Five Successful Consumer Big Data Applications

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Mark Young rounds up five popular everyday big data applications and asks what inspiration businesses might be able to take from them

In this day and age, consumer use of new technology is what drives the enterprise use. We have seen this with cloud computing and Bring Your Own Device (BYOD) and we will now see it again with big data. Users will demand that the functionality that gets served up to them at home to be replicated in the office.

So which consumer big data use cases provide us with the most innovative examples and what can business learn from them?

1. Partnering for end-to-end service: Spotify – LastFM – Songkick

With the Internet music service Spotify, you can instantly stream pretty much any track that has ever seen a studio release. A handful of bigger names have opted out (Oasis, Metallica, Led Zeppelin and The Beatles most prominently) but other than this, there’s not much you can’t find on it. Most niche tastes are catered for, and you can listen to as much music as you want for a few pounds per month.

Meanwhile, Last.FM – considered by many to be one of the founders and key players in the East London ‘Tech City’ start-up movement – is an Internet radio service which automatically tracks all of the music users listen to, and then suggests new music they might like.

Finally, we have Songkick. Another East London start-up and a key employer in the rapidly growing ‘Silicon milkroundabout’ jobs fairs, Songkick allows users to track their favourite bands and receive live updates when new gigs are announced.

The magic happens when you link the three together. You play music on Spotify, Last.FM gives you a dashboard wiyh information on what you are playing, while Songkick scans Last.FM to find out what bands to keep you updated on. Every app is fully operational across PCs, tablets and mobile.

What businesses can learn:

Quite often, services like these work better in partnership, rather than isolation. Historically, a lot of software has been developed specifically to be inoperable with anything outside of the developer’s own portfolio. This is changing somewhat on the business front, with software companies bowing to their customer’s demands for better links in order to expand their possibilities.

Therefore, businesses that are looking to utilise the services of one particular company should explore closely whether that company has interoperability with any other services, the combined benefit of which would be greater than the sum of its parts.

2. Information layering: Sat Nav and traffic updates

One of the best additional features of the Sat Nav systems that we use to find our way around (much to the dismay of not insignificant army of paper map enthusiasts) has been the ability to turn live traffic updates on, and have them superimposed on top of the map as red lines.

This constant visualisation of the build-up on our roads probably won’t force old Sally Traffic into an early retirement just yet, but it’s probably fair to say that it offers a far more reliable and accurate  alternative.

What businesses can learn:

Satellite navigation systems are already something of an achievement in the big data field. Now, with real-time traffic displays, they are an inspiration for more effective visualisation of data through the use of information layering. The analysts, in their infinite wisdom, say advanced visualisations will be a development that will grow in-line with the rest of big data applications – now that we have significantly greater volumes, variation and velocity of data, we need better ways to present it.

Specifically, we need ways of presenting it dynamically – with depth, paths and pockets of data, and high levels of interaction. Through these features, these extensive and complex data sets can be delivered to, and understood by, busy executives who have no desire to pore over reams of numbers.

3. Data transparency: London transport services

Want to know where that infernal London night bus is? There’s a slew of apps which will tell you its exact location and how many minutes away it is from your stop. Want to plan your journey across the London travel network, comprising Overground journeys, Underground, London buses and even the Thames river transport? Just go to and input your start point and destination – it will give you several options for the best way to travel, mixing and matching various means of transtportation, starting immediately and factoring in any delays, detours and closures all in honest real-time.

We won’t even get into the fact that the Oyster system works across the lot. Even without that, the London travel operations represent one of the best consumer-facing uses of big data that you can witness.

What businesses can learn:

Giving as much information as you can to your audience breeds trust. Clearly the data that the London bus operators use to monitor their services needs to be collated centrally for operational purposes. Making it available for the public has had immense benefits.

There is no easier way to create a ‘them versus us’ mentality with your customer base than to keep them in the dark. Today, many organisations are beginning to operate under the mantra of total transparency. When they get things right, it makes it easy to celebrate success; when they get things wrong, it offers an opportunity to appeal to a level of human understanding and, hopefully, avoid public spanking.

This new politicised ideology for communication appears to be an active policy across Transport for London. Whenever there is a two minute delay on the tube, the drivers know that the only way to avoid a mutiny on board is to come clean with all of the details of the incident. The honesty certainly appears to reduce the vexation back to a mere grumbling. How do we know it’s an honest account? It’s difficult to see why they would bring out the grim ‘one under’ calls unless they were true. Meanwhile, on the platforms, the fact that engineering work has overshot its schedule once again would surely not be admitted unless it was the policy to do so.

Big data offers the chance for ultimate transparency – there are many companies out there that could do worse than pick up the baton.

4. Appropriating data: health monitors

There are countless health and diet monitoring applications now available across PCs, tablets and smartphones. These include pedometers, heart rate monitors and calorie counters. These apps are effectively a digital personal trainer which is responding to you and the real things that you do every day.

The apps make use of the kinetic sensors and GPS tracking devices within mobile phones to monitor the speed and distance at which the user is moving. Users can also scan the barcodes of the food products they eat and collect information on all of the nutritional values, including calories, saturated fat, salt and so on. The apps will then schedule exercise routines or diet based on general health recommendations or the user’s fitness or weight ambitions.

What businesses can learn:

The most effective of these tools are the ones that make it as easy as possible to administrate on behalf of the user. Working out is hard enough, without having to spend ages calculating what you’ve done and what it’s been worth to you and probably, in all likelihood, getting it wrong somewhere down the line.

In order to succeed, the apps need to automate and make use of other data that is created or already available, such as the sensors of the mobile phone or the barcodes.

What this teaches businesses is that a whole host of pre-existing data sources can be brought in to add value to their product – and anything that can be leveraged to take away pain from the user can work out to be very valuable indeed.

5. Real-time analysis, visualisation and interaction: Squawka

Squawka is a so-called ‘second screen’ application for football fans. It allows them to see a portfolio of different statistics and analysis of a game in real-time on their PCs or tablets.

Users are able to see general stats about the match (possession, shots etc) and each individual player (pass completion rate, distance covered etc). The really clever bit is that the developers have created an algorithm which they can use to establish how influential each particular player has been in the game.

What businesses can learn:

Real-time, visualised analysis of events is no longer a pipe dream, nor the preserve of mega rich tech organisations. In the case of projects like Squawka, it is now available for free.

Watching sports is the ultimate armchair activity – the majority of people that do so delight in getting one over their friends in the pub by purporting to have a theory about a particular player. Really what they do is repurpose statistics and comments made by the commentators and pundits.

The point is, if you give somebody the tools to do something easily and effectively, they are much more likely to adopt it. There is a certain type of football fan that will love Squawka because it allows them to instantly understand the game. If an executive had the same information about his business, it would allow them to easily spot opportunities for process efficiencies or potential revenue streams. You you can they will use it – it’s their raison d’etre.

Mark Young is editor at Big Data Insight Group, where this piece first appeared

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