Analyze All Your Data in One Place with CustomerView’s Omni-Channel Analytics

Posted by Helene Servillon on Jan 9, 2018 5:14:30 PM


In a big data world, there’s a lot going on. Enterprises in particular are struggling to optimize and leverage all of the data they collect and monitor. In fact, 58% of businesses use eight channels to communicate with their customers, according to an Aberdeen study.

Given that, how do multiple departments within a large enterprise efficiently keep up with this wealth of structured and unstructured data? The same Arbedeen study exclaims that, 85% of organizations struggle to make informed decisions when managing customer conversations because their data is captured and stored in these 8 disparate, disconnected systems. If you’re looking to be the other 15% of companies, it’s time to get to know CustomerView, the solution for omni-channel customer analytics.

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What Is CustomerView?

CustomerView is a customizable omni-channel customer analytics application that allows you to measure every touchpoint along the customer interaction journey - it takes the pain out of aggregating data from your company’s various data sources (call recorder, contact center, CRM, web, chat system, social media, etc) and simply interconnects them to analyze, categorize, score and tag unstructured data. This data is then beautifully visualized in easy to consume dashboards, graphs and KPIs to deliver actionable insights across the Enterprise.

How Does The Technology Work?

CustomerView allows enterprises to cleanse, organize and ingest their current archives of data to build KPIs. The magic sauce that enables these capabilities is CustomerView’s Natural Language Processing (NLP), machine learning technology and easy to navigate interface that provides you with the tools to create near real-time alerts, triggers and filters to drill down on areas of your enterprise that you need to investigate. I.e. who are your best sales agents and why, are your agents adhering to mandatory scripts with proper greetings, how is your new product offering campaign performing this week, etc.

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To dig more into the technical details, CustomerView’s NLP engine powers semantic-based topic extraction and sentiment scoring which enables automatic tagging and categorization of keywords and conversation topics between agents and customers. To put a cherry on top of the technology stack sundae, CustomerView is also powered by Semantic Parsing Language (SemPaL), which enables complex queries of unstructured data to QA agent conversations and understand intent of a phrase for contextual scoring.

So, what does that all mean? This gives supervisors and business analysts the ability to automatically segment calls into buckets and flexibly score calls based on customer type. For example, a retention and sales acquisition support line will not have the same QA scorecard as they cater to different customer needs (support vs. interested buyer questions), and agent goals (support vs. sales scripts). 


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What Problems Does It Solve?

When your company starts to scale and implements various software systems, getting a holistic view of your customer’s satisfaction levels and business performance can be a mess and multi-person job within itself. With CustomerView, you can analyze multiple parts of your enterprise and drill down on problem areas that may be costing your company money.

Your organization’s call center is at the forefront of customer interaction and is where everything from marketing to sales and customer service takes place. Thus, a polished Agent QA program will directly affect your customer’s experience and bottom-line. Just take a look at your current Agent QA program, how manual and time consuming is the process? What kind of results is it driving?

The Value of Automation


A speech analytics driven QA approach will eliminate human bias and emotion from your quality assurance evaluations and enable you to generate up to 100x the amount of data. Let’s face it; each and every QA advisor reviews calls a slightly different way, each and every time. Consistency in this measurement will provide more accurate, aggregated data that now tells a story, which can be influenced to institute changes as needed.

Top Use Cases

  • Auto QA
  • Voice of the Customer
  • Top Agent Modeling
  • Compliance
  • 100% NPS
  • First Call Resolution
  • AHT Reductions
  • Call Scoring
  • Script Monitoring

Is CustomerView for you? Give us a ping and let us know what problems you’re running into. Our team of experts are happy to schedule a quick call to help you evaluate this solution. Omni-channel customer analytics are one of the latest contact center trends to watch so don’t miss out!

Written by Helene Servillon

Helene leads Partner Marketing at VoiceBase, an API-based and enterprise grade speech analytics platform. She is focused on developing go-to-market strategies and rules of engagement for VoiceBase's channel and enterprise partners around the globe.
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What is Big Voice?

AI-powered speech analytics for the cloud

VoiceBase is defining the future of deep learning and communications by providing unparalleled access to spoken information for businesses to make better decisions. With flexible APIs developers and enterprises build scalable solutions with VoiceBase by embedding speech-to-text, speech analytics, and predictive analytics capabilities into any big voice application. 



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