Every year, the world’s dictionaries publish new words. Last year alone, the Oxford Dictionary added over 1500 entries in its latest update. In the marketing world, the diffusion of neologisms is even more frenetic. Every year, dozens of new, bizarre words come to our ears. In this blog, we analyze three new buzzwords that reflect emerging marketing and social media dynamics: Gen Z, Gig Economy, and Small Data.
Yes, the term ‘Generation Y’ is already something from the past. We’re sorry to make you feel seasoned, but the good old Millennials are today men and women in their 30’s. Those who have been first described as digital natives could already have way-more-digital daughters and sons.
The term Gen Z (also known as Generation Z, iGen, Post-Millennials, Centennials, or Plurals) identifies people who were born between the second half of the 90’s till 2010. They represent 26% of the current world population.
According to an interesting Google report called – what a surprise – ‘Gen Z’, the members of this new generation are quite different from their predecessors. The biggest difference, from a technology perspective, is that they are not simply digital anymore: they are mobile first. This means that, for those who today are 7 to 23 years old, the smartphone is the first point of access to access the internet, not just to browse it or to chat with friends, but also to take all those actions that Millennials (and those before them) normally still relate to as “desktop experiences” – online shopping, or videogaming, for instance. To have a smartphone, according to the report, is a pivotal step in the lives of the “Z” kids. The equal of graduating or obtaining their drivers’ license.
The Gen Z people are the first generation of mobile shoppers, but there’s more. These youngsters watch videos online with a frequency never seen before: 7 out of 10 stated that they watch videos on the internet (mostly on social media) for more than 3 hours a day.
Characteristics that marketers need to carefully acknowledge, especially if one takes a second to realize that the purchasing power of the Gen Z is today 44 billion dollars globally – and it surely won’t decrease anytime soon.
‘Gig economy’ is a term that describes an increasingly common economical model, in which steady jobs (the so-called permanent positions) are becoming more and more rare. In fact, in this new scenario, a job is often requested and offered on-demand, meaning only when someone’s competence is actually needed.
The classic difference between employee and self-employed now falls short. In the gig economy, all workers are somehow freelancers, inasmuch they perform some kind of temporary working activity, such as a temporary or part-time job.
Another peculiarity of this model is the presence of digital intermediaries that act as the point of contact between offer and demand. Think of Airbnb for rooms, Upwork or Fiverr for websites (and more), Etsy for artisanal products, Derliveroo for food, or Uber for car rides. However, a typical gig economy job doesn’t necessarily have to be digital and be based on these hubs. On the contrary, very traditional types of jobs (e.g. a carpenter who fixes bicycles in their free time) could be considered a full-fledged worker of the gig economy.
So, while temporary jobs are not new per se, the extent in which they became the standard caused the term ‘gig economy’ to become a widely-used term to describe today’s economical system. In fact, it goes without saying that the number of independent workers is rising rapidly, with all the consequent ethical debate that follows. If utopians glorify the benefits of flexibility and variety that distinguish this way of working, distopians cannot but underline the critical issues in terms of rights for the workers, who are often left with no paid leave, medical insurance or competitive salaries.
In this time of “Big Data,” there’s those who rightfully underlined the importance of qualitative information over quantitative one. The term ‘small data’, in fact, was introduced in opposition to the general trend of basing business strategies on extensive numbers (the ‘big data’), with the goal of finding valuable correlations. Not that big data are valueless – on the contrary. The question, rather, is: is it enough?
Those who claim the importance of small data would answer “No.” Giving importance to small data means to carefully observe (small) details in consumers’ behavior that can be significant for business strategies – a marketing plan, for instance.
A valid example is the one by Martin Lindstrom in his book ‘Small Data’, in which he tells the story of his experience of brand consultant for LEGO. The small bricks company found itself in the middle of a severe crisis in early 2000. As a consequence, it was going to take a revolutionary choice: making its bricks bigger in order to simplify the product and making it more accessible to the wider consumer.
This choice was driven by insights related to big data. Lindstrom, surprising the company’s management, suggested a shift in the strategy. His approach was as simple as it was innovative. He interviewed an 11-year-old kid with the aim of understanding what he really liked about those colored plastic bricks. The answer was a revelation: what really excited the kid about the product was the satisfaction to have a tangible proof – a trophy that represented to him and others his ability in putting together a complex construction.
Thanks to this simple but crucial intuition based on observation (small data), the Danish company decided for a deep change of strategy, and actually decided to make their games richer and more complex instead. It was an extraordinary success, to the point that LEGO became the first toy company in the world.
In conclusion, the lesson here is the following: new digital tools provide marketers with extremely precious insights on a large scale. But not always this is sufficient. Complex variables, such as human emotions related to a product or service can’t always be reduced to numbers, and often intuitions that can be game-changing for your business are hidden in details that analytics software isn’t as yet able to detect. The only device that can do that, for now, is the human eye.
Find out here the marketing buzzword of October.