Tag Archives: social media analytics

Don’t be a virus

This should be the age of personalisation, where companies send communications that are both personal and personalised to each of their customers, as appropriate.

One of my favourite ways of doing that is using  Personality Insights Service (some may know of it by its previous name of Watson User Modeling), a service that allows you to understand a person’s personality, needs and values from a variety of inputs of your choice (such as Twitter, other social media, and even your recordings of customer calls).  These characteristics are categorised into approximately 50 traits (see an example diagram below), and you can use these to understand which of your products or services are most likely to be attractive to a person.  For example, someone who has a high score against “self enhancement” may be more likely to purchase products that would support that value. So perhaps they would be more likely to buy a clothing retailer’s designer or high quality ranges.  Or may be someone who is likely to purchase wearable technology for improving their health and lifestyle.

Of course, there are other ways to use social media data to personalise – such as through knowing what a person has liked in facebook, or when they are sharing information about events in their life in twitter, and so on.

That access to a customer’s social media data is surprisingly easy to get these days.  One study has shown that 38 percent of shoppers are willing to share their social handle.   Another way to tie a social network ID to a customer ID is to use a service such as that provided by Gigya that provides a customer identity management platform to register and identify customers across your sites and apps, using their social media accounts.

Unfortunately I’ve been hearing about some companies who are not applying any sort of intelligence at all.  They are simply using their access to a person’s social media ID to find out the IDs of that person’s contacts and spam them too.

Is that not what some email viruses do? Don’t they access your address book and then spam all your contacts to spread the virus further?

Don’t be a virus.

The 50ish traits analysed by Personality Insights.

The 50ish traits analysed by Personality Insights.

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Making Wimbledon Relevant

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.

IBMslamtracker

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