Since the early 20th century, companies have used market research to align products with customer needs, believing that deeper insight into consumer behavior would lead to better design, smarter marketing, and ultimately, stronger sales.
Over the years, a wide range of tools emerged to achieve this. Surveys, statistical analysis, market segmentation, PEST and SWOT frameworks were all aimed at decoding customer preferences and preempting competition. These tools created a sense of scientific certainty about what consumers wanted. However, this approach led businesses to draw up a map before properly understanding the terrain.
Traditional market research methods such as focus groups only reveal a thin slice of reality, stuck in time. With the wealth of data now available through digital platforms, businesses need to pivot to more intelligent strategies.
Market Research Stifles Innovation
In the late 1990s, Jonathan Rosenberg was the head of the product team at a company called Excite@Home. The company had developed a breakthrough product, turning the coaxial cables carrying TV Shows into people’s living rooms into broadband pipelines, but soon ran headfirst into an intractable enemy: market research.
Cable operators had data showing that their customers mostly had Personal Computers (PCs) with Intel processors that were incompatible with Excite@Home’s cable modem. What the research failed to recognise was that PC performance was following Moore’s Law, doubling roughly every 2 years. This indicated that slow PCs would soon disappear and that developing a product restricted to this outdated tech would render it redundant.
The market research pushed Excite@Home to the brink of offering a fairly useless service on the backs of outdated PCs. Additionally, market research claimed that the most important aspect for potential customers was speed. However, what proved to be most exciting for customers once they purchased the product was its ‘always on’ quality – no waiting for the dialing and hissing of modems and servers as they established a choppy connection with the web.
Traditional market research highlights current needs and desires. This stands the risk of calcifying thinking, forcing product to align with current trends rather than coming to the market with breakthroughs.
Giving Customers What They Don’t Know They Want
Eric Schmidt in How Google Works maintains that “Giving the customer what he wants is less important than giving him what he doesn’t yet know he wants”. The Excite@Home story is a cautionary tale. Market research is not inherently flawed, but it becomes dangerous when it calcifies thinking. At its core is the recognition that understanding your customer is essential, but static segmentation, and assumptions about your customers’ needs and desires risk holding you back.
Getting to Know Your Customers, Intelligently
In the digital era, customers leave behind a wealth of data that indicate their preferences, their current context and their spending behavior. Harvested in the right way, this data creates a unique signature of an individual customer, allowing you to see beyond static data and instead see your customers as the products of their actions. ecosystem.Ai Modules such as Spend Personality have been created with the sole purpose of enabling segment-of-one personalization, modeling individual personalities on behavioral data that change dynamically as customers evolve.
“Giving the customer what he wants is less important than giving him what he doesn’t yet know he wants” ~ Eric Schmidt, How Google Works
Traditional market research facilitates broad-sweep segmentation rather than segment-of-one personalization.
Another key aspect of finding the individual behind the data is keeping up with change over time. Even if you acquire a full picture of your customers’ context and behavioral data, human beings inevitably change from moment to moment. Without the tools to connect with your customer at exactly the right moment, your marketing strategies lose relevance, especially in environments with high volatility.
Modules like Intelligent Sales address this problem with ecosystem.Ai’s real-time capabilities, allowing dynamic in-the-moment model-training, with algorithms set to converge on your customers.
Traditional market research risks setting limits on product development, and narrowing the scope of marketing strategies by making assumptions that human beings remain static. This overlooks the reality that human beings crave novelty, and often don’t realise they want something until it reveals itself to them. ecosystem.Ai’s behavioral and real-time capabilities opens a new world of possibilities for companies to innovate based on the dynamism of human beings and not on guess-work and assumptions.
