Customer Experience (CX) Management

Turning customer feedback data into actionable analytics

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Did you know that 66% of consumers worldwide switched companies due to poor customer service last year?

Your customers talk about your business. Ease of access to mobile and social channels means that not only is it easier than ever before for your customers to share their experiences with your company to the world, but it’s also just as easy for new potential customers to discover and be influenced by these opinions. While this creates challenges to engage and interact with customers, it also opens up significant opportunities to optimize the customer journey into a seamless, personalized, outcome-driven experience. This customer-focused transformation prioritizes an improved customer experience, and aligns organizational objectives, processes and technology to create the optimal environment for satisfied customers.

Survey Analysis

Providing actionable feedback on products, the buying process, and customer support.

  • Customer satisfaction surveys measure how happy customers are with a company’s products and services. Survey analysis provides companies with feedback about everything from products to the buying process to support. Most organizations combine this powerful data with other forms of customer feedback to create actionable intelligence about the entire customer journey.

Voice of the Customer

Identifying and responding to the expectations, wants, and needs of customers.

  • VoC captures how customers feel about their experience with a business, product, or service. More and more businesses are building VoC programs to meet customer needs and stay ahead of the curve. These VoC programs identify and respond to the expectations, wants, and needs of customers, with the goal of improving customer satisfaction and loyalty.

Speech Analytics

Extract contextual meaning from audio recordings and analyzing it to find relevant business intelligence.

  • By incorporating deep contextual awareness, emotion, and situational discovery, we extract meaning from audio recordings and analyze it to find relevant business intelligence. Using natural language processing and sentiment scoring to capture the literal voice of the customer considering nuances like emotional data, including tone of voice, phrasing and punctuation.

Text Analytics

Analyzing unstructured text and transforming it into useful business intelligence.

  • By appling linguistic and statistical algorithms to text, we are able to analyze unstructured text and transform it into useful business intelligence. Text analytics processes can be performed manually, but the amount of text-based data available makes it increasingly important to use intelligent, automated solutions.

Predictive Analytics

Predicting future customer behavior by looking at past data and trends.

  • Through a process of applying math and statistics to data mining, predictive analytics
    allow businesses to predict future customer behavior by looking at past data and trends. Purchase history, customer service interactions, and demographics can predict customer churn, potential next purchases, and customer lifetime values. To do this, businesses must analyze data from all feedback channels, including surveys, social media, and more.

Sentiment Analysis

Determine if an expression is positive, negative, or neutral, and to what degree.

  • Through the examination of written or spoken language with a linguistic process that
    maximizes accuracy and eliminates ambiguity, we can determine if an expression is positive, negative, or neutral, and to what degree, and index the sentiment score with an 11-point scale. This provides greates accuracy over the standard positive, negative, or neutral ratings.

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