customer data [non]sense
Customer data and data quality in general confuse 84% of CEOs, according to KPMG. A story about our Chairman, Dr. Linden Brown, is the perfect gambit for this blog post.
When he studied marketing as a young man, he had to do quantitative research for Coca-Cola. And he found, as you all would suspect, a strong correlation between ad spend and sales. Spend more money on ads, and sales go up. Spend less, and sales go down. Then, his tutor asked him to look at the correlation between temperature and sales. And that is when he learned about the intervening variable. When temperatures went up, sales followed, and that triggered more advertising.
That is quite a reversal. Movie theater operators, for instance, know intervening variables well; they established a long time ago that rainy summer days bring in more moviegoers. Now we can start to study the correlations between COVID-19 measures and customer behavior.
Let me take you on a short trip through the sense and nonsense of customer data. As marketers and entrepreneurs, you can probably cite various examples of strong correlations that are, well, hilarious.
Like this one, albeit a morbid example: there is a near-perfect positive correlation between the United States’ spending on science, space, technology, and suicides by hanging. The question the morbid comedian asks is, of course, who hangs him or herself? The one who gets the funding, or the one who doesn’t?
Yet, as of 2007, there might be the onset of a trend reversal. Does 2007 mark the point in time when rope supply in the US became more scarce? Or did the suicidal start killing themselves by other means?
This example is what our Spanish-speaking fellow humans call ‘caca de toro.’ Yet, the questions that sit at the core of customer data collection are:
- why did an individual do that, and;
- why would she or he do this or nothing instead?
And that is why I brought up the story about intervening variables at the start.
Generic Demographics Won't Cut It
Person A, 35, female, living in Boulder, Colorado, who has a Master of Arts degree from Penn State in political science, will buy a Louis Vuitton handbag. I think you all will agree that these data and the purchase assumption tell very little.
We now know that generic demographic data alone does not explain what makes a customer unique. Age, gender, and location tell us little if we are selling, for instance, vegan drinks. No, we want to know who the individuals are who pursue a vegan lifestyle and why. I know engaged vegans who are sixteen-year-old females and males of sixty-six years of age. Yet, they demonstrate similar behavior regarding eating and clothing habits and exhibit different behavior when it comes to fun.
The lazy route to categorizing this data is by assigning tags in your CRM. By lazy, I mean thinking that tagging suffices. It does not. Perhaps we should clearly define what customer data are first:
- It is the customer information you can collect in the first-party context, and for which you received the explicit consent of your customer to assemble it.
The first-party data context includes all situations where your customers share their information directly with you, be it on your website, in your app, your store, your contact center, during face-to-face interactions, etcetera.
Customer Data is Multilayered
At the lowest level, we find the basal data; the demographics, or firmographics. The layer above holds the interactional or engagement data; how many page views does our site have, what is our click-through rate, how many white paper downloads this week? The third level deals with the transactional data; who buys what, how much, how frequent? Or is everybody ignorantly happy when sales go up, no matter from where they come? The fourth level is home to the behavioral data; how do customers experience your products or services?
The fifth level houses the attitudinal data; how do your customers feel about your company and what you deliver. Then we cleanse, harmonize, and integrate those five data levels in a Customer Data Platform or CDP, and we think we got it. We might even add some artificial intelligence to tell us when the persona D will place her next order. Well, let me give all of you a reality check: what you have at that point is your entry ticket, your table stakes.
The paradox of customer data is that it is a never-ending story with an expiration date. I will make that paradox clear in the next minutes. But let me first read aloud the latest marketing definition as agreed upon by the American Marketing Association in 2017.
The questions I now have for you are the following: How many are involved in creating, delivering, and exchanging offerings that have:
- Value for customers or clients?
- Value for partners and suppliers?
- Value for society at large?
Who noticed that I purposefully left out one of the four verbs in the definition; to communicate?
Now I can ask you how many of you are predominantly or even exclusively involved with communicating value propositions to your customers or clients? How many of you speak about the value they offer to society? Who decides if the value you offer is indeed value? And how do you define value? If you are solely preoccupied with marketing communications, how do you know there is any value in what you promise?
From a customer’s perspective, value equals the benefits received minus the money, time, and efforts paid.
Value = perceived Benefits Received - (fiat money + alternative currency + time + effort)
The challenge is that value is unique for each customer. And, the sobering reality is that your opinion of value does not matter. Neither does mine. A recent study among five thousand customer experience practitioners in twelve countries across seven industries reveals that:
- Businesses are four times more likely than their customers to rate an experience as “excellent.”
- They score themselves higher in Net Promotor Score or NPS than customers in every channel.
- Ninety percent say that their company provides a better customer experience than their competitors.
These beliefs even remain consistent when there is overwhelming evidence of the contrary. Given these facts, my question now is: why on earth should you spent money and time collecting customer data?
Of course, dear reader, you, you do not fool yourself. Yet, the question of why to collect customer data remains pertinent. There are three possible answers. The first is, I have no clue. In that case, I recommend educating yourself first. The second is; for ourselves so that we can sell more. In this case, I urge you to self-examining your mindset. The third is; for our current and future customers, so we learn what they value and for what they will exchange it. Two answers are nonsense; the only explanation that makes sense is the third;
- We collect customer data for current and future customers: it is the only way to build a sustainable business.
Why dare I posit that? Because I am a firm believer in the following three statements, sprung from the mind of one man, the late Peter Drucker. I have put them in a deductive order for you.
