How would you describe the skills makeup and scope of your data team?
Schibsted’s data and analytic capabilities are primarily located close to the market and the brands. Data competences, primarily focusing at behavioural data, is paired with research, insight and business expertise to ensure that it drives actual business value. The output from the data can both be data driven products and decision support.
What are the most important components of your data and AI strategy?
The core of the Schibsted’s strategy is to minimise number of weak links in the processes of refining the raw data into insights and actionable conclusions. The data and analytics is seen as a crucial component in the vast majority of the core processes of editorial and consumer business rather than a standalone function.
To ensure rapid development and high focus at business application a scalable data architecture will be crucial. Machine learning, AI, is a common component already used in various predictive models. However, developing the methodology itself is not in focus but the applications are.
How is audience data used to drive advertising and subscription revenue?
We use audience data for several purposes such as statistical modelling, content optimisation, pricing (both B2C and B2B), segmentation, optimisation of customer service etc. The overall objective is to provide our users and customers with relevant and personal(ised) experiences through fully data driven products.
If you were advising other data directors on how to build their operations, what key lessons would you impart?
- Clean up your data structure. You need high quality data you can trust
- Focus at application and do not dive too deep into fancy techniques
- Make sure your data and analytics team is close to core business. It is much harder to succeed if you have a highly specialized team disconnected from the people producing output (content) and/or doing marketing activities
- Build data and analytics’ competences in your management team and/or management level
- Minimize time spent in number logistics and try to automate recurring tasks
- Make sure you have the right people and competences. Recruit new competences if necessary
How does audience data factor into product development and improvements at Schibsted?
We use audience data to identify new opportunities and optimise core processes across most of our business. How we do this varies from project to project and process to process. I believe this is more a of a mindset question: We need to make informed decisions. Looking at audience data is a very easy way of working data informed.
In your opinion, what does the future hold for the business use of data and artificial intelligence in media?
I believe data and AI will continue to be extremely important going forward. Our first experiences with algorithms running our front pages, optimising advertising sales and improving how our products work are mostly positive. We believe that a combination of human creativity and smarter technology will help boost our business going forward. A higher degree of machine learning in our processes doesn’t have to imply less human interaction. Human creativity and fingertip feel can be enhanced with well design decisions support.
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