One of the most arresting stories of the 21st century is how quickly and profoundly technology has changed marketing. It began innocently enough with banner ads on websites. Then came search and communities. Quickly after, the complex ecosystem of advertising technology (Adtech) – a multi-billion dollar vertical with a cornucopia of offerings stretching across display, search, video, mobile, social, content marketing, native advertising, gaming and commerce – emerged.
The next generation of technology emerging on top of Adtech is marketing technology (Martech). It aims to make marketing “programmatic” – operating automatically and autonomously, similar to programmatic advertising. Martech entered the vernacular relatively recently but has grown rapidly, with companies that deal in it growing from about 100 in 2011 to more than 1,800 by 2015. Martech today is spread across consumer and B2B marketing domains while it increasingly absorbs the elements of Adtech.
What connects and underpins these technologies is data. Behavioral data is generated frequently as the “exhaust” of all digitalized processes. The emergence of this data creates and fuels the disintermediation of (quantitative) research through the rise of business intelligence (BI). BI is a collection of technologies originally developed to look at areas like supply chain or finance; data feeds not relevant to the insights category. But today we are seeing the absorption of all things market research into BI, driven by expansion of data collection processes, visualization platforms or analytical systems that incorporate many of the quantitative tools.
However, the impact on qualitative research tools and platform is different, if not opposite. These technologies make current qual tools faster, better and more efficient, and also help scale them in ways that used to be cost prohibitive, if not entirely impossible, in the offline world.
Some of the new approaches are new interpretations of existing tools, like participant observations, diaries, IDIs, or focus groups. Here technology delivers a significant change but may not be a game changer. Other approaches result in completely new tool – in fact, sometimes it is debatable if these are qual or quant; just think about sentiment analysis in social media.
Once upon a time, the demarcation line between qualitative and quantitative research was clear and impossible to cross. This is no longer the case. Today’s “new qual” maintains the depth and richness of insights from the “old qual” era, but it can also scale in a manner that is more reminiscent of quant.
While big data and the technologies that create and live off of it are frequently discussed in research, they are many degrees removed from consumers and respondents. The technology that impacted the consumer most in this decade is undoubtedly mobile.
The smartphone has seen the fastest ever consumer adoption rate and half of the world’s population now has a mobile subscription – up from just 1 in 5 ten years ago. It has become our primary connector to the world, offering a solution in just about every situation (to paraphrase the popular ad: “there’s an app for everything”).
This is also true for the insights industry because research and mobile get along well. With all the capabilities mobile offers and the need for the research to be faster and better in data gathering, this dynamic duo presents great opportunities.
Qualitative research particularly benefits from mobile. With enhanced techniques such as ethnography and diaries, some argue that mobile has also created entirely new research methodologies.
Mobile offers a solution for several research challenges, including:
Video took the consumers’ world by storm and now makes it into almost every interaction they have online. Daily time spent watching online video in 2015 grew by 23.3 % across 40 key markets. And, thanks to the continued popularity of YouTube, the growth of video on Facebook/Instagram, and the accessibility of high definition video on almost any device, video growth will expand by another 19.8% in 2016.
Video increases engagement and consumer involvement in every situation. For example, landing pages with video can lead to 80% more conversions. In fact, 88% of visitors stay longer on a site with prominent video displayed. Those that stay longer spend an average of 120 seconds more on a retail site and are 64% more likely to purchase after viewing a single product video.
With sophisticated mobile devices, network improvements and consumers’ increasing ease at sharing their life via mobile, it’s no wonder that half of all video traffic in the world is now routed to a mobile phone or tablet.
While it began with professionally produced content being scaled up, the proliferation of mobile devices shifted this balance towards user-generated content. This helped create new companies like GoPro, communication services like Skype or live video feeds for social media networks like Meerkat.
This has meant that video analytics have also grown at a comparable rate. The need for enhanced insights from customer behavior gathered by the existing video platforms is driving improvements in these analytical solutions.
The video analytics market broadly falls into categories including security management, crowd detection, pattern recognition, and other applications. Pattern recognition includes face recognition, Optical Character Recognition (OCR), and object detection. This category, partly driven by the quest for insights, is experiencing the greatest increase in demand enhancing the economical scalability of video based insights generation solutions.
Scalable qual, mobile and video are powerful forces on their own, but when you combine them together a truly formidable research proposition emerges.
In summary, mobile video is an important addition to the researcher’s toolbox, upending the traditional qual-quant equation by delivering deep, rich, insightful information at unprecedented scale and speed. As techniques and methods further mature there is less and less excuse for not using it in your next research project.