4 Steps to Calculating the ROI on Customer Experience Intelligence

Harvard Business Review estimates it costs up to 25 times more to acquire a new customer than to keep an existing one. And NewVoiceMedia approximates that poor customer service costs U.S. companies $41 billion every year. That’s why “customer experience” (CX) has never been more of a focus than it is right now.


But for most companies, achieving intelligence into true CX is easier said than done. Yet it’s imperative— the ROI is undeniable. By harnessing the power of data, you can translate the voice of your customers into CX business intelligence (BI) that sets you apart from every other organization. In this article, we share four key steps for building and executing an effective CX ROI strategy, and explore the sometimes-obscure value proposition of CX intelligence.
The average organization analyzes just 2% of all customer interactions


But for most companies, achieving intelligence into true CX is easier said than done. Yet it’s imperative—

the ROI is undeniable. By harnessing the power of data, you can translate the voice of your customers into CX business intelligence (BI) that sets you apart from every other organization. In this article, we share four key steps for building and executing an effective CX ROI strategy, and explore the sometimes-obscure value proposition of CX intelligence.


STEP 1: START DISCUSSING THE VALUE OF CUSTOMER TOUCHPOINTS.


First, ask your quality team for the Quality Index Score (QIS). Don’t worry if eyes glaze over—most people don’t think in terms of QIS. Then ask how many customer interactions the organization has each day and make sure they consider all touchpoints (e.g. inbound/outbound calls, chats, emails, snail mail, social media, IVR self-service, etc.). Once you’re armed with this number, ask how many quality touches are made on these customer touchpoints. I typically hear about quality touches from quality assurance, compliance, and audit checks, which I refer to as “checkmark mentality.” Few—if any—of these efforts really impact the customer experience, but it’s a way to gut-check employee work.

Now, back to the numbers and a simple math exercise.


Take the quality touches number and divide it by the first number—the total interactions per day—to get your index score, which can be converted into a percentage. So what does this index score tell you? The average organization analyzes just two percent of its customer interactions, so if your organization scores less than two percent, it’s scoring below average. ie 160.000 / 90,000 = 0.0018.


2%

The average organization analyzes just 2% of all customer interactions – mostly for random assurance checks and reactive investigations.

98%

The rest of this invaluable intelligence sits on the 98% shelf – not working for the organization.

Use this data point to start the discussion on building BI around customer touchpoints within your organization. And be sure to include your C-Suite in every discussion!


STEP 2: DOCUMENT YOUR CX GOALS AND OBJECTIVES.


First, you need to help align your executive team’s vision around the customer experience while considering your customers’ expectations. Starting the discussion on building BI around customer touchpoints begins with planning, and planning begins by documenting baseline measurements for the customer experience. Even if your baseline data is skewed by low volume survey results and/or low QIS, capture it anyway— you can use it as a starting point until you have more accurate data. Then work with your executive team to understand and whiteboard the organization’s high-level goals—both short- and long-term—and build a cross-functional team to identify the top five high-level customer experience objectives that align with each goal. Now for the tough part: solicit input on your objectives from a handful of customers representing different personas and vertical industries. And, since customer expectations often do not align with existing or planned goals and objectives, their feedback may need to be reviewed by your executive team. Conflicting goals usually do arise, at which point it’s helpful to identify and define the relationship between them—i.e., cause and effect. I recommend Ishikawa diagramming, which is a simple way to visually explore all of the potential factors that may be causing or contributing to poor customer experiences.



CX Live Calabrio
4 Steps to Calculating the ROI on Customer Experience Intelligence

Examples of mismatched executive goals and customer expectations.


Executive Team: Ensure first interaction resolution with the customer…always with a hidden context of “within our published average handle time (AHT)” for that interaction type.


Customer: I don’t care how long I interact with an employee, I want to ensure that I have the right answer before I finish. Anything less than that can break down my relationship with you.


Executive Team: Monthly goal and KPI is to upsell “x” on 20% of all interactions with a customer. Ask open-ended questions to ensure an upsell and meeting your personal KPI goals.


Customer: Do not try to sell me anything until I am 100% happy my issues are resolved. I need to know you are knowledgeable and have given me accurate information before I will purchase.


