Dr. Augustine Fou, Chief Marketing Science Officer for The Advertising Research Foundation and myself are writing a series of blog posts inspired by our recent roundtable at CES. Each time, we’ll both write a post on the same topic to provide a wider range of views. Here is my first post on the evolution of geo-location. Will post Dr. Fou’s next.
We now live in a world where we can identify all public conversations at the neighborhood level.
This level of technology advance has the potential to revolutionize how we look at the 1,9,90 model. Today, we can identify who the influencers are who create content (the 1%) and who shares and shapes the conversation (the 9%) to reach those of us who choose to benefit from all of their work (the 90% who lurk and learn).
So now we can identify, via geo-location, who has influence by neighborhood, which means that we can correlate who has influence at the store level. It means that we can see who has the most influence in a town or city vs. a region or country. It means that we can see how word of mouth actually moves across a region.
In the future, we’ll be able to map out the entire retail network for BestBuy or Walgreens and show exactly who the right people are to go to for a promotion of a new PC or for a health screening.
And this is where we start to realize the power of geo-location and the limitation of Internet of Things.
Geo-location allows us to understand the “public you”. IoT allows us to understand the “personal you”. The only problem is that our personal data is most often stored and owned by companies who provide us with sensors to track our body, house, car and other relevant data in our life. We don’t keep that data and it can eventually go away, never to be seen again.
Why is this important? Here are four key reasons:
Preventing and managing our health – knowing how many steps we take each day is cute, but not the answer to managing a disease, like diabetes, for example. We need to combine the knowledge of our bodies (heart rate, blood pressure, steps), our choices (which restaurants do we choose) and our educational needs (Q&As, ideas on how to live healthy) and be able to access all of our data to share with our family and our physician. We need aggregation of data across all Apps.
Providing the information we want – we don’t want most coupons, deals and emails outlining the wonderful new idea du jour for us. If we can see, holistically, what we talk about publicly, where we go physically and where we are near over time, we can see that just because we are near BestBuy, we don’t want a deal sent to us, but if we have been searching for a new HP PC in the last 30 days and we’re now walking into BestBuy, we probably are interested in a deal for that system, but not unrelated merchandise we have never looked for.
Learning how to improve our lives – biometric sensors could tell us that we need a backpack, since the briefcase we carry on our shoulder is going to wear out our body over the next 10 years. Or we can get advice on how to change our posture to avoid lower back problems. Or we can see that we’re not heating our house optimally and we could save $75 per month if we adopted a new routine. We need cumulative data and aggregated sensors to tell us this.
Understanding the real boundaries of privacy – when we see the data that is being created related to what we do and say, we also develop a better understanding of what we are comfortable with sharing. Today, too much of this information is not known. We’ll get the privacy situation right with full transparency and access to our own data. Our own data should not be a mystery to us. With the “public you”, we can see and keep it all. With the “personal you”, it sits behind a walled garden.
The result is we’re making great strides in understanding the “public you” but we have a long way to go to understand the “personal you” and combine this data, so you (all of us) are better off for it.
Walled gardens of data will never get us there. We are all smarter, companies and consumers alike, when we have full access to the data that is appropriate to help make the best choices in our lives.
This will require a consolidation of the IoT world for us to get there. It won’t happen via individual companies creating better sensors and apps. It will happen when some of the larger companies in the world start buying 20 or more IoT apps per year and start mashing them up to get the insights we really need. We’ll have to create the ability to access, store and learn from our data over our entire lives. We’ll become our own Google, in a sense.