How our VAMP project will tackle the challenges of the voice/audio revolution

  • Content Delivery: enabling editors to deliver customized audio content to different outlets, e.g. smart speakers, audio platforms, social media.
  • Content Discovery: allowing users to search and find audio content according to their interests and consumption needs, e.g. while commuting, during housework, for a quick update.
  • Monetization: establishing revenue streams through innovative ad formats and ad serving, e.g. automated, performance-based ad insertion, and new paid offerings.
  • Analytics: providing reliable metrics for content and ad performance, e.g. completion rates and drop-off points.
Main fields of work for VAMP: An open infrastructure that provides components for delivering and monetizing journalistic audio/voice content
Modular framework for optimized monetization: Built on efficient production, delivery and analytics of audio and voice content

1. Content Delivery

  • Bridging the audio-text gap: For us, voice-engineering our primarily text-based content by adding standardized features for audio is a clear first case. Each article will be supplied with voice-optimized abstracts that can be machine-read. News briefings could be generated from homepages. Editors should be supported by linguistic content checks.
  • Rebundling audio: This is about structuring audio content for repackaging and reusing — automatically slicing up podcasts into sections that can be delivered according to the demands of different devices.
  • Distribution: For publishers, it is essential to control the distribution of content; for editors, this process needs to be easy. A custom database and player to distribute audio to different platforms facilitates the collection of data for our analytics module.

2. Content Discovery

  • Metadata and tagging: Adding metadata and tags to each audio snippet (using speech-to-text technology) to make audio content searchable. This also builds the basis to deliver audio in topic-based dossiers according to user demands or queries.
  • Social media integration: Developing a simple workflow to clip soundbites and combine them with compelling visuals and subtitles to expand content reach.
First outline of content model and architecture: Creating agile journalistic audio by adding metadata and adjustable ads

3. Monetization

  • Consumption-driven ad sales and pay-per-hour ad offerings. Packages such as pay-per-hour — in which ad clients pay for real minutes listened to — are more attractive to advertisers and enable publishers to optimize their inventory. Reliability of audio ad delivery is a key factor in increasing its attractiveness for clients. Customers will buy a specific amount of listeners’ time; ads are dynamically rendered into streams based on this sales mechanism, standardizing the ad product.
  • Establishing new forms of audio ads/integrations. Ad clients would like to target their message more effectively to specifically desired audiences and have them delivered in a more standardized way. However, they do not want to lose the specific touch of podcast ad formats (classic radio ads would be no alternative). A versatile audio ad management combined with a tailored player and distribution technology is key for that.
  • Establishing new forms of voice ads/integrations. The same challenges exist with voice UI, but they are even harder to address due to the limited number of ad slots on current platforms. From a publisher’s perspective, these ad limitations diminish the appeal of this technology. We want to apply versatile ad management and player/distribution technology not only to audio content and ad offerings, but also to voice UI products.
  • Human voice ad solutions: Establishing native-speaker ad solutions for voice. As some platforms only allow ad inserts spoken by a human voice, a dynamic audio ad server can also solve voice UI monetization issues.
  • Establishing paid podcasts in a freemium audio/voice environment to be built in the VAMP context, either as a separate product for users or as part of existing subscription offerings. With our flexible paid content technology we could experiment with selling different types of podcasts (journalistic formats, service offerings, niche products for target groups etc.) and ascertain whether there is potential for paid offerings.
  • Packaging news content with audiobooks and other long formats. We could explore the potential of creating platforms for audio longformats or promoting and selling our editors’ books; selling audiobooks by integrating our bestseller lists; developing a freemium cross-promotion system for audiobooks etc.

4. Analytics

  • Consolidated audio metrics: We will create a data hub that uses APIs and website scraping to collect and consolidate metrics.
  • Content performance analytics: The absence of tools such as Google Analytics or Chartbeat in the audio realm would be eased by basic stats tools that analyze listener curves, exit moments or top voice request keywords.
  • Journalistic/Delivery KPIs: amount/percentage of voice-enabled text-first content, minutes of newly produced and voice-enabled voice-first content, minutes of accessible voice-enabled content etc.
  • Consumption-driven KPIs: (growth of) listened minutes of our audio offerings, (growth of) number of voice UI interactions etc.
  • Technical KPIs: percentage of text-first content items, e.g. regular articles that are fully voice-enabled automatically, percentage of audio-first content items, e.g. podcasts that are managed and served through our open and automated system, etc.
  • Business-related KPIs: Of course, revenue and profit growth are the primary goals of all commercial enterprises. In the nascent market of voice-enabled audio content we face the following challenges with classic KPIs: First, there are no standard metrics established for the monetization of digital audio content on voice-interfaces. Second, market developments are highly unpredictable and revenue streams depend on the behavior of dominant tech players. For these reasons, defining monetization metrics is one focal point of VAMP itself, as described above. Additionally, we want to use the following proxies to measure commercial success of VAMP: growth of potential ad integration points, (growth of) automated advertising insertion, growth of paid content revenue.
First outline of VAMP personas: User centric approach to content production, ad placement and delivery




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