How Would Silicon Valley Reinvent Market Research?
By Kristof De Wulf
The future has never been more fascinating. 10 years from now, we expect to be able to manipulate DNA the same way as a Word doc, to buy the power of a human brain for just $ 1,000 and to see a robot journalist win a Pulitzer. That’s why I was extremely excited to join a group of 20 fellow entrepreneurs on a 5-day trip to Silicon Valley at the end of last year. We had the unique opportunity to discover the secret fabric of the Silicon Valley ecosystem and reflect on what it means for our very own future. Here are my key takeaways on the future of the market research industry putting on a Silicon Valley lens.
Back in 1930, the economist Keynes already predicted that in 2030 we would only work 3 hours a day because machines would be doing our jobs for us. While robots and artificial intelligence are still in the early stages of development, automation will undoubtedly take over from humans. We are about to witness a world where having robots around us will be as familiar as having a coffee machine in our kitchen. Oxford University estimates about half the existing jobs will be gone in less than 20 years from now. With intelligent machines getting smarter not just by learning from humans but also from their machine peers, technology will destroy more jobs than create new ones, which is referred to as the ‘great decoupling’. What’s more, machines never get tired or sick, don’t waste time on Facebook, don’t choke under pressure and don’t join a union. So expect robo researchers to come for your job soon. They will be able to analyze data in a more sophisticated and context-dependent way using artificial learning (think about the way Google’s AI won a game of Go by defying millennia of basic human instinct), they will replace human moderators having passed the Turing test multiple times already (think about the near-human cognitive capabilities of Amelia, an AI system learning how to perform the work of call center employees and possibly taking out 250 million jobs in no time), they will auto-code and -interpret speech and text as well as visual information (think about Google’s PlaNet computer that can tell where nearly any photo was taken). While most of us are still convinced the research future will be about blending robotized automation with humanized interpretation, I expect it to be heavily skewed towards smart machines rather than to be balanced.
During our visit at Andreessen Horowitz, Benedict Evans talked about the power of mobile, describing it as “the first universal tech product”, which is a fundamental change compared to previous tech innovations. By 2020, 80% of adults are expected to have a smartphone. Mobile is the new scale, accelerating the creation of many more components, smaller and cheaper. Smartphone components are becoming the Lego bricks providing the basis for new technologies such as virtual and augmented reality, wearables, drones, etc. As such, mobile is a new platform, not a device. Cars for example are being transformed into ‘smartphones with wheels’, with the future being electric, on-demand and autonomous. I expect a similar evolution for the market research industry, with the traditional and labor-intensive market research value chain most likely being replaced by platforms bundling mobile, peer-to-peer sharing, open data, and ‘always-on’ in a unique new mix. ZappiStore is already a good example of the direction we will be moving in.
Consumers have cultivated a power never seen before. Consumer emancipation is taking new heights with consumers capable of raising their voices through social media, of knowing more about themselves and the products they use through wearable and sensor technology and even of creating the products they want themselves with increasing access to maker tools and ‘how to’ information. It implies that research will need to revolve around consumers and their lives. I anticipate to see native research grow really big just the way native advertising is gradually oppressing traditional advertising. Our visit to IndieGogo is a good example; started up in 2008, IndieGogo is now one the global leaders in crowdfunding. By democratizing funding (400,000+ campaigns per year), Indiegogo helps fill a massive gap in providing access to capital, helping small entrepreneurs as well as larger corporations like GE, Sony or Hasbro to source, improve, sponsor and/or validate innovations. IndieGogo applies native research as, in just 30 days, companies can get critical feedback on features, price, messaging and so on, while at the same time building awareness for the new product. It taps into the logic of behavioral economics to test and optimize the performance and go-to-market strategy of new products. In addition to asking what people want, our industry needs to learn from companies such as IndieGogo to tap into real rather than claimed or intended behavior.
The on-demand society which we live in will hugely impact our professions. This was well demonstrated during our visit at Quid, a company focusing on solving the problem of dealing with the huge amount of data, 80% of which is unstructured. With most existing tools being unsuited to deal with complex questions and not providing any context, Quid reads and organizes information on a massive scale and helps you see connections. Augmented intelligence is what they believe in: a blend of computer intelligence with human intelligence. An algorithm reads texts from public economic (patents, private investments, newspapers, etc.), public consumer (social media) data or data dragged in from specific owned data sources, removes meaningless words, creates a mathematical fingerprint of a document and develops connections between different fingerprints. The result is an overview of different networks containing massive amounts of documents. Really cool is that, depending on the similarity of the content that is scraped, Quid gives a color code to content which is similar in nature, thus creating natural ‘segments’ in the network (e.g. interpretation of facts, objective facts, discussions related to impact on politics, etc.). Following the Quid example, the future of the market research industry will be much more visual, slicing and dicing information based on different tags, in line with how our human brains work. In the future, I expect to see a big shift in the way we consume data, moving from static, one-off and textual information to dynamic, continuous and visual information.
The future is unfolding quicker than we all think, with exponential technologies driving the massive change. But, as one of the speakers said during our Silicon Valley trip: “It is never too late to be early”. Make sure crazy ideas have a place in your company and apply a ‘just do it’ philosophy: sometimes just trying is better than thinking too hard about how to do things. Good luck in embracing the Silicon Valley DNA!