effort, Dr. Sunil Issar, Head of Professional Services said, “VOZIQ recently conducted interviews* with senior customer retention leaders from industries such as telecommunications, home security, insurance and utility providers. The latest update reflects the priorities, needs and expectations of these respondents by bringing creation and consumption of retention intelligence to support multiple strategies into a single platform, driven by AI and Machine Learning.”
*To learn more, download VOZIQ’s Customer Retention Survey – 2018.