Insights & Decisions Are “The Brain” of the Media Tech Stack [Infographic]

About 4 or 5 years ago, the conversation in the publishing business started to focus on becoming “data-driven” and developing 360-degree views of the audience. There was industry-wide recognition that data was the fuel for any revenue-growing activity – and the future of the media business overall. As Publishing Executive contributor Rob Keenan said back in 2014, "The key going forward is figuring out how to mine your data, so that it's turned into something actionable and ultimately something that you can sell back to your clients." Many publishers have spent the interim centralizing their data, structuring it, cleaning, and appending. While some publishers may be more advanced and successful in these efforts than others, it’s fair to say that we’re now entering Phase 2 of the Data Driven Era of Publishing. Now that audience data is collected in centralized databases, the focus for publishers is getting it out – or more appropriately -- extracting insights that can be used to make decisions. It turns out that decision-making is just as important as (and more monetizeable than) insights, because decisions lead to actions, and actions are where publishers can demonstrate ROI for marketers. It’s clear that this is where publishers are investing their technology dollars: The Top Technologies Publishers Will Buy in 2018 report revealed that Audience Analytics tools are at the very top of publishers’ shopping lists this year. If we look at the below infographic of the media tech stack, we can see publishers have squared their investments on the “Decisions” component of the tech stack. These tools serve to take the raw data (in the broad sense of data being audience data, content, and advertisements/marketing offers), extract insights, and arrive at decisions that inform the distribution of that data through publishers’ many platforms, owned and distributed. Publishing Executive developed the below media tech stack in collaboration with our advisor board of digital media experts. Click the image below to view the full infographic. What Do We Mean by Audience Analytics? To be fair, “audience analytics” is a broad and nebulous technology category. For the purpose of our buying intention research report, we defined audience analytics as “tools to track/manage/visualize audience.” Of course, many tools in the media tech stack provide a measure of this type of functionality. In order to get more granular results on what tech publishers are buying, we separated out several technologies that can be key to increasing audience intelligence, such as DMPs, CDPs, content analytics, ABM and lead gen platforms, and social media tools. Trying to determine the best lineation between technology categories when developing our buying intention report was a difficult task. This speaks to the challenge that publishers face when making technology investments. Because the so called “tech stack” is more of a spider’s web, it’s hard for publishers to know where one technology ends and one begins, whether a new shiny tool on the market offers truly new capabilities that can’t be achieved with their existing tech, and if a new buy can eliminate costly redundancies. Where is Audience Intelligence Headed? In the tech buying report respondents indicated that “making audience data more actionable and monetizeable” was the number one business objective they aim to achieve through technology investments. To do so, publishers are developing the brains of their tech stack. So where is this brain development headed? Using technology to extract insights that a human couldn’t Putting machine learning to work to answer important questions and solve problems Making decisions at scale and taking automated actions Making data more accessible to non-data experts through visualizations Personalization, personalization, personalization Here are some of the technology areas publishers should start or continue venturing into to boost their intelligence. Data Visualization – Publishers (and organizations in general) have underestimated the need to make data more understandable and actionable for all parts of the organization and are looking to change that. Social Listening – Harnessing machine learning and data science to optimize content distribution and maximize content engagement. Predictive Analytics – Driving content recommendations, lead gen, ABM, and ecommerce capabilities, and price optimization/subscriptions. Prescriptive Analytics - tools that suggest decisions based on descriptive and predictive analytics. Business Intelligence – perhaps all these capabilities could be rolled up under the even more nebulous concept of business intelligence, but BI really gets to a more holistic business analytics view that goes beyond the content-audience-advertiser equation. Publishers are beginning to eye this space. Publishers will need to constantly increase the intelligence of their tech stacks not just to be competitive with other publishers, but to compete with marketers’ own capabilities. Many marketers are working to develop these same capabilities, though they face even greater organizational challenges because it’s not the main focus of the organization. For publishers, tech stack IQ is job number one.

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Insights & Decisions Are “The Brain” of the Media Tech Stack [Infographic]

Denis Wilson

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Denis Wilson