It's been estimated that Brits spend six months of their lives talking about the weather, and digital tech enables us to talk about it even more. So when the Met Office wanted to enhance its digital offering, its analytics showed that consumers were particularly interested in content that brings weather data to life – such as information that helps them plan for events or learn about weather phenomena.
The Met Office also focused its efforts on determining specific types of content that drive the most engagement – video is particularly effective on its mobile app (for example, what is a weather bomb?) – and tailoring content to different demographics, such as infographics about the pollen season or blogs about Glastonbury.
By creating and distributing this kind of contextual content, the Met Office has built its social audience up to 1.75 million. It's just one example of how organisations are using data to improve their business and enhance customer experience. This is often driven not necessarily by big data, but, as the Met Office has done, by utilising data smartly and swiftly.
However, what rarely gets talked about in public is the way that data is used internally by businesses to understand the impact of their decisions. I recently attended an Econsultancy roundtable and spent a couple of hours with a variety of renowned high street brands, as well as data and digital platform suppliers, discussing this very topic, among others.
It was fascinating to hear some of the issues organisations have in understanding the value of the data that they hold. One of the perennial problems seems to be the idea of whose data to believe. With so many different stakeholders involved, from product teams to channel owners and functional departments, each is eager to prove that their version of the ‘truth’ is the correct one. If anything, the proliferation of channels has only made things worse.
Unearthing the real value of the data and the data teams themselves is not achieved overnight. Often organisations can achieve big successes by starting with small, low-risk projects where value is added to existing reports incrementally. Then, as awareness of this capability builds knowledge and instils confidence, there can be a gradual increase in the number and scale of projects. It’s just as much about data culture as availability of data and platforms.
Scale of projects also means moving away from just delivering numbers, instead focusing on adding insight to those numbers. But insight can only be delivered by combining data and providing the data teams with some background. Without knowing the ‘where we’ve come from’ and ‘why we are doing this’, it can be very difficult to deliver the ‘so, what next?’
Talking of ‘where we’ve come from’, it is unrealistic for marketers to expect analysis to be available even without the original input from the analysis teams to help steer framework setting and data collection. If we haven’t been able to collect historical data in the right way, please don’t assume trends or comparisons can be made!
And one last thought for those who may think that buying the right tech or software can magically eliminate all the hassle. Think again: without enough analytics resource you’re never going to reap the benefits of that Google Analytics 360 investment.