I love personal data tracking.
Some examples of what I use on a daily basis:
- Fitbit – General Health
- Zeo – Sleep Data
- RunKeeper – Running
- Ginger.io – Wellness
- Pandora Favorites/ Last.fm – Music Playlists
- iFitness – Workout Data
- RescueTime – Productivity
And the list goes on and one all the way to just simple pen and paper (which works really well for most things.)
For this post, I counted the number of devices and applications I own solely designed for passively tracking my life data.
The count: 12
(And its growing …) 🙂
However, despite all of the data I’m collecting on a daily basis – I’m not really doing anything with it.
Yes, I love the graphs my Fitbit creates each week and the maps of my runs created by RunKeeper- but beyond that, I don’t really gain any value spending all this time tracking the activities of my life each day.
What I find really interesting is that every company in the world is experiencing the same problem today.
They’ve spent the last few years capturing trillions of bytes of information about their customers, suppliers, and operations through active human input or passive sensors because data was important – but very few have figured out what to do with it.
Similar to my situation above – some have created interesting charts mapping performance over time or heat maps of where customers are located – but no one has truly found a way to take data and make it really useful for the end customer. (And others haven’t done anything with the data yet at all.)
In reality, it’s not their fault. We’re at the beginning of a massive shift in how products and services are built and the first wave of this shift was fully focused on enabling companies to more easily collect and store the firehouse of data that was being created by their business everyday.
As part of that we saw tremendous innovation with:
- Rapidly declining cost for sensors and mobile devices which allow for simple passive data tracking and collection
- The creation of opensource database products such as Hadoop and Cassandra optimized for large quantities of data
- Relatively cheap storage, bandwidth, and computation via platforms like Amazon and Rackspace
And the end result was two-fold:
- Companies are storing a ton more data about their business that they’ve never been able to track before
- Companies are opening this data up to other companies and developers for use in new products and services
And what’s exciting is that this “open access to data” has created a for significant disruption and value creation not seen since the beginning of the “social web.”
Similar to the early days of the social web (when social was just a feature, before becoming core to every product today) – there is going to be tremendous opportunity for early players in the market as data moves from being simply a feature to a must-have core part of every new product and service.
Or simply put – the next wave of software applications are going to be driven by this new world of open and available data sets – in what we’ve been referring to at True as “Data Apps.”
In short, “Data Apps” are software applications where the core user experience is driven by combining various sources of data (both internal to the application and from third-party sources) to create value for the end user.
These products will leverage both internal data (collected via sensor and human input) and external data via third party API (such as Yelp or OpenTable.)
The net experience puts data at the core of the product experience – leveraging data inputs from various sources to create new actionable insights that were unapparent before.
Some early simple examples of data products:
- Milo: Leverages local inventory data to tell users where a product can be purchased near them.
- Linkedin: People you may know feature
- Klout: Quantifying social media influence for consumers
And today, this is more a feature than core to the entire product offering.
However, in the case of Milo, it’s not too hard to imagine a similar product that goes a step further and taps into my purchase history (via a service like ProjectSlice) to tell me when a clothing brand that I like is having a sale or that my laptop is coming up on warranty and I might want to check out a new one.
More over, go a step farther and a product like Milo who is able to take input data from sensors in my home and can remind me to pick up milk on the way home or even help me plan the dinner party it finds in my calendar by selecting a recipe from Epicurious and purchasing the ingredients from Safeway.
Even today, we’re starting to see early examples of this type of product design with companies like Ginger.io who are tracking cellphone sensor data to provide predictive healthcare insights for consumers.
By sensing the change in your movement and contact patterns, the team is able to predict when an end user is going to have a health issue. While today its only for a few select diseases, its not too far fetched to imagine the day when the growing numbers of sensors and time enables them to get better and better at predicting issues (and potentially even order your prescription at the pharmacy and schedule an appointment with your doctor.)
Yes, all of these examples have huge privacy implications and seem like crazy big brother issues today – but as technology improves and makes our lives better – those problems will be dealt with.
As technology continues to improve with innovations such as Linked Data and people continue to get more ambitious in how technology can improve their lives – we’re going to see more and more products leveraging this outside data set pushing the boundaries on better enabling us to live happy lives with the help of technology.
From a purely technical perspective – no longer will the “What’s your technology stack” question be answered by simply Linux, Apache, Database, and a Language – but rather will include a list of first-party sensor and third-party data inputs that will be core to the product design and execution.
Value is created at the bleeding edge of emerging platforms.
As the social wave moves towards maturity and social becomes a required feature set, it opens the door for the next wave of value creation in data and data-driven applications.
And I’m totally ready.