While common thinking suggests emerging technologies will follow a steady path to mainstream because they offer something better than the old, that road ahead is not always linear. In fact it’s often riddled with obstacles. For marketers and investors the key is to assess what will get adopted by a number of different cohorts and ‘stick’ in a reasonable period of time. The flip side of this coin is that there may also be brewing negative attitudes and experiences, pushing against adoption. Below are some assessments on today’s buzz technologies and how consumers and marketers are reacting to them.
Streaming adds to our choices… in a good way? New research commissioned by the ARF’s LA Council to Hub Entertainment Research shows that majority of consumers enjoy a broad range of TV content through both traditional and new channels (69%). However, a small but notable portion (12%) also point out that they are overwhelmed by the amount of programming and pathways to get to good content. While use is a good metric, the negative attitudes are also important to track: If consumer attention continues to get dispersed across channels, will TV/video content consumption see a decline?
AR/VR remains niche: WARC‘s global survey of marketers shows that some of the emerging technology fields such as AR/VR will continue to remain niche.
AI continues to be of interest: Artificial intelligence (AI) remains a big focus for brands as they battle to make sense of, and then apply, the many data sources at a marketer’s disposal.
Interest in wearables and blockchain decline: The same survey notes the wave of interest in wearables and facial recognition has declined. And just 13% expect to invest in blockchain in 2020.
Here’s a good and short list from TrendWatching on what to look out for in 2020. It’s particularly relevant for brand marketers and those in service industries. You may find that the headlines are not necessarily things you have not heard before, but the examples bring the call outs to life.
At the turn of every year, our inclination is to make a list of top trends to watch. Yet, there are some trends that are undercurrents and reveal over time. They are value-based shifts which yield cultural changes and affect business as we know it. No need to wait for December 2019 — earmark Gen Z values as signals of change.
Here’s an A.T. Kearney report noting that Gen Z is turning away from social media and in fact stepping into brick and mortar stores. According to this study, 81% of Gen Z prefers to shop in stores, and 73% like to discover new products in stores. A Gartner study provides further support suggesting that marketers look for Gen Z in second tier social media networks. They don’t like branded, crowded digital spaces.
Gen Z is picking up the baton from millennials and raising the bar. This is more than a preference for conscientious shopping from green brands. It’s a firm ‘no’ to pushy, canned marketing. Earning Gen Z’s trust and loyalty will take more than banner ads. Marketers will need to rely on the fundamentals: good product/service, positive experiences and a pledge to do the right thing.
The activist movement on climate change continues. Every day, I continue to read articles and posts about Greta and her piercing speeches. But I’d also like to point to a subtlety that’s making a difference here, at least in NY circles. This is the message parents with children in public schools received prior to the school strike. Department of Education, along with public schools, enabled parents and teachers who wanted to teach their children about advocacy. Not only you could be excused from school, but some schools even coordinated transportation and pick up. Yes, there is a lot to be said and admired about the power of ‘one’ in the protest events where Gen Z students walked out following Greta. But support from key institutions is what brings about trues change and catapults movements to new heights.
When discussing futurism with a colleague, he said he didn’t believe in predictions but relied on history. Fair. I also think we do not need to make lofty call outs to see how our future might shape but rather pay attention to the shifts happening now.
Demographic changes constitute a fundamental fray in the way populations will change their purchase , media and voting habits among others. With Gen Z emerging as the most diverse generation with pronounced socially-conscientious values, we will see a diversity in consumer choices as well. Expect a surge in new flavors from different cultures, blended products, willingness to pay a premium for the ‘right’ service (e.g., those who provide equal and fair pay to their employees) and green votes.
The packaged food brands are pedaling to respond to the ever growing self-care, healthy living and eco-consciousness trends by looking for plant-based ingredients and alternatives. Givaudan, a global taste and scent innovation company, partnered with University of Berkeley to develop a framework and evaluate the next set of proteins that are likely to be on shelves. The evaluation considers ingredients for commercial viability, supply, regulatory conditions as well as taste. Oats and mung beans have gotten the most ‘green lights’ out of the six that rose to the top of the evaluation. To read more about this research, click here.
Facebook has developed an algorithm that can work back from a food picture to ingredients. Then it delivers the gourmand photographer the recipe. This technology can elevate ethnographic/food/beverage research to new heights — as researchers gather photos across demographic groups and locations, they can see which ingredients are emerging and establishing themselves as crowd favorites.
One of the first things I remember studying in the US as an international student of sociology was the ‘Protestant Work Ethic.’ This was the work culture of the US, inherited from the Puritans — who associated hard work with redemption. Whether you’re Protestant or not, you emphasize work not time away from work read the subtext. Obviously there are variations to this tune depending on generation, geography, upbringing as well as the office culture among other factors. Nonetheless, I was not surprised to read that more than half of American American workers do not use all their paid vacation days (source: US Travel Association).
In a survey released in May by Discover and cited by the Wall Street Journal in June, 71% said they were planning a summer vacation this year, a notable increase from 58% last year. Now, what people say and do may vary. It will be interesting to look back and see how American workers used their time off in 2019. But if they do take their paid time off, this may signify boosts in
Building on what I had been pontificating and sharing on AI and autism-related research, I came across this break through from Princeton University. According to the report on the study, ” The method sorted among 120,000 mutations to find those that affect the behavior of genes in people with autism. Although the results do not reveal exact causes of cases of autism, they reveal thousands of possible contributors for researchers to study. ”
Here’s why and how AI saved thousands and thousands of dollars of research budget, not to mention precious time to arrive at robust findings:
“Prior to this computational achievement, the conventional way to glean such information would be painstaking laboratory experiments on each sequence and each possible mutation in that sequence. This number of possible functions and mutations is too big to contemplate — an experimental approach would require testing each mutation against more than 2,000 types of protein interactions and repeating those experiments over and over across tissues and cell types, amounting to hundreds of millions of experiments. Other research groups have sought to accelerate this discovery by applying machine learning to targeted sections of DNA, but had not achieved the ability to look at each DNA unit and each possible mutation and the effects on each of more than 2,000 regulatory interactions across the whole genome.
“What our paper really allows you to do is take all those possibilities and rank them,” said Park. “That prioritization itself is very useful, because now you can also go ahead and do the experiments in just the highest priority cases.”
Lastly, the system calibrates its predictions based on known disease-causing mutations and develops a “disease impact score,” an assessment of how likely a given mutation is to have an effect on disease.”
The sample of families who participated in the study was under n=1,800. It’s not too large, but strong enough for analytics. It goes to show us the efficacy of the method as well. The announcement also notes that the same method could be applied to cancer research and heart disease as well. This is an incredible step forward for humanity.