Media companies are not data companies.
Data companies make money by managing and processing data. Media companies make money by attracting and retaining human attention.
Good data, technology and data scientists can only help a media company if they serve the raison d’etre of media businesses.
Data projects are deployed to support business goals, of course, however the legacy departments – editorial, ad sales, marketing, accounts – must change their behaviours and mindsets to gain the benefits that data offers.
Data quality, data technology and recruiting data scientists all persist as challenges, but all are solvable after an effective audit of both business needs and available suppliers – as well as making the right choices, of course.
However, “non-data” departments and employees must embrace the benefits of data. That requires cultural changes which good data, technology and data scientists cannot attain in isolation.
1) You cannot just delegate data projects to the data team
There’s a common misconception that media businesses can recruit a team of data scientists that will single-handedly optimise and monetise a company’s data. All the other departments can carry on as they were, and the data team will deal with it.
Data professionals are not media professionals, a fact confirmed by Deloitte’s Data Maturity Report which makes clear that it’s hard to find enough data professionals that understand the media business.
Media businesses must start recruiting media professionals that understand data: data journalists and data-driven colleagues in sales, marketing and business development. The objective must be for every department to make the most effective use of data as part of their day-to-day work. That means they must have the same level of practical, technical and mental access to data as data scientists. They must also be involved in devising data strategies. They must own the data projects from the get-go. That will give them an emotional attachment to data. When they help to devise the projects and to build the products and services, they will be more likely to use the data.
Working Effectively with Data Teams
2) Be prepared to use “brute force”
Deloitte’s Data Maturity Report is really quite blunt in places, thank God. It recognises that silos are a barrier to both “data fluency” and “data democratisation”. Whilst setting KPIs and managing incentives may change behaviour in the long term, the report is clear that in the near term “brute force” may be needed to “break down silos without apology” and “discipline [is] critical to making cross-functional teaming the norm.”
Silos are a cultural condition of media businesses, most apparent in the long-standing division between the commercial and editorial functions. With regard specifically to data, Deloitte rightly recognises the problem that one department collects & analyses data, but another department monetises it. Yet Deloitte really doesn’t go far enough. In all but the most data-advanced media businesses, data collection, processing, analysis and monetisation are performed outside of the core, most demanded product of the media industry – the editorial content. It’s imperative that all departments should be able to make use of data, including the editorial team.
As well as tackling the departmentalisation problem that characterises all media businesses, it’s imperative that media businesses chooses a data platform that’s so easy that you don’t need data scientists to use it. If only data scientists can use the data platform, a new “data team silo” will automatically result, and the media business’s use of data is immediately restricted.
3) Start with top performing departments
Departments already performing well based on their established business practices are often the most reticent to adopt new strategies. After all, if it ain’t broke, why fix it?
However, it makes sense to start deploying a data strategy with these departments. Rather than suggest anything new, the first step should be to simply use data to articulate the current capabilities of these top performing departments. That’s a quick win. It will give them proof of their success. That gives their team a morale boost, whether they need it or not. They can show off the data to senior management teams. Those human motivators encourage them to adopt data strategies.
When data helps to sell their current offerings – which it invariably does – it makes it easier for those departments to sell new data products and services.
Other departments are always encouraged to learn from top performing departments, too. Once one department has a positive data project experience, other departments will be more open to applying data to their activities.
4) Train the departments in data strategies and tactics
Since data professionals aren’t media professionals, and media professionals aren’t data professionals, most media businesses aren’t getting the most out of their data. Those that rely on a specialist data team for all their data operations only seem to build the most basic audience segments or run rudimentary queries. The data is a largely wasted asset.
When departments are empowered to self-serve their data needs, able to build their own audiences and run their own queries, they start pushing the boundaries. They get more engaged with the data and start to use it more frequently.
As well as choosing an easy-to-use data platform and breaking down silos, employees need training on data driven marketing and sales strategies. There’s plenty of technical training available on how to write SQL queries, but good data platforms have made running extremely advanced queries WYSIWIG (What You See Is What You Get) now. Hence media professionals really don’t need to learn how to write an SQL query – although I’d never try to stop them.
Running queries, building audiences and extracting reports – that’s the basic stuff. What they really need to know is: how to set data goals and strategies; what sorts of data tactics work for their objectives; how to use data to inspire innovation and creative ideas which are the lifeblood of the media industry.
5) Ensure creative ideas are supported by data
There’s lies, damned lies and gut feeling. The media industry rightly holds creativity in high regard, however, there is such a thing as a bad idea. Performance data proves that, whether in audience sizes, engagement rates, sentiment, sales and the bottom line. Far too often media businesses run with tactics simply because they appear “cool”, “creative”, “visually impressive” or “hot right now”.
Products and services that people want, need and that work are far more successful than those that are simply creative.
When media businesses have data at their disposal, they’re foolish not to use it to inform innovation and to guide creativity. Using data reduces the risk posed by relying on gut feeling.
What’s more, when media professionals that can accurately analyse data are frequently surprised and inspired by the data. They develop a more acute understanding of their audiences, enabling them to engender ideas that people engage with. When campaign managers can use a data platform well, it’s like conducting market research and campaign testing on amphetamine.
It’s easy to get consumed in the geekiest elements of deploying a data strategy – the technology, the regulation, the data science, the artificial intelligence, and of course, the cost. However, the importance of the “soft” issues must not be underestimated. The benefits of data technology must be obvious, applicable and accessible to every single department, never restrained by departmentalisation or complexity. If cultural considerations are overlooked, it will take far longer to maximise the value of the media business’s investment in a data platform.
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