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Quantifying customer experience programs into dollars and sense (or how I got my honorary finance degree)

I’ve known Nancy Porte for a long time. Probably about seven to eight years. Aside from her genuine niceness, she is one of those people who have the experience and insight to actually teach a teacher. Nancy is the VP of Global Customer Experience at Verint, a company that is focused on CX as its raison d’etre. And she’s really, really good at her job. But she is also really good at thinking through CX-related concepts and values. So, I’d pay attention to what she is saying here. There aren’t too many left-brained applications of right-brained concepts out there. But think about it: Both make it whole-brained. (Here is a link to Verint’s CX video that has Nancy in some clips)
Your stage, Nancy.
We’ve all heard it before: It costs less to keep a customer than to obtain a new customer. Rather than add new logos, companies now understand the value of providing a positive customer experience to grow revenues from their existing customer base. After all, growth is hard to come by when you have dissatisfied customers leaving the stable.
Enterprise customer experience (CX) initiatives, designed to boost customer satisfaction and loyalty, have become part of the corporate landscape. In general, organizations know these initiatives are worthwhile — but to what extent? And what specific actions move the mark?
Business leaders who approve business plans – and funding – are focused on supporting overarching organizational goals of cost containment and revenue growth. Customer experience initiatives aren’t immune to the need for business justification. As we move toward the emergence of data-driven predictive models, we need to understand, what is the financial upside of a happy customer? And what are the specific dials to turn to get existing customers to buy more from your company?
CX professionals must become more effective at building and selling a CX business case. And as it turns out, this applied first and foremost to me. I can journey map my little heart out, but when it came to developing a financial model to determine the return on investment of customer experience, I was a fish out of financial water.
DEVELOPING A CUSTOMER EXPERIENCE MODEL THAT GOES THE DISTANCE
Developing a CX business case requires a “crossing of the chasm” to bring in data outside of customer satisfaction data. Ideal additive data sources are financial and operational data. Operational data can include how customers are using your products and services or engaging with your company – this can indicate which interactions produce greater satisfaction. Financial data can help establish a correlation between those interactions and the amount of money they spend over time. Typically, it makes sense to start by correlating financial data and then move on to see what behavior leads to greater satisfaction. To do this, CX professionals need to establish a strategic partnership with the finance department. CX people are good with customer data, but they need to know how to ask for the right information to support a valid conclusion that triangulates on business impact.
Enter the finance team – the group with the credibility and the experience in developing financial models combining key accounting, finance, and business metrics to model the company’s current and future financial performance. If CX people are from Mars, finance people are from Venus. Each group brings a different perspective and discipline to the table. CX professionals know what interactions are most memorable and significant in the customer journey. But do satisfied customers buy more and does this actually add dollars to the balance sheet? This requires a merging of customer journey mapping insights and customer satisfaction and spending data. Finance has the data and acumen to show the business value of a CX program in dollars and cents – to help formulate a CX business justification that goes well beyond philosophical arguments.
A first step in developing a CX business model is to acquire the right data. Most customer experience professionals don’t have access to the systems of customer spend (most often these are Enterprise Resource Planning systems). So, to acquire this information, reference our earlier point about partnering with the finance team.
But wait, there’s more! The finance team also can assist with recommendations on what data will provide an optimal modelling outcome. Qualifying and quantifying spend is challenging due to many factors; these include revenue recognition or accounting rules, legacy products, consulting engagements, etc., and then there is the issue of taking into account revenue from multiple geographies and currencies. The finance team is used to navigating these challenges and providing data that can complement customer satisfaction data. For example, it may be tempting to simply look at closed opportunities in your sales pipeline when it comes to customer spend. However, there are anomalies such as multi-year contracts, credits, or cancellations that will give you erroneous results.
From there, finance can assist with helping construct a model and testing the theses to ensure the model is valid and identify any “holes” in the model. An additional benefit to asking your finance team for assistance in developing the model is credibility. Financial models are part of their everyday existence and when you present the results to your executive team, having the “seal of approval” from the experts goes a long way towards acceptance of your conclusions.
WHAT THE COURSERA COURSE DOESN’T TEACH YOU
In my infinite wisdom, I tried to go down my own path to gain the necessary financial acumen to support this CX modelling project. I think it maybe got me a GED in finance. That’s when I knew I needed to be mentored by someone steeped in the craft, who could teach me more.
