The term “big data” is used so often in research and marketing terms that you’d think it’s been around forever. But actually, big data originated from database marketing (read the first attempts of targeted direct mail) in the mid-late 1980s. This was the first attempt by marketing agencies and large companies to segment their customer databases to create different offers based on the demographics or psychographics of their customers. Today, you will hear from CMOs, CFOs, and even CEOs who say they won’t make a decision without using big data. And that can be a problem.
Very often there is so much data that marketers and others can be frozen in their decision making. Ultimately, marketers spend much of their time organizing and sorting the data rather than working with it, drawing the buyer’s picture and refining their efforts. It’s essentially a scaling issue. There is so much data, from so many sources, and much of it may be outdated or invalid that marketers often struggle to gain insights or gain anything meaningful. Too much reliance on big data showing history doesn’t necessarily indicate future trends or customer needs. Another problem could be an even bigger problem.
How many entrepreneurs and executives today have actually met their real customers in person in their environment? Why aren’t more companies using ethnographic research in their product development and marketing approach? If sales in a particular store have fallen because of the ‘sales numbers’, why have they fallen? If you’re not there to observe and talk to customers, you won’t be able to ‘see’ that the store displays are incomplete or that the training of sales associates has not been done effectively. Big data analytics won’t give you those insights. Perhaps by having a small data mindset you can gain more insights that are often invaluable and help you better meet your customers’ current and future needs.
If you really want to understand better customer insights beyond your big data, you need to actually observe and meet with your customers.
Better observe. Studying customers in their environment through observation labs or ethnographic studies is not new. But with the advent of big data and digital marketing, fewer and fewer entrepreneurs, marketers and senior executives are using these tools to actually meet and understand their customers. Big data really doesn’t give you the small insights that make a big difference.
See trends earlier. While collecting large amounts of data about your customers can bring some benefits, you rarely see trends in the historical data. So many companies collect as much data as possible, but spend little time on emerging trends. When you meet regularly with customers, you see the solutions and hear what they say about the competition. Also read more trend/industry reports and spend more time with trend forecasters and futurists who always know how to dot the i’s and cross the t’s.
Insights from competitors. When was the last time you really researched a competitor’s product or service offerings? It’s not about beating them, it’s about understanding the market and your customers better. Don’t bury your head in the sand and don’t let bravado get in the way of gathering more information that can help you understand an industry shift. Buy your competition.
Creative solutions. The analysis of big data can reveal potential insights that then require some action. But instead of pressing your face against the glass of big data, take a step back and observe the real opportunity or problem. You can’t come up with an important strategic creative solution until you really understand the problem.
Focus on the customer. How many entrepreneurs and business leaders say this: ‘Customers are our lifeblood and we do everything we can to serve them.’ How many of those same people regularly meet customers? When was the last time you sat or observed your client? Don’t expect a customer to tell you exactly what they want or need; they don’t always know. But customers vote with their wallets and while they may not always be right, they are never wrong.