- “An enterprise’s purpose begins on the outside with the customer… it is the customer who determines what a business is, what it produces, and whether it will prosper.”
- “Because its purpose is to create a customer, the business enterprise has two – and only these two — basic functions: marketing and innovation. Marketing and innovation produce results; all the rest are ‘costs.'”
- “The aim of marketing is to know and understand the customer so well the product or service fits her or him and sells itself.”
You can deduct a statement about innovation, the second primary function, yourself now. I encourage you to please do so and to share it. Imagine I would select the best statement and reward that person with a small gift. But for the winner’s present to arrive at the address she or he wants me to send it to, I will need some of her of his customer data.
That need provides me with a perfect hook to get back to the customer data paradox, so let us return to it. For those who already forgot, customer data is a never-ending story with an expiration date.
Let me first explain the never-ending story part. Customers evolve, and the data within the various layers increase incessantly. Why is there an expiration date? Let me illustrate this by referring back to the research I mentioned earlier:
- Fifty-eight percent of the surveyed believe that their CX (which they seriously overestimated) will be outdated in just two years.
Plus, there occurs a natural degradation of customer data: an accepted cross-industry average is that email marketers lose twenty and a half percent of their lists annually. In short, the commoditization of our value offering plus the degradation of customer data makes it a never-ending story with an expiration date.
Now you might wonder, I thought this guy would tell me a thing or two about marketing technology. I am a technology enthusiast who has learned that, although it is mighty, technology is not the be-all and end-all solution. Can we do without technology? No. In 2021, 3.8 billion people will have a smartphone. Should it be our number one priority? No.
What Then Is The Number One Priority?
The number one priority is to: a, come to the realization and the firm belief that you must be an environmentally and socially responsible marketing and innovation company in the service of customers, and, b, act upon that belief. Every single company should be able to say: “We are a marketing and innovation company catering to the needs of X, with X being the customers who define us as a specialist in our category.” When they define you, not as a specialist but as the specialist, you temporarily made it.
The number two priority is to make sure you are ‘organizationally ready’ to create, communicate, deliver, and exchange your value offering. Do you have the organizational culture, the core competencies, and the leadership for it?
The third is to make use of technology to help you excel in the previous two.
At every step in your journey, you can ask yourself a crucial question: where do I stand in relation to whoever and whatever contribute to me reaching my goals? Based on the most rigorous research on relationship cognition ever, a feat by Dr. Olaf Hermans, we can introduce the sixth level of customer data: the positional data layer. And by doing so, we enrich the Voice of the Customer with the Mind of the Customer.
The visual you see above depicts all of what I have said so far. You see three spheres represented in a two-dimensional world. The first is the customer behavior sphere. It contains the energy generated by everything the customer puts into action to achieve her life and work goals. The second sphere visualizes the organizational readiness or expressed simpler, the extent to which a business or organization is ready to contribute to achieving the customers’ goals. Setting out to achieve such readiness also generates energy. The third sphere depicts exponential technologies, and it empowers the two other spheres. The third sphere’s power is potent, and it can drive the two others away from each other. The energy generated by the overlap and often conflicting interests of the spheres is compelling.
It took the smartphone 16 years to reach one billion users and four more years to reach two billion. At the same time, the device empowered companies like Apple, Uber, and Airbnb. Simultaneously, it gave customers a power they never had before, and they use it, often to the detriment of organizations.
Vodafone Germany, in collaboration with data science firm Gemseek, developed the predictive NPS. It is about being so smart that they know the customer who will run into an experience-degrading event, having the capability to solve the issue before it impacts the customer, and then communicating the proactive action taken to the customer.
The question of where one stands concerning someone or something else is hyper-relevant. Where does the customer behavior sphere stand regarding the organizational readiness sphere? On a more personal level, where do you stand, while reading this article, concerning me? Do we have a future together? A fate that can be limited to one next step or a series of steps that grows into a professional relationship that lasts for years?
Goodwill = X*Z*Y
Positional data provides insight into the three-dimensional goodwill position, expressed as:
- X, or your business and its agents;
- Y, or your challenges (operational, innovation), and;
- Z, or how the customer positively contributes to your operations, your commercial success, your strategy (by providing ideas for innovation), and your brand equity or your capacity to differentiate yourself from your competitors.
Positional data might sound complicated, but the crux is that ‘inversed empathy’ or the empathy the customer has for you leads to the former’s behavioral contribution. It activates her to be involved and contribute to your goals.
Isn’t that amazing, knowing that you can depend on your customers, helping you through inversed empathy. Let us connect this aha moment to collecting customer data. Customer goodwill helps, and you rely on your customers’ goodwill to trade, yes, trade, and not share their personal data to achieve an outcome that benefits both. I said trade personal information because a survey of forty-seven thousand banking and insurance customers reveals that eighty-one percent is willing to provide more personal information to a bank if it makes loan approvals faster and easier.
Whether all I told is nonsense or not is up to you. All I know is that goodwill can lead to more people voluntarily taking the next step together in the direction you want. One in five Europeans is quite willing to share personal information regarding getting personalized e-commerce offerings. Very few are willing to share it with social media platforms because they lost the customers’ trust. What is not nonsense is that goodwill is a two-way street.
Stating that technology will solve your marketing challenges is nonsense. Will it help you if you took care of mindset, culture, and competencies? Absolutely, in such circumstances, it is a vital enabler for your competitive advantage.
© Jef Teugels, 2020-2021. Edited by Olaf Hermans, Ph.D. Relational Engineering.