DAM News Round-Up – 5th December 2022
A series of DAM and marketing technology related articles from around the web, sourced by the DAM News editorial team.
This recent article from digital experience agency Cylogy’s co-founder and director Ryan Bennett takes a look at the Metaverse, and attempts to unravel the hype and decide whether marketing teams need to start preparing to interact with it, or simply dismiss it as another madcap idea from Mark Zuckerberg that’s destined to fail. With some surprising statistics about the current level of awareness and interaction among both consumers and marketers, the article breaks down the key obstacles to widespread adoption of the metaverse.
Digital Asset Management software provider Pics.io provides a brief introduction to digital marketing assets, including what they are, how they differ from regular marketing assets, and how to leverage the value of your company’s digital assets such as domain names, websites, email campaigns and social media platforms. There’s some useful tips and insights here for anyone tasked with building a digital marketing technology strategy in combination with a DAM system.
DAM platform vendor QBank present the third part of their three-part series on metadata structure. The topics covered in this instalment include complex business rules and the benefits of developing automated workflow that sit on top of your metadata foundation. Practical examples cover image review and consent requests, integration with Product Information Management systems (PIM), and automating expiry dates for digital assets in order to comply with licensing and usage rights.
As Stable Diffusion – a form of AI-based image generation technology along the lines of DALL-E and Midjourney – gains traction, Apple have echoed their support for the open source platform by announcing a series of improvements for M-based Mac devices including the M2 MacBook Air and the M1 iPad Pro. Apple cites numerous benefits of running Stable Diffusion locally, including security, flexibility and cost, along with offering code to help users get started with the technology. Benchmarking results, Python code, and deployment tips can be found at their GitHub repo.Share this Article: