© Illustration by Aurélie Garnier
This article was written by Ann-Kathrin Wind & Marvin Suder at Handelsblatt Media, Germany.
Key takeaways to copy & share
> Handelsblatt Media Group, Germany's leading business publisher, had a paywall conversion problem that wasn't a product problem. Its four H+ tiers were each well-positioned. The mistake was showing all of them at once, at the moment of highest reader impatience > Step one was removing the higher-priced products from the paywall entirely. It felt like hiding revenue. Conversion rose significantly instead, because the reader no longer had a package comparison to work through before checkout > The new default is a single offer: H+ Standard digital access, with a trial or a three-month commitment at 30% off the monthly price > Step two put choice back selectively. A Likelihood-to-Subscribe score decides who sees Premium, on the hypothesis that high-scoring users have both a higher willingness to pay and genuine use for the extra features > The decisive metric was never initial conversion. Premium converts from trial to paid less reliably than Standard, so a failed Premium trial doesn't just underdeliver, it replaces a Standard subscriber you would have kept. The question became which offer generates the highest sustainable revenue per segment, not which offer converts best
At Handelsblatt, the problem was clear: our paywall conversion rate was too low, and we were not generating enough subscription volume.
However, product diversification was not the issue. We already offered a strong portfolio tailored to different use cases:
- H+ Standard, including digital access to all articles on the website and in the app
- H+ Premium, adds the e-paper and a paid newsletter
- H+ Premium Student, the Premium experience at a student price
- H+ Premium Business, users who also want business-focused content, events and professional learning opportunities
Each product was relevant and well-positioned. The mistake was showing all of them at once, at the moment of highest reader impatience.
We set two objectives: Reduce the number of decisions a reader has to make and make better use of our Likelihood-to-Subscribe scores.
