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Supervised vs. Unsupervised Learning: What’s the Difference (Plus Use Cases)

Uniphore

Supervised learning is best suited for things like: Structured data. Messy data with fewer labels requires unsupervised learning. Much like trying to uncover the secrets of a lost language, unsupervised learning relies on connections, patterns and trends in whatever data is available for training. Desired outcomes (i.e.,

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5 Reasons Why Traditional Retention Efforts Are Inadequate

VOZIQ

Structured Data Over-reliance. Organizations using traditional models rely on structured data – e.g., subscription information, billing details, payment history, and FICO scores, to name a few -. However, structured data is transactional, quantitative, and fails to answer ‘why’ a customer might cancel.

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Sprinklr named to IDG Insider Pro and Computerworld’s 2021 list of 100 Best Places to Work in IT

Sprinklr

At any given instance, this AI engine processes millions of unstructured and structured data points ingested from myriads of channels and software applications. Employees have the opportunity to work with the core of Sprinklr’s technology — our proprietary AI engine built with sophisticated deep machine learning algorithms.

CXM 96
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Confirmit Genius: Mining for Hidden Truths in Free-form Content

Confirmit

It is tightly integrated with Confirmit Horizons, our comprehensive, multichannel Voice of the Customer (VoC), Voice of the Employee (VoE), and Market Research platform, so you can easily combine structured data from surveys with the depth of insight and unprecedented level of detail available only in open-ended feedback.

VOE 40
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6 Reasons Why Unstructured Data Is Key to an Effective Retention Program

VOZIQ

This information includes customer data captured from contact center agent notes, surveys, emails, chats, and web forms. Traditional customer retention strategies only use structured data because it’s easier for their models to understand and be trained with.

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How Artificial Intelligence and Predictive Analytics Can Help You Reduce Customer Churn

CSAT.AI

The second challenge lies in whether it’s structured or unstructured data. Structured data is highly organized and readily searchable within a relational database, like a CRM. Unstructured data doesn’t often live in a database, but in a silo without any organizational structure to it.

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Five Keys To Driving Voice of the Customer Success

CX Accelerator

4) Tell a complete story with your data. Only using structured data in your VoC initiatives is like having a one-sided coin. Combine structured and unstructured feedback data in your analyses. It doesn’t tell the complete story. In fact, it could set you up for a lot of false positives.