DON’T FORGET ABOUT ANALYTICS TECHNOLOGY


The single most significant software development in this decade unquestionably is sophisticated analytics. For enterprises—and, in our case, contact centers—you most often hear about use cases involving speech analytics. But don’t be fooled—today’s analytics is so much more than that: desktop, text, sentiment and speech. So to substantially impact customer experience and differentiate your service delivery model, it’s important to consider which type of reporting and analytics technology will be needed to meet your new goals. And there are some must-haves. For instance, you want reporting and analytics that:


• Capture and measure the right data needed to track performance against your goals and objectives

• Can be personalized to your organization’s unique needs

• Deliver dashboards that are: a blend of performance management (and drillable to coaching moments), process improvement and customer experience, so you can easily balance between efficiency and effectiveness measures; and also intuitive and drillable, so users can quickly reach the root cause(s) of performance, process or customer experience issues

• Let users visualize and customize “actionable” dashboards based upon each unique role in the organization, so anyone can easily understand how and when to take appropriate action

• And has an artificial intelligence (AI)-powered and machine learning framework that drives predictive, embedded analytics throughout the entire platform. There’s no cookie-cutter recommendation on software to support your unique needs, so be sure to work with a vendor that will help you take your CX strategy, decisive data needs and goals to the next level. In addition, pick a software vendor that has analytics and BI woven into its entire platform (so you can easily add the modules you need without increasing your software costs); has embedded analytics and business-driven visual discovery into everyday customer experience tools; and allows all business users to intuitively consume and act upon data with less effort and higher precision.


From the Trenches: Top 3 Challenges in Strategy Execution


1. Over-promising on the return (ROI) with scattered themes. I typically reference this as a “scattershot ROI with minimal qualitative and quantitative data” that lacks focus on specific goals and/or an accurate estimate of ROI that aligns with the strategy. Do this just once, and the credibility you lose very well might hinder any future budget requests.


2. Trying to collect too much data to launch your project and/or support your budget request. These projects never get off the ground due to the analysis paralysis and procrastination caused by insufficient preparation and disorganization of the data needed to meet the goals.


3. Insufficient understanding of customer needs mapped against internal biases. Without enough upfront planning and communication of the documented current state, projects are strategized and executed without a true understanding of the existing customer experience.


STEP 3: ASK, “HOW HARD IS IT TO DO BUSINESS WITH US?”


Now that we’ve discussed how much value your organization puts into customer touchpoints and the value of capturing baseline data to support goals and objectives, let’s take a look at how easy—or how hard—it is to do business with you. When looking through this perspective, you’ll probably have an “ah-ha” moment when you realize all of the areas where you can positively impact the customer’s experience within your organization—the same areas, I believe, where you also can reduce costs. So where do you start? I suggest you build a key indicator that consists of 5-6 metrics that can measure on a basic level how easy it is to do business with you.


First identify some of the key outcomes from your conversations and findings from the first two steps above that can be tracked and measured—that’s your basic starting point. A few tips


  • If you want to translate the voice of your customers into actionable BI that will transform your company into one that’s easy to do business with, you must ensure you have the right data—specific customer data. Even if your organization is a pro at collecting a lot of data, the guidance here is collecting the right data to make intelligent business decisions—quickly and easily—and knowing where to focus in order to positively impact the suggested key indicator. And you’ll need much more than transactional data— you’ll need access to and the ability to understand and act upon unstructured data as well.


  • One metric you’ll definitely want to track is how quickly your agents resolve customer issues since repeat interactions severely and negatively impact a customer’s experience with your organization while exponentially adding costs to the business. And—because customers connect with you in so many more ways than just through a call—I suggest you measure “first interaction resolution (FIR)” instead of “first call resolution (FCR).” Then build a balanced dashboard, so you can easily visualize and take action when your organization is at risk of missing or negatively impacting FIR goals, so you are continuously working to positively impact the customer experience.


  • Start small to ensure you achieve the goals you set and to ensure you simply get started. Once you take the first step, the other steps will follow more naturally.

STEP 4 Translate the Voice of Your Customer (VoC) into Business Intelligence


Now it’s time to deliver those measurable benefits by transforming the way you work and illuminating compelling insights about your customers. You might think I’m going to disclose some special formula or secret sauce on how to do so, but it isn’t rocket science. You can easily make this type of transformation! First, take a few moments to articulate and write down any quantifiable changes made in your organization in the past 12 months that positively impacted the customer experience. Need a jumpstart? Here are a few basic, real-life examples that highlight in red the specific analytics struggle faced by contact center leaders, as well as the path we suggest they instead take.


Example 1 Outcome/Struggle:


After four weeks of analysis, leaders asked the analysts to investigate one additional dimension of data that may have had an impact, forcing the study to be restarted with an expanded scope and adding human capital costs to the original project cost estimate. Suggested Path: For many companies, simply taking the time to calculate all of the ancillary requests required to complete all small and large research initiatives will expose significant ROI possible with an automated analytics approach. In this instance, we suggested the company automate VoC for every interaction in order to study shipping issues (eliminating the need start from scratch if or when requirements change); expand the study with opinion mining machine learning (sentiment) for polarity classification; and augment current work with additional needs in order to quickly analyze the additional scope.