Measurement Matters: From Brand Experience to Bottom Line
Connecting the dots between experience, behavior, and customer lifetime value
Do you make decisions based on fact or feeling?
If your choices are guided by “what feels right” you’re in good company. A growing body of research suggests that is how we’re wired: we analyze information to learn and understand, but we make many of our decisions based on emotion.
That’s why how we feel about our interactions with products and brands is so important. Our experience affects whether we make a repeat purchase, engage more deeply, or abandon a brand for one that better meets our needs.
Yet business leaders often fail to recognize the link between brand experience and financial performance. Believing that design and experience do not matter – or that customers won’t notice compromises – is a hidden trap.
Consumers do care.
And in this golden age of data and analytics, it surprises me that this relationship is not more widely appreciated. Organizations collectively spend billions of dollars building data warehouses to analyze sales, revenue, and profitability in nearly infinite ways – by neighborhood, product type, sales office, channel, pricing, and promotional activity. Sales reports that break down revenue by sales channel and ad campaign are common, but most of them come across as “flat,” as if the world is mechanized and output is simply the sum of tightly controlled inputs. But it’s not.
How might conversations change if we spent more time with reports that showed how revenue and profit changed based on the quality of customer experience?
Putting Consumers at the Center
When we put consumers at the center, it spawns inquiry that leads to insight:
Who is our customer? What do they need? What matters in their experience? What data is available? How much improvement is needed to make an impact, and knowing that, what would we prioritize? What value can we unlock if we do better?
Emphasis on better – not perfect.
When seeking answers, these discussions quickly turn to data and measurement. Measuring the relationship between brand experience and business outcomes requires data on a variety of topics including:
Your product(s)
Consumers who consider and use your product
Where, how, and in what way the product(s) are used
Consumer sentiment at points of interaction
Outcomes of these interactions, including sales, revenue, cost, and profit
You may also need data on contextual factors. For example:
Consumer preferences and how they change over time
The composition and behavior of segments and cohorts
Packaging, pricing, and promotions
Competitor moves and activity in the market
Factors like seasonality and economic conditions
If you’re not gathering this data, it’s not too late to start. Consult with your analytics, digital, and engineering teams and adopt an iterative and nimble approach, because you are likely to find surprises. It’s common to discover that one group defines the same metric differently than another group – like the meaning of “southern potato salad” or “premium economy seat” can mean vastly different things to different people. Just keep in mind that it is more important to get started than to get it perfect out of the gate.
How to Quantify Sentiment at a Point of Experience
Preference surveys, brand trackers, and satisfaction surveys provide insight at a high level, but to pinpoint specific experiences that both delight and disappoint, you’ll need data to identify a unique consumer who engages in a specific experience, when they do so, and the consumer’s sentiment about that experience. Many companies use Net Promoter Scores (NPS) and similar systems for this purpose.
There are several formulations of NPS – and transactional NPS (tNPS) can be especially useful. You know those “On a scale of 0-10, how likely are you to recommend…” emails that hit your inbox after making a purchase? They are designed to collect your feedback and calculate a tNPS score for that interaction.
When used widely and comprehensively, tNPS combined with customer demographics, behavioral observations, and transaction data can reveal a great deal about what’s working and what’s not in a brand experience.
Insights will abound from the moment you start to gather, review, and analyze this data. For example, you may reveal:
Cases where customers bounce from channel to channel in search of answers
Instances where your brand says one thing and then does something different
Long wait times and negative interactions with associates
Transactions handled well at one touchpoint but poorly at another
Apps and website functions that are slow to respond or crash
Onboarding and tech service visits that go awry
Connecting Experience to Behavior and KPIs
The real magic begins when you weave the data on interactions, sentiment, and customer behavior together – and tie it through to business KPIs. But which KPI provides the best measure of value?
I’m a big fan of Customer Lifetime Value (CLV). CLV is the cumulative revenue or profit you can expect from a customer over the lifetime of their relationship with your brand. I prefer using the profit formulation along with a second model to estimate the value of prospects, which is useful to prioritize marketing and outreach campaigns.
CLV changes as consumers change their behavior, and when those changes are correlated with sentiment and interaction data, it can reveal the impact of brand experiences in concrete financial terms:
“Comparable customers that had Experience A are worth more on a CLV basis than customers that had Experience B.” It makes apples-to-apples comparisons easy.
CLV also avoids the “black box problem” because it is constructed from metrics that the business already knows like revenue, expense, expected growth and tenure, and cost to serve. CLV can also be combined with customer demographics and sales history to determine how customer populations are changing, how they respond to different pricing and product mixes, and whether there are underlying behavioral differences in segments that affect the portfolio.
My favorite aspect of CLV is that it anchors strategy discussions with a long-term view of what delivers the most value for the business.
Yes, deep discounts may attract new customers and help hit the monthly acquisition goal, but if these new customers are less likely to stick around, it may be the wrong thing to do.
