In the modern world, there is a growing tendency of information overload in regard to people’s ability to consume, rate, and sort it out. At the same time, with lower barriers to enter the media market (everybody is a publisher), we see a situation wherein media quickly react to events and support authors with different views on the problem, but with less and less ability to pre-filter and rank authors and their materials.

People face two problems, which influence the manner they make their choice in and a variety of choices they have:

  • There is a growing “censorship”, caused by naturally limited attention people are able to pay while looking for information. It happens often with popular topics, that, whenever you search for media related to them, all the pieces are essentially the same.
  • While media pieces, popular by any sensible metric, may look like a good choice, it happens often, that they are only a good choice for majority. Or biggest group. Or – and this is what makes situation really sad – for nobody.

To create some content is easy. To create that of quality, to distillate many pieces of content, to make a story of it – this is an art of editorial work.

And this is a must for content delivery system too.

There are ways to enrich the content space for internet users by illuminating the problem from different angles and making the user’s experience more comprehensive and diverse. These are:

  • Cross-channel communication, incentivising cross-channel content discovery;
  • Smart use of tagging and auto-sampling of news agenda based on users’ background (with built-in out-of-field discovery mechanisms, dedicated to bring new and unexpected scenarios to user’s established routines;
  • Look-alike/score alike targeting – audience differentiation with no discrimination;
  • Bottom line-based metrics instead of use of intermediary metrics like views/clicks/time spent.

Let’s look at native advertising and content discovery landscape

Video ads are almost as unrelated to accompanying content and watcher’s background, as it was several years ago. Consider the following:

  • More people preferring videos to text (30% vs 54% for business executives according to Forbes research; in another survey, 59% of business executive answered they prefer video materials to text);
  • More persons developing selected blindness (so that 60% of people under 40 do not mind watching in-stream video advertising before and after the);
  • More persons relying in search of contractors, equipment and methods to be used on video (with 51% of execs under 40 making business-related purchase in comparison with 26% of those, who are older than 50).

According to Socialblade, categorial distribution of 100 most popular YouTube channels is as follows (first 10 for highlight):

As we see from the entire list, videos are mostly for entertainment still, and, at YouTube, they are for reviews, clips, game replays, comedies and – to less extent – Discovery-like commercials. It is ok, but many of the categories are not represented in current internet video space at all.

There are basically two ways to deal with this situation: play along or to try to go against it

In the first case you will, naturally, abuse the power of viral clips, pre-roll ad or two (making sure several others are played in background) and hope that Internet is too big for you to ever make everybody angry with your tactic. As you already use the most viral videos, it is better to resort to YouTube gems for filling your video layout, and, as advertising and videos you use are often unrelated, not to care about their complementarity at all – the way you show such ads and audience you get leave few chances for you not to increase click-through-rate/delivered-to-shown impression ratio in comparison with default case.

One team which decided to go against is NVB, a decentralised native video advertising platform, leveraging power of machine learning for efficient ad targeting mechanic in order to give smaller player an opportunity to focus on content creation, relying on modern content distribution and targeting technological solutions, born in AdTech, and fed with information on auditory segments, users’ associations and most looked-after news/topics.

Instead of resorting to purely manual approach, characteristic for a few professional news media we still have (and even less of other types), or pursuing big numbers no matter the relevance and quality, common for big media platforms of mass-market, team has decided to try a dual approach, picking vloggers on individual basis while retaining predominantly automated approach when it comes to placement, frequency of repetition and targeting for created material.

With other complementary platforms going to market, such as AdHive, AI-controlled influencer marketing platform, which aims to serve as facilitator of qualitative content creation, and ThetaLabs, creating blockchain-powered video delivery network, new approach to native video advertising coupled and co-evolving with video content discovery will, in our hope, prevail in a future.


Editor’s note: e27 publishes relevant guest contributions from the community. Share your honest opinions and expert knowledge by submitting your content here.

Featured image: 123RF Stock Photography