I spoke at this year’s Tessitura Europe Conference in Manchester on “the importance of context”. Over this series of posts I will try to explain why I think meaningful context is essential, the issues we need to overcome to harness data in a useful way, and some examples of meaningful context in action.
We are all increasingly opening ourselves up to more and more data and as a result we’re overwhelmed, measuring the wrong things or unable to understand the broader context within which all of this data sits, may make more sense and as a result may be able to provide us with some useful insights.
You’ve got important data in your ticketing, CRM, fundraising and retail systems, you’ve got data relating to website behaviour (probably a few different pots of that) and also for every digital platform that you’re active on. You’ve got data relating to email activity, you’ve got data relating to your digital ads. There’s probably a load more I’ve not mentioned. That’s a lot of data.
Whilst there are some notable exceptions for colleagues and organisations who may be comfortable with using data as part of the conversation, driving priorities and areas of focus, as a sector we are very, very bad at it.
“the majority of arts and cultural organisations still do not use data for important purposes such as understanding their audiences better through data analysis and profiling”
“34% of respondents said they were well-served for digital skills in the area of data analysis”
Nesta/Arts Council England “Digital Culture” survey, 2017
Nesta and the Arts Council’s annual digital culture survey, which in 2017 surveyed over 1000 arts organisations, found that the use of data was limited and only a third of organisations felt they were well set up to be able to make the most of data analysis.
And it’s not just the Arts Council, the Department for Culture Media and Sport have found the same thing, in their recent Culture is Digital report they identified the same sector-wide issue around the collection and use of data.
“A lack of skills in data analysis is preventing cultural organisations from collecting data and using it to develop their business models”
DCMS “Culture is Digital” report, 2018
So we can measure absolutely everything that’s happening online, but we — as a sector — are under-skilled and not comfortable using data to drive core activity and help set priorities.
So this is a problem, if more and more of our activity is being delivered online. And audiences are increasingly looking to engage with us online. And we can measure all of this. But we’re not, as a sector, well set up to be able to use and act on this data then that’s a huge missed opportunity.
If we can’t join the dots between all the data we’re capturing and generate meaningful, actionable insights then we aren’t going to be able to keep up with the rapid pace of change and ever increasing user expectations.
It’s getting easier and easier to access data around activity on every single platform, everything now comes with its own, baked-in metrics dashboard.
But none of these metrics really tell you much that’s useful, they are almost all interested in vanity metrics (“x number of people looked at your profile last week”…great?), and none of them are really set up to be able to help you fill in the detail of the bigger picture.
This silo-ed, isolated data is useless, it’s like peeking through a hole in a fence, you’re never going to be able to properly understand what you’re looking at.
We know that ours users move across platforms in their interactions with us but almost every free, baked-in metrics package presents isolated data that actively works against you being able to understand the bigger picture.
So the ability to measure everything has become an overwhelming task in filling in the gaps and whilst our ability to measure everything grows and grows, this growth is also fuelling responsible for an increase in guesswork.
We’ve just seen that as a sector we don’t have enough of the skills that might help us understand each pot of data in a broader context. How do we join the dots? It’s hard.
I believe we’re becoming increasingly trapped, trapped in a sea of meaningless, unconnected data, trapped by metrics that don’t really tell us anything useful, trapped by our lack of time and lack of knowledge around being able to make proper use of all of this.
What should be an exercise in ever-increasing certainty — I mean, we can measure everything, right?! — is actually causing problems and increasing uncertainty.
We are stuck in telling the only stories we can. The simple stories. When the human brain is confronted with complexity it looks for the easy, or most obvious, answer.
And most frequently that story is: “This is what happened last time”, and the decision-making process attached to that too often seems to be “if it wasn’t a failure last time then…let’s do it again?”
If we’re only telling ourselves the story of what’s happened, over and over again, we’re limiting our context. If your only reference point is the last time, or the last few last times, that you undertook that activity you’re not really giving yourself a chance to make particularly nuanced or informed decisions.
Labouring under false impressions or a partial understanding of the situation isn’t going to do anyone any good.
That story is not going to improve user experiences.
And we need to improve user experiences.
We need to understand our audiences and users, their motivations, needs and frustrations. And we need to understand that all of those things exist in a much broader context.
Our audiences are not just ‘our’ audiences.
If people are doing more and more shopping online — the UK spent £13.7 billion online in 2017 and spending more and more of their ‘leisure’ time on platforms like Netflix — there are about 5 million Netflix accounts in the UK, which will represent a far larger number of actual users. And cultural web traffic actually accounts for a fairly insubstantial chunk of UK web traffic, then we need to be realistic and understand that when users interact with us, firstly we are making up a very small part of their day, but secondly they spend so much of their time online that they have a level of expectation that we need to understand and deliver to — users don’t care that we’re cash-cash-strapped and time-poor, no-one resets and lowers their expectations when they engage with us online.
But if we’re struggling to really understand where the friction is in those experiences then we’re never going to be able fix them.
If we can’t construct a meaningful context, and understand the data we’re capturing within that context, then we’re never going to be able to properly understand how or what we should really be focusing on.
In the next post I will look at some straight-forward changes you can look to make that’ll help you better capture meaningful data. I will also share some examples of where a broader, more detailed contextual understanding of how your users are behaving can be harnessed to drive meaningful improvements in your digital experiences.
Originally published at substrakt.com.
