How can we transform Big Data into the Big Idea that turns into an opportunity in the digital revolution? How can we use this data gleaned from multiple sources and turn it into smart “consumer style” data driven, mainstream apps? The answers aren’t easy.
But without these answers we'll be unable to develop the data driven-apps that analysts are flagging as the next “Big Thing” in the sales and marketing arena.
Breaking Down to Bite-Sized Pieces
Customers want “mainstream” apps that are useful, provide information or tie into key personal or business data. They want apps that can deal with huge amounts of data, while providing it in an intuitive, visual way – much the same as consumer apps -- that are “click and go.” Where users can learn on the job and don’t require any training. If these apps can be personalized -- so much the better. Users also want apps that respond to the context of their daily lives, both in and outside of work. They want apps that can hone in on their locations and that can be synched and accessed on a variety of devices, including emerging wearable technology.
Forget “Big Data,” think “Small Data” -- bite-sized functionality. This is the best and easiest way to consume big data. We therefore need to develop “information hubs” that will centrifuge out big data from multiple sources, into small data that will make apps deliver on functionality and make them even more customer focused.
The Challenge in Delivering Small Data
So the test is to deliver small data to customers, both internally and externally, in mainstream, useful apps that deliver on content.
The mainstream data apps will include an infusion of historical, real time and trend-based data. Real time data can be used to target selling services for consumers as well as support business functions such as inventory optimization. Historical or trend data can be used to develop competitive intelligence or create online merchandising apps. This is just the beginning. There are many compelling apps that can be developed by refining big data into actionable small data.
This all sounds great, but remember that to get to the full potential of data driven, customer apps, we need powerful technology to collect and process the data, as well as tools to create visually compelling apps that are useful and easy to use.
Guidelines are starting to take shape that will help data-driven app designers achieve their goals. These best practice guidelines started to take shape after watching the move from big data to practical small data in my role as an analyst and researcher at firms such as Yankee Group, McKinsey and most recently Digital Clarity Group, where I and my colleagues defined the concept of small data in a marketing environment.
Supporting these emerging principles will be better business analytics and superior APIs. A few rules of the road to keep your apps on course:
- Focus on The Customer -- The app has to be useful to the customer in order for it to be adopted and used.
- Don’t Focus on the Macro Picture -- Think about what your customers -- whether internal or external -- are going to need from their big data filtered into small data, and how it can be delivered effectively.
- Scale is Key -- Don’t forget you will need the resources to launch your still data-driven apps to thousands if not millions of customers, on different devices, from smartphones and tablets through to wearables.
- Personalize, Personalize, Personalize -- This should be your mantra. Data-driven apps need to be customizable, according to each user’s requirements.
Consumers have seen the potential of small data to streamline their shopping and help them get the best deals, from Amazon “buy” recommendations to Kayak’s “When to Book” tool. Now enterprises need to jump aboard fast. With wearable technology emerging, there will be even greater demand for packaged small data -- both in and outside the workplace.
Big data may be on everyone’s lips, but the real revolution is small data. This is all about people being able to collaborate easily and effectively around an ecosystem of small data, distilled from the big data barrel. Small and simple sells!