Marketing Week hosted the Data Storytelling conference in September, which attracted a large crowd of likeminded professionals from across both marketing and data fields.
The agenda was positioned to explain the concept of mobilising data through building greater understanding of the customer and then exploiting insights using informed campaigns.
It was a brave ambition that covered a wide gulf of technologies and opportunities.
Key to the conference, however, were two underlying themes. This wasn’t a smoke and mirrors affair where promises of big data were banded around by vendors (I’m as skeptical as anyone going to data conferences), but a surprisingly operational discussion around where and how data fits within marketing today, across a range of industries, data types and opportunities to utilise the data.
The two key themes centered on making use of appropriate data as an asset, and having the right blend of staff to enable creativity to play a part.
Read on to find out more, or for more on this topic check out our range of data and analytics training courses.
Data isn’t something that happened as a result of digital.
Yes there has been an explosion of data available to marketers – especially on customer behaviour – yes it comes from confusing and complex data sources, and yes it’s hard to structure it all together.
But really the crux of the issue comes from the belief that this (from a data management perspective) is something new.
The old marketing mantras still apply – get whatever you have got together, group up your audiences and use those groupings to generate understanding.
This was very much reinforced during Kenneth Cukier’s keynote suggesting ways to survive the big data avalanche – to focus on what matters. Data types and context are much more important than volume.
Kenneth Cukier from The Economist
Case studies given by Visa, where operational segments could be derived quantitatively from multiple under and over indexed variables, or the qualitative approach taken by British Airways to get an emotional judgement on every aspect of a customer’s journey, were great commentaries on how to focus in on key data types that best relate to the products or services being offered.
As a recent MSc graduate, having a research method that must match your hypothesis was not lost on me.
Select only appropriate data to include in your data story. What data do you really need and how do you operationalise it?
The end result should operationalise itself. A well informed matrix of behaviours and patterns that fit groups of people within your customer base cannot help but inform your campaigns.
The wealth of information only blinds you, so start small and expand, growing your data relevancy and include new streams over time.
As Land Rover’s case study explained, justifying little wins first will then allow greater expenditure. This is after all, not a one stop project, it’s an ongoing discipline.
People and the future: P45s for marketers?
Okay, so there’s a skills shortage in data. Clever data analysts are hard to find.
Juan Mateos Garcia from Nesta suggests that this is impeding his end goal, which is to create multi-disciplined teams formed from a fusion of science and creativity.
We have talked around necessary marketing skills before, however these people have proven hard to find. Kenneth Cukier’s keynote commented that sooner or later algorithms and processes would replace the humans and decisions will be made faster and more accurately by computers.
That may be so, but it lacks creativity and, as both Kenneth and other commentators have noted, good marketers know when to ‘flip the bird’ at data and make decisions based on intuition.
Juan Mateos Garcia from Nesta
I think the reality is Ken holds marketers and their data sources in too high regard (kind although it is).
In general I agree with the idea that data-led decision making is too formulaic, so data-informed decision making is preferable as it helps to ensure creativity.
But my concern would be that egos within marketing teams would lead decisions to be made by intuition in order to excuse lack of understanding, incomplete data or just the desire to push a more political agenda.
Starting small should be coupled with appropriate learning mechanisms, as imperfect data allows variables to creep in to implementations. We can then lay blame on the data processes, rather than the decision itself.
Everyone sees a place for the established, market knowledgeable staff who can balance data with their unique creative understanding.
But until marketers can embrace data as a concept that informs their everyday and the systems improve to allow them to understand the wealth of data available and its limitations, then I fear we will lurch from fad to fad.
It’s not time to throw out the rule book, it’s actually a time to revisit what we all know as marketing best practice.
All that profiling work, focusing on customer understanding, test and learn – data allows us to move closer to that halcyon academic world.
We, as marketers, need to embrace this world and not just rely on data scientists. We need to challenge them with our understandings and make them model our customers to give us stuff we can actually use in the real world – and conferences like Data Storytelling really help pull together these disciplines and understanding, adding to the conversation rather than just confusing people further.
I hope the Festival of Marketing in November will continue that discussion. My colleague Sam has been promoting the idea of ‘festival playlists’ – with over 200 sessions available over the two days, he suggests we should create customised tracks for different disciplines and share them.
Ashley has created his ‘202 reasons to attend‘, keep an eye out for ours tailored for data professionals – see you there!