Insights | Customer Experience

Customer Experience Analytics: 5 Steps to CX Value and ROI

By taking a holistic view of customer data, pinpointing areas of opportunity, and making specific, targeted recommendations, it's easy to prove the ROI of customer experience analytics.

Image of a woman giving a report on business metrics
Author: Jen Walsh



In the first of our series on Customer Experience Analytics, we shared that research shows the majority of companies, a full 90%, will use customer experience as a key differentiator. Diving deeper into that research, we know that when enacted strategically, Customer Experience (CX) creates brand trust, customer loyalty, and sustained company growth. It has been – and continues to be – the competitive differentiator.

Modern CX has evolved beyond reactive customer service and cost-center thinking. This new world of CX includes predictive analytics that deepen our understanding of data and drives targeted, specific offerings and experiences that customers find valuable.

CX analytics is the lynchpin between customer insight and company performance. With expert knowledge of customer sentiment, preference, and behaviors, RevGen Partners turns disparate customer data into cohesive, relevant, actionable, decision points to drive value for customers and brand trust, loyalty, and growth for companies. Our novel approach is grounded in the foundational relationship of CX investment and return on that investment.

We define CX Analytics as “The practice of turning customer feedback into novel insights about customer needs, sentiment, preferences, behaviors and trends that are used to inform decision-making and target specific actions that drive customers’ success and company performance.”

In this second of three CX Analytics article series, we dive deep into how the CX Analytics process actually works for clients and customers. We use a five-step process to outline RevGen’s practical and unique approach.


1. Customer Listening Posts

It all starts with your customer listening posts and understanding feedback they are providing. Listening posts provide direct customer data and can include the following areas, as well as many others.

  • Sentiment metrics including NPS, CSat, CES
  • Behavior metrics including customer retention, expansion (up and cross selling), and CLV
  • Social Media
  • Digital Ecosystems
  • Customer Journeys
  • Customer Focus Groups
  • Frontline employee feedback


2. Data Strategy

Though customer data is captured in step one, it’s not yet in an optimized state. That data is disconnected, disparate, and varied. When data is incomplete, it is difficult to identify trends, draw data-driven insights, or make nuanced decisions. In the data strategy step, we want to consolidate and consider the following aspects:

  • Discover and procure customer data sources
  • Integrate, centralize, and organize disparate data sources
  • Create data platforms to enable analytics
  • Develop reports, dashboards, and analytics models
  • Provide cross-enterprise access


3. Analytics

In this step, we learn and analyze the consolidated data to understand customer trends and highlight specific findings that are at the root of challenges and opportunities. The data mining in this step helps to discover new and nuanced understandings about customers.

  • Customer insights and intelligence
  • Preference analysis
  • Segmentation analysis
  • Preferred and customized experiences by segment
  • Targeted engagement opportunities
  • Predictive, prescriptive recommendations


4. Informed Action

Once we have learned precisely what’s driving customer problems or opportunities we can target and fix the right problems. This informed approach to investing in CX fosters confidence in spending on these initiatives by producing the outcomes we want and proving an ROI. This step also:

  • Pursues CX goals worth achieving
  • Closes highest value gaps
  • Addresses root causes and effects
  • Acts on targeted CX improvement areas
  • Confidently executes remediation and action plans
  • Acts on opportunity areas


5. Business Value

Finally, we are able to clearly see the business value from the investments made. This is where the “real” CX value is achieved and the ability to measure it, both quantitatively and qualitatively, becomes a reality. Examples include:

  • Improved NPS, CSat, CES scores
  • Increased retention (and associated revenues)
  • Higher upselling and cross-selling results
  • Longer customer lifetime value
  • Enabled customer re-engagement (link to that article)
  • Increased customer advocacy, references, and referrals
  • Deeper brand trust
  • Maximized CX return on investment


At RevGen, we believe there is a shortage of comprehensive, yet common sense,  approaches to the close alignment of Customer Experience and Data Science. To bridge this gap, we’re committed to finding the targeted actions that are driving business value for companies and clients. Join us in the new evolution of science backed customer experience! Contact us today to schedule a complimentary 30-minute consultation.


Jeniffer Walsh is the Director of Customer Experience at RevGen. She specializes in CX transformation, digital optimization, and Artificial Intelligence technologies for growth.

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