It’s official: Marketers and technology are jilted lovers.
Gartner’s latest Marketing Technology Survey found that marketing leaders are only using 58% of their martech stack’s potential. And a new survey by Martech Today shows that 83% of the marketers surveyed upgraded or replaced at least one of their tools in the last year.
Why all the disappointment? I believe the inflated expectations, just like the heady days of a star-crossed love affair, can only lead to a crushing reality when your partner falls off their pedestal. Much of today’s technology seems to reliably not meet the high expectations set by many technology vendors and starry-eyed buyers.
I believe the reason this disappointment is so stark in the U.S. is, perhaps counterintuitively, due to the wealth of data we have available. A lot of the tech that American companies are heavily investing in works best when fed large amounts of data. But reliance on one thing can lead to neglect of other equally important things.
While the amount of data available for analysis is exploding across the world, in the U.S. — a mature market with a digital population generating immense data — companies have become addicted to “tool fuel,” as I call it. Tool fuel is numerical data whose worth is proportional to its quantity, such as the number of visits, sessions, hits, views, likes, shares, etc.
Rather than exploring and deeply understanding customers and their behavior, many companies look for shortcuts to customer insights based on volume-reliant data trends alone, where tools shine. Soon, the tool, not the company leadership and strategy, is setting the customer experience agenda.
Of course, quantitative data trends and machine learning insights are important to leverage, but customer-centricity also requires thick data for rich customer insights.
Tools alone won’t make your company more customer-centric.
Don’t get me wrong; tools and platforms are important components of customer experience optimization, but unless companies have a thriving customer-obsessed culture, where the tool serves a strategy (and not the other way around) wielded by an empowered team that is laser-focused on understanding and meeting their customers’ emotional and functional needs, then the technology investment is likely doomed to fail.
The international experimentation consultancy I cofounded validated this crucial point when we discovered that fast-growth companies tend to have a 36% higher experimentation program health score than slow-growth companies. The impact of testing is larger when comparing those companies that test and those that don’t. Gartner found that “organizations that significantly outperform their competitors are almost twice as likely to make testing and experimentation a marketing priority.”
It appears that these fast-growth companies are better at discovering, exploring and exploiting customer insights because of their customer-obsessed experimentation culture, not their tools.
A great experimentation strategy relies on multiple methods to surface customer insights.
Our research also showed that American companies are less likely than those in the U.K. and Germany to harness customer-centricity to power business growth. European companies, especially fast-growth companies in Germany, which scored 21% higher than American ones in customer-centricity, reported using multiple methods to understand the customer and their needs.
Less reliant on tool fuel, businesses in these markets are leveraging advances in behavioral design, which maps quantitative and qualitative customer data to optimize customer experiences. Research by Gallup tells us that companies that leverage behavioral insights outperform their competitors by 85% in sales growth and more than 25% in gross margin.
Meanwhile, according to our research, slow-growth companies reported a much higher reliance on a single method of customer understanding to set their innovation and experimentation agenda. They make decisions more often based on gut feeling over evidence and fail to use rich data to optimize the customer experience. They certainly don’t look at the human element that drives their customer’s behavior.
Instead, many of these companies exclusively rely on clickstream web analytics or another tool to “understand” their customer at an impersonal, quantitative level. Simply put, slow-growth companies are only looking at “what” customers are observed doing, while guessing about “why” their customers behave one way or another. And any strategy derived from that guesswork likely isn’t paying off.
Customer-centricity is a journey, not a destination.
At its best, quantitative technology tells us what happened (and predicts what might happen) with high confidence, but it can’t often tell us why it happened.
I believe companies need to combine knowledge of what customers behave the way they do with why they do it in order to truly be customer-centric. Companies that are driven by such insights are growing at an average rate of more than 30% per year, and they’re predicted to earn $1.8 trillion annually by 2021, according to a report by Forrester.
For nearly 20 years, I’ve set up countless digital experimentation programs for companies big and small, and here’s what I’ve learned: The best have the process, accountability structures, cultural buy-in, expertise and, yes, technology too to discover and validate customer insights faster than their competitors. Tools are one of the five factors that serve that purpose (the others being process, accountability, culture and expertise).
Successful programs share common characteristics that make them customer-centric.
Companies might start by gathering and examining quantitative data and looking for trends. Equipped with potential insights from the quantitative data, they use qualitative methods to hear the voice of their actual customers.
They have conversations with their customers; they don’t just tick boxes with the tool du jour. It’s in these conversations that insightful leaders ask why their customers feel and act the way they do. Backed by insight, employees across the organization hypothesize solutions to solve the challenges described by their customers.
These fast-growth companies use rigorous experimentation to validate whether the solutions helped their customers achieve their desired outcomes. Those that don’t aren’t regarded as failures but are tapped for further customer insight. “Winners” or “losers,” the process creates a feedback loop that propels customer-centricity forward.
Before you invest in your next technology love affair, first take a hard look at the process, accountabilities, culture and expertise that are needed for successful digital transformation and experimentation. With the right environment, you can make your next technology partner the one that lasts.