In my CX modelling odyssey, I am beholden to my finance colleague Kim Enders; we’ve worked together for over a decade, so I knew she was the perfect person to school me to attain my honorary finance degree. If I could sum up what I learned through this experience, I would boil it down to the following three things.
Getting Real About “Rev Rec”: Have you ever heard of term? I hadn’t either, but this is what all the cool kids in finance talk about; it’s slang for revenue recognition. It’s also really important to understand as revenue, realized revenue, customer spend, and GAAP revenue are all different things, and if you choose the wrong one to base your model on, it can totally invalidate what you’re doing.
I learned that while rev rec is technically GAAP for all companies, GAAP is not applied consistently (it’s a “gray area,” which (surprisingly) there are many in accounting), and also the method of delivery of the product/service (perpetual license/maintenance versus Software-as-a-Service, etc.) affects when revenue is recognized. As it turns out, many non-public companies don’t have a good handle on GAAP revenue recognition, the concept of which has changed a great deal over the past several years and is very complex. Net-net (to use more finance “slanguage,”) annual spending (cash basis) or new/additional spending, or something along these lines is a better indicator of customers that are happy. Revenue recognition can go on for years if a customer is locked into a contract, whether they are happy about it or not.
Approximate is OK, and Actually More Valid: I learned that while accounting is more of a science with rules and required reporting formats, finance and modeling are more of an art form. Kim explained to me that when you look at financial models and reports, they tend to be somewhat generalized — even budgets and forecasts are usually rounded to the closest thousand, or something along these lines, as they function as a best estimate or guideline.
So while I thought the goal was to land on an exact dollar amount of increased revenue that could be correlated to increasing customer sat by X percent, my finance mentor informed me that one number could never be right because my company doesn’t sell one thing — we sell many things with many different pricing margins and models. Furthermore, no one would expect you to know exactly, to the dollar or thousands of dollars, how much money any given customer would increase spend if satisfied. What’s more, said Kim, if I did present an exact number, no one would believe it!
Instead, Kim told me the goal was to develop a good working financial model, with solid inputs and valid assumptions. This would enable me to say that with the data I had, we could expect an increase of approximately X dollars, or even a range of X to Y dollars. This principle reminds me of another mentor-mentee “teachable moment”. As the karate master in the movie Karate Kid told his young student Daniel-san – “You trust the quality of what you know, not quantity.”
Modelling is a Time-Honored Process: Validating the model is important. If you are going to demonstrate customer experience initiatives will contribute something in the range of $40 million in revenue, you want to ensure the model is conservative. Just as companies should be conservative in earnings estimates, the return on investment for CX investments should be conservative and attainable – it’s always good to under promise and over-deliver. 
Eventually, someone will look back at the model and expect you to give some reconciliation of how you did versus what you thought you’d do with given resources based on the model. I learned it is important to keep tracking the data after the initial model to improve inputs and assumptions, to “tweak” the model, or change it if necessary. The more data you have over time, the better the predictive nature of the model will be and therefore, the more credible.
TAKING A MATRIX APPROACH TO CX MODELLING
Organizations often tier their customers based on customer lifetime value or other factors. This provides the opportunity to factor this tiering into CX financial modelling.
It may be that satisfied customers spend 20 percent more on average, but are there other variables at play that may dictate why for some customers the same satisfaction levels may only translate into 10 percent more spend, while for others it could be 40 percent more? By establishing a predictive model from the operational and behavioral data, I believe organizations can continue to learn by experience to “solve for X” in this equation. And in this way, they can zero in on priority accounts and segment customers and CX efforts accordingly. As I look ahead to the future, this is how I envision “levelling up” the modelling we have in place today. Maybe this will be my finance grad school thesis project?
The ability to collaborate, quantify, and communicate the contributions of the customer experience function is vital to ongoing support and success. Understanding what a successful customer experience looks like to an existing customer is a great start, understanding what premium they will pay for that experience requires the infusion of finance into the art and science of customer experience to take it to a whole new level – one that C-level executives will understand and appreciate. Knowledge is power, as is collaboration across the enterprise aisle. If you think you’re a fish out of financial water, my advice is to find your Mr. Miyagi/Kim – a finance mentor who’ll hold your hand as you take the plunge and immerse yourself in the deep end – and rise to the surface with your honorary finance degree. 
Told ya! Thank you, Nancy.
 
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