I’ve successfully used CLV in cases like this to clear away years of legend and anecdote with detailed observations of how customers behave and how that impacts the health of the business.
Examples in Practice
Below are several hypothetical examples to illustrate how experience linked to sentiment and CLV can be used to influence strategy:
Service and Reliability
Outages and a perceived lack of reliability can dramatically impact the CLV of service subscribers. For example, a single outage might lead to higher churn even if the duration of the outage is short. Repeated service interruptions may have compounding effects, as may the timing of outages if they occur around the same time as a bill cycle or rate increase.
Implication: Every service blip matters. Even just one and no matter when it occurs. With this knowledge, service providers can prioritize investments to improve reliability and assess the potential financial impact of outages when they occur.
Sales Funnels / Digital Buyflow
Perhaps you offer two buying experiences. Let’s say the first offers pre-built combos like a fast-food drive-thru: “I’ll take a number one, medium, with an orange drink.” The second offers a build-your-own “I’d like a footlong meatball on Italian herb with provolone, lettuce, mustard, and pickles” experience. These are vastly different experiences – and it’s possible that one delivers customers with a much higher CLV than the other.
Implication: If similar customers generate significantly different CLVs based on their acquisition path, it strongly suggests that the experience plays a role, or perhaps self-selection is at work. Delving deeper is certain to surface a variety of insights; with better knowledge, it may be possible to proactively identify customers who are likely to prefer one experience over another and guide them to a better outcome for them as well as CLV.
Feature Changes
Let’s say your preferred phone manufacturer launches a new model that touts a better camera and people are clamoring to buy it. Sales are way up and the future appears bright. But will the new camera result in higher customer CLV?
Implication: The answer depends on whether the benefit is transient or durable. To increase CLV, the camera must incent consumers to change their behavior in ways that generate sustained incremental margin, increase tenure, reduce acquisition and/or retention costs, or lower the cost to serve.
If consumers with the new phone take 3x more photos, tell everyone how much they love their new phone, and all those photos increase the average revenue per user (ARPU) for monthly cloud storage fees – then the new model is accretive to CLV. On the other hand, if after three months, the novelty wears off and consumers don’t maintain different patterns of behavior, then the impact is likely not durable and won’t improve the company’s fortunes over the long term.
By using data and analysis to connect the dots between interactions, sentiment, and business KPIs, we can find problems, prioritize improvements, and build better experiences that benefit consumers as well as the bottom line.
These are just a few examples of how to Do Good by Doing Better. Put consumers at the center, measure the impact of experiences on sentiment at each interaction, and connect the data to CLV to reveal your brand’s roadmap to stronger relationships with consumers. And with each step you take in that direction, you’ll up your impact, one act at a time.
Bonus Content
I’ve curated a short list of resources that you may find useful in your journey to better measure the value of brand experiences:
How to Measure Anything: Finding the Value of Intangibles in Business
by Douglas W. Hubbard
If you consider “you can’t measure that!” to be fighting words, then you need this book. Hubbard explores the many ways that a lack of measurement can be harmful to our lives and careers and the steps necessary to measure nearly anything.
https://amzn.to/3WUvzPN
Books and Resources on NPS and the Net Promoter System, including works by Fred Reichheld, the inventor of the Net Promoter Score:
https://amzn.to/3WUvzPN
The International Brand Valuation Manual: A complete overview and analysis of brand valuation techniques, methodologies and applications, 1st Edition
by Gabriela Salinas
Get ready to geek out on theory and stats! With 400+ pages filled with methodologies, formulas, figures and tables, author Gabi Salinas provides a comprehensive overview of the concepts of brand and brand valuation, and “how these relate to the associated concepts of corporate reputation, intellectual capital, and intangible assets.”
https://amzn.to/4568MCD
Fast and Slow
by Daniel Kahneman
The author, a world-famous psychologist and winner of the Nobel Prize in Economics, published this book when I was an adjunct professor at the University of Cincinnati’s Linder College of Business. Kahneman’s straight forward explanation of our two thinking systems – so-called “fast” and “slow” – was a major influence on how I introduced the art and science of design, perception, and communication with data visualization to my students. A must-read in my book.
https://amzn.to/3VzSQo8
Lovemarks
by Kevin Roberts (with foreword by A. G. Lafley)
If the language of “brand love” and “emotionally resonant brand experiences” seems foreign to you, consider this entertaining and eye-opening view on the future of brands and why it’s essential to put consumers at the center of everything. Yes, it was published in 2005 and some of the references and cited figures are dated. However, the fact that I keep a copy handy says something about how forward-thinking and relevant Roberts’ vision in the book was is, and it remains a constant reference for inspiration.
https://amzn.to/4eDkf0Q
These recommendations are unsolicited by the authors and publishers – I’ve used them myself or found them in the course of my own research and believe you may find them of value too. You can further support my work on Do Good by Doing Better™ by clicking through the included links, which generates a small commission for me when you make a purchase. Thank you.