VOZIQ
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About
VOZIQ is an AI-powered customer retention platform designed for recurring revenue businesses. It uses 10+ machine learning models to proactively identify at-risk customers, predict and manage NPS risks, and drive personalized price increase campaigns. The platform offers behavioral intelligence, customer intent analytics, agent guidance, and intelligent IVR routing, helping businesses maximize customer lifetime value (CLV). VOZIQ has delivered over $750 million in CLV to its clients and offers a range of solutions across multiple industries and use cases.
Platform
Features
• behavioral intelligence
• customer intent analytics
• agent guidance
• intelligent ivr routing
• predictive nps management
• predictive price increase
• predictive customer retention
FAQs
Which data can I use? Does my business have enough data to drive VOZIQ’s AI?
VOZIQ can work with any structured and unstructured customer data. While structured data will help in segmentation, unstructured data will improve the accuracy of predictions in multiples by infusing very early-stage risk signals from customer conversations. We carefully select mission-critical data sources based on needs and goals assessment. Typical data sources we use include: 1. Direct feedback and sentiment (email/SMS/phone surveys), 2. Indirect feedback and sentiment (contact center/web/mobile interactions), and 3. Inferred feedback from other time series and IoT data like usage/trouble histories. Integrating this engagement and interaction data with billing, transactions, demographic, and cancel history allows us to develop the most accurate customer profiles. This enables machine learning models to assign not only an accurate churn score but also an NPS score, cancel reason, likely contract extension, likely intervention through either rate change or add-on equipment for 100% of customers for micro-segmentation, and targeted campaigns through contact center and marketing channels.
How do I know if my data is good enough for AI?
Data is almost always scattered and unprepared. We have expertise in dealing with such data and the necessary processes and technology fine-tuned on millions of customer records to make it ready for driving AI-powered retention campaigns.
Why are my data and models not delivering results?
Three pillars of any analytics program are - * Data * Intelligence * Actions In our experience, it takes synergy of all these three areas to deliver a demonstrable impact on profits and revenue. The rule of thumb for improving retention effectiveness is to start backward from existing points of impact, such as care/technical/retention/service/marketing. This helps identify quick-hit opportunities and make these points aware of risk/value by augmenting them with predictive intelligence from multiple AI models.
What about my existing investments?
VOZIQ works with your existing systems and complements your teams. There is little disruption.
How long a time horizon are we looking at?
VOZIQ typically starts delivering results (not just models) within the first quarter. By the first year, you should see a clear drop in attrition rates. The result compounds over a 3-year/5-year timeframe to deliver tens of millions of dollars in revenue from proactive customer saves, reduced service costs, and improved lifetime value.
Where do we start?
We follow a step-by-step plan to ensure alignment and value: * Kickstart with a needs assessment to identify top use cases and prepare a business case. * Demonstrate initial ROI from 2-3 use cases before releasing further investment. Expand AI use cases using proven results and execution capabilities from initial campaigns.
Why is VOZIQ Better than Other Retention Solutions
[Learn more](https://voziq.ai/why-voziq/) why VOZIQ is the right customer retention partner for you. What’s more: * Backed by a team with proven security industry expertise * Quick time-to-value with our build-operate-transfer delivery model
Job Opportunities
Manager – Database Engineering
AI-powered customer retention platform maximizing CLV for recurring revenue businesses through proactive identification of at-risk customers and personalized interventions.
Responsibilities:
guiding the team
designing robust database architectures
establishing efficient processes
fostering a culture of excellence in database management
work closely with cross-functional teams to ensure that our databases are scalable, secure, and optimized for performance
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