Steffen Konrath

I have seen newsrooms in fear of the next round of layoffs. Constructive feedback turned into fear of failure, which usually became a prelude to the worst. But I also saw newsrooms that worked well because they knew high-quality journalism would still be honored by watching people subscribe to the feed of impactful, meaningful news or stories. Yes, feedback, but context matters as keeping corporate culture, journalistic values, and ethics.

How to create a sense of purpose in the newsroom -- or better, how to keep the journalists' sense of purpose as they usually begin their careers with high intrinsic motivation. (1) Document your journalistic work's impact on the local community, region, county, or country. There is no better motivation than to see the effect of what you are doing - and this is not measured by visitors on site, session duration, etc. (2) A note to publishers: if you shrink the newsroom all the time in favor of margin, remember that the only way to keep the quality is to turn to journalists doing journalistic work and honoring their work. There is no ChatGPT that can substitute genuine, high-quality work, and what is clickbait if you have no real impact?

Is it possible to address Unknown Unknowns and Known Unknowns? - Yes, it is. Shift the focus from Big Data (using historical knowledge to predict a future) to Small Data (the things we haven't experienced so far and lack data and knowledge). We use Small Data to find those triggers that can cause a certain future. It doesn't require you to know where to look. Instead, you rely on the method to surface questions you need to ask and future scenarios to address. Small Data analysis can help you to become antifragile (in the sense of Nassim Nicolas Taleb) so that stressors strengthen instead of breaking you.

When we analyze the status quo of a market, we use semantic (NOT! sentiment) analysis to understand the critical topics of interest for the target audience and the positioning of others in the market. Using empirical evidence helps to understand barriers, obstacles, opportunities, gaps in the mix of market offerings, and even misinterpretation without explicitly looking for all that. SWOT analysis is more like a theoretical framework, while semantic analysis is an actual way (an AI-driven method) to find the data without asking for answers directly. Using Small Data also allows us to find those events for which we lack historical knowledge to understand their impact on the business side. It's qualitative research multiplied by 10,000.

We developed a method to analyze the "genome" of the target audience. The genome of an audience is its unique blend of brand affinities, hobbies, interests, etc. The good thing is, that based on our method, we have a concrete way to segment the audience and test conversion further, adding more factors to the equation. We made this cycle a way of life for campaigning to get better and better over time.

Based on our CPL focus with full transparency on the closing of the leads, the hypothesis for the a/b testing was always the obvious question: (1) Campaigning works if costs(campaigning) < costs(traditional way of selling) (2) Campaigning a is better than version b: if costs (a) < costs (b) (3) If (1) is worse, stop the campaigning (did never happen) (4) If (2) is worse, use campaign b instead and look for more or better alternatives (c, d, ...)