In a previous post I was thinking about some of the exciting things we do with Wimbledon, and I thought it might be useful to add some practical applications of social and analytics in other industries.
I’m not going to talk about Big Data. If I’m honest I don’t really like the term. To me there’s just data. And there’s an abundance of it, some of it we own, some of it we don’t but we do have access to, some of it is highly accurate, some more questionable. There are many types we can make use of, from a variety of sources, in many shapes and sizes. And a lot of that data can be from social media and from social business platforms – that is, from systems of engagement.
When that data is analysed it can allow you to do something you were already doing but do it better – because you have a better understanding.
It can allow you do something you weren’t doing but is related to a strategic objective such as understanding customer sentiment to become more customer centric.
It can even allow you to do something truly transformative such as real time traffic flow optimisation, as is done in Dublin.
There the city uses data to identify and solve the root causes of traffic congestion in its public transport network. This means they improve traffic flow and provide better mobility for commuters. Data is taken from a citywide network of sensors, bus timetables, cctv and combined with geospatial data and the gps updates transmitted by the city’s 1000 buses every 20 seconds. Using this, the traffic can be monitored and managed in real time by those who have the responsibility in the city.
Based on the success we are now working on projects with Dublin and our Research organisation to add meteorological data into the traffic control centre so actions can be taken to reduce the impact of severe weather on commuters. We are also developing a predictive analytics solution which will combine the city’s tram network with electronic docks for Dublin’s free bicycle scheme.
We tend to divide analytics into three categories although there are other ways to do it. Those are descriptive – what happened, predictive – what is likely to happen – and prescriptive which not only anticipates what will happen and when it will happen, but also why it will happen, and suggests decision options to take advantage of the predictions.
I see a lot of organisations do the descriptive analytics, whether using more intuitive and interactive dashbords or just, dare I say, excel spreadsheets. Fewer are taking advantage of predictive, and even fewer prescriptive.
So, with the right type of analytics there all sorts of things one could do:
- We can predict and act on the intent to purchase. It’s possible to identify what customers are researching and send this information to human and online channels. The SlamTracker keys to the Wimbledon game are based on prior player performance, and we can similarly understand customer behaviour and predict likely purchases.
- We can truly personalise our interactions with the customer. System U within Watson – needs just 200 tweets to understand an individual’s wants, needs, psychological profile, emotional style, and so on, and this – combined with any other data we may have about a customer – can allow us to tailor the right message for the right customer at the right time. I talked about this at the TEDxUniversityofStrathclyde recently.
- IBM helps Thames Water analyse a range of social media channels including blogs, online forums and Twitter to create real-time public opinion snapshots, identifying trends and usage behaviour while understanding how consumers feel towards the brand. But we are taking that analysis one step further and working with other water companies around the world to determine where there is a leak in the infrastructure using social media as a feed.
- In Toulouse they use social media analytics <French site> to understand where they have a problem with their road infrastructure – pot holes to you and me – and they’ve cut response times down from 15 days to 1.
- In the Netherlands and the US we’ve applied analytics to social media to understand the likely success of programme and film launches, and to take direct action to change the outcomes.
For Wimbledon data and insight is crucial to the fan experience. The same can be said of all business, replacing the word “fan” appropriately – “employee”, “consumer”, “citizen”, and so on.