Acquired Novosense
Piano Media, a paid content strategy provider, has acquired all technology and associated rights of Austrian real-time audience identification technology company, Novosense (view press release).
The acquisition brings metered pay-walls and individual content payment systems into Piano’s product portfolio. Known as ‘Piano Solo’ the new technology aims to allow individual media to more efficiently monetise online content while also providing detailed user analysis of real-time activity on a media partner’s website. The move also sees some of the Novosense staff join the development team at Piano.
Piano Media’s CEO Tomáš Bella said: “We knew that Novosense spent the past five years perfecting their technology and the opportunity to incorporate it into Piano’s system presented us with an ideal platform to create a new product. Some of our media partners were asking for individual systems; now we can offer something which will be absolutely the best solution for them. With these innovative analytics we can be even more exact when determining what the best method to monetize content is; whether a client would be better served using an individual premium system, a metered pay-wall or a combination of the two.”
Whitepapers
Related reading
Central banks best suited to issue digital currencies
By Aaran Fronda A recent report by the Official Monetary and Financial Institutions Forum (OMFIF) said that central banks rather than private ... read more
Instant payments: innovations inbound for corporates
In 2020, instant payments look set to continue their current trajectory to become the biggest trend in payments. While these schemes already offer numerous benefits to corporates, leveraging innovations such as APIs and request to pay will go some way to unlocking their full potential, argues Michael Knetsch
Obstacles exist for banks to meet ECB’s instant payments goal
The cost of joining instant payment platforms will be one of many hurdles banks and payment services providers must overcome to meet ... read more
Banks must be aware of “biases” in data used to train ML models
Financial institutions need to be conscious of biases in the historical data that is being used to train machine learning (ML) models, ... read more
