So, how will Internet of Things change brand and consumer interaction? It might be too early to predict! But, in this video, Jasmeet Sawhney, talks about some areas that are emerging that give us some insight into how it might impact brand and consumer interaction.
Alphabet/Google’s revenue continues to grow. In fact, earlier this year, it briefly surpassed Apple to become the most valuable public company. But, over the years, Google has reported one number that has left the advertising world wanting to know more. Since 2011, the average ‘ad cost’ continues to decline. In simple terms, Google is serving more and more ads every year, but each ad is earning company less and less. To someone in the online advertising world, this should not be news; online ad effectiveness has witnessed slow and steady decline over the years. The industry doesn’t want its customers to know about some underlying issues that are creating an online advertising bubble. Following six issues are a big reason for concern as there would likely be no turning back the moment advertisers get a grip of what is really happening.
1 – Perils of Technology & Automation
Yet, there is a much bigger irony at play – virtues of automation are becoming its own flaws.
Advertising technology has seen tremendous advancement in the past decade. From precise user tracking and matching algorithms to automation and programmatic buying, placing an ad now requires very little human effort. For most part, this has been a big boon for all stakeholders, but some cracks are starting to show. For one – advertisers took industry’s word on ad effectiveness, who in turn totally relied on advanced technology for their argument. If you look at ad performance over the years, it paints a completely different picture – online ad efficiency has been declining, and it has been declining for some of the most advanced online businesses who really know what they are doing. Yet, there is a much bigger irony at play – virtues of automation are becoming its own flaws. Automation has made it extremely cheap to plan and place ads on small/low quality websites, which has encouraged advertisers of all sizes to join in hordes without understanding anything about ad efficiency.
“Given the modern marketing ecosystem, the single most important factor is to…”
Train marketing teams on technical skills. In the work that we do with both large and small clients, traditional marketing teams still rely heavily on IT and Business Technology teams. It ends up affecting all marketing activity since every single marketing process is driven by technology these days. Whether you are doing lead nurturing, social media marketing, content marketing, website optimization, or customer segmentation – if the marketing team doesn’t have the right technical tools and skills, none of the processes will be efficient. Same is true for data analytics, which is also traditionally a CIO responsibility, but never efficiently used if marketing teams don’t know how to work with data.
Modern marketing teams need to acquire these skills if they want to streamline processes and stay ahead of the competition.
The Internet of Things has arrived
While some continue to write it off as futuristic, they are not acting any different from skeptics we had when mobile technologies were maturing. We all know what happened next – it took only couple of years for smartphones to change our lives. And, if mobile brought ‘change’, IOT will be nothing short of a transformation. Only a couple of years ago, impact of IOT didn’t seem much. But, then, almost instantly, mobile, web 2.0, and connectivity technologies became ubiquitous and inexpensive. Technologies like Wi-Fi, NFC, RFID, and sensor tags now make economic sense for widespread use. These technologies when added to everyday products enable massive data exchanges, and make it possible for brands to deliver dynamic services.
According to Cisco Systems, 15 billion connected devices already exist, and the number will reach 50 billion by 2020. Intel is even more bullish and predicts 200 billion connected devices by 2020. But, another number from Cisco puts things in better perspective, i.e., 98% of all physical devices will be part of the Internet of Things ecosystem. While most people only think about the obvious IOT candidates such as cars, consumer electronics, and appliances, these make up a very small percentage of trillions of consumer products sold every year. The biggest opportunity for marketers is in dumb products that will become part of the IOT ecosystem via smart packaging and software.
LET’S START WITH DATA DELUGE (WHICH, BTW, IS NOT THE PROBLEM):
We all know – there is data everywhere. In the past couple of years, the world has generated more data than the prior civilization put together. Whether it is content posted on web and social media, data transmitted from sensors in cars, appliances, buildings and airplanes, or streamed to your mobile, television or computers, we are surrounded and overwhelmed by data. Advancements in technology are the main driver of this data deluge, but similar advancements have taken place in the technology to collect and store data. This has made it economical for organizations to build infrastructure to store and manage large sets of data. But, the real problem is deriving value out of this data and making it useful. This is where most of the stagnation is today. According to International Data Corporation (IDC), only one percent of the digital data generated is currently being analyzed.
THE DATA REVOLUTION IS ABOUT INSIGHTS:
Everyone agrees there is a big data revolution happening, but it is not about the volume and scale of data being generated. The revolution is about the ability to actually do something with that data. What used to take millions of dollars to first build the infrastructure and then hire really smart and expensive individuals to analyze data, can now be done in thousands. It all comes down to using the right set of new age technologies and implementing right set of rules (read algorithms) to deliver answers that weren’t possible earlier. This is where the new age data computation and analysis shines. We have come a long way to leverage machine learning, graph analysis, predictive modeling algorithms and other techniques to uncover patterns and correlations that may not be readily apparent, but may turn out to be highly beneficial for business decision making.
There have been vast improvements in how and what type of datasets can be linked together to capture insights that aren’t possible with singular datasets. An example that everyone understands is how Amazon links together shopping and purchase history of customers to make product recommendations. Along with linking of datasets, improvements in visualization tools have made it much easier for humans to analyze data and see patterns. These technologies are now making inroads into all types of disparate use cases to solve complex problems ranging from pharmaceutical drug discovery to providing terrorism alerts.