We live in the marketing clutter era: every day we receive several thousand advertising messages. Ad fatigue is a condition that arises when an Internet user is tired of seeing too many ads. It causes resistance for commercials and moreover can induce negative sentiment towards a brand. Because of this marketers can witness the reduction of ROI (Return of Investment).

Ad avoiders generation

The numbers speak for themselves: 64% of people believe Ads are annoying and they use Adblocker. Among other reasons why Internet users install adblocking plugs are: disruption, security concerns, better page load-time, inappropriate ad content, privacy concerns and also ideological reasons. Therefore the population of Adblocker users grew by 41% year over year. You can say there’s a simple solution: cooperate with publishers who use Adblocker walls on their websites. Not so fast! Up to 74% of Adblock users in the U.S. will leave such portals (Delhi School of Internet Marketing).

The simple deduction would suggest that people hate ads. But if we’ll take a closer look at statistics, we’d learn that people only hate intrusive ads. ”Not all ads are bad, but I want to filter out the obnoxious ones.” – 83% of respondents agreed. Moreover, they mainly dislike marketing methods as telemarketing calls, direct mails, auto-playing online video advertisements and pop-ups. From all ad categories, the most user-friendly is online video (25%). Also, 77% of respondents agree with the statement “I wish there were a way to ad-filter instead of ad-block completely.” (Video Design).

The challenge for marketers isn’t to attack customers with their ads from new sources, but to serve the best-tailored ads. For publishers quoted statistics mean that they should focus on the user experience not to lose their audience because of frustration caused by small ads. To achieve their goal, they must look for new solutions, often based on new technologies and modify the previously implemented methods. One of them is in-video commerce, which thanks to the use of artificial intelligence and machine learning are changing the face of contemporary advertising.

Hopes of video marketing

Video marketing is more and more popular: by 2019 video traffic on the Internet will arise up to 80% of the entire online consumer traffic in the world (SmallBizTrends), and Facebook by itself generates an average of 8 billion videos every day (Social Media Today). We watch the video not only on desktops but also on phones: YouTube records a 100% increase in mobile video consumption year by year (HubSpot). The video content is easily and quickly absorbed; it also can affect receivers emotionally. No wonder that the video attracts not only recipients but also publishers and advertisers.

For e-commerce, this means more advertising opportunities and the potentially more effective campaigns. For video publishers, it’s high-quality content, eagerly consumed by Internet users. Video can combine the interests of publishers (the pursuit of monetisation of content) and online stores (the pursuit of increased conversions).

The answer to these issues is cooperation in the in-video commerce field. It’s ad embedded in the video material, adjusted to the content and context in which it was displayed.

Why is the context important?

In the era of so-called „banner blindness” context in which the ad was presented to the recipient raises ad effectiveness. Unreasonable creation and inadequate time and place of its publication make users irritated – they see inappropriate advertisements, unmatched to their potential shopping impulses and, as a result, take actions to close the ad or the entire website.

Contextual advertising is maximally precisely matched to the content in which the brand performs. It makes a natural, even apparent impression and offers a personalised shopping experience. Chances that the user will enter into further interaction with such prepared advertising content, therefore, increase, placing both the publisher and the advertiser in a comfortable situation.

How does in-video commerce work?

In-video commerce is presenting to the user relevant products while watching a given video material. The products are chosen according to the content, i.e. identical or very similar to those that can be seen on the screen. Such a personalisation effect, combined with the accompanying emotions, triggers a shopping impulse, which thanks to the precision of in-video commerce, can be immediately satisfied. After clicking on the ad, the user is redirected to the store, where he can finalise the transaction in a few seconds. The time of the purchasing decision plays a huge role here, but the chosen content and good recommendations in e-commerce stores are crucial. High-quality content combined with adequate advertising can have a positive impact on user retention and conversion on the sites (both publisher and advertiser).

This is the win-win-win situation: the recipient receives personalised, relevant content, the publisher serves the right user experience, and the e-commerce store has the chance to reach the user precisely.

How does it look in practice?

Imagine a program about mountain climbing. Sharp peaks contrast with the soft clouds, and the actors overcome further obstacles to reach the goal. Such a picture carries with itself an emotional charge connected to the user’s desire to travel and hike. There’s a chance that after getting familiar with such content, you will be inspired for a place for another trip, think about buying new trekking shoes or a perfect backpack for further trips. It’s an ideal place for advertisers to present products that are adequate to the content and respond to the potential needs and desires of the recipient.

The content is analysed: the objects and the context in which they are presented are recognised. The relevant elements of the image are described with tags such as trekking, mountains, backpack (with accuracy to size, colour or type), which are then combined with products in e-commerce stores. Everything happens in a few seconds, sufficient to trigger and satisfy shopping impulses.

Artificial intelligence: the engine of in-video commerce 2.0

In-video commerce is not a new term, but only the use of artificial intelligence and machine learning can automate this process and make it as precise as possible without incurring costs (money, human resources and time). The analysis of the content and its proper tags, as well as the connection with the product feeds of e-commerce stores, allows a new dimension of monetisation, and the tagging of content opens up the possibility of quickly creating new content. This process, carried out manually, would be impossible or very time-consuming.

Plastream automates these processes by changing the face of in-video commerce. Thanks to the use of artificial neural networks (deep learning) to automatically analyse the content of images, it is possible to match the content to pictures of products in e-commerce stores and automatic reference. This is significant support for publishers in a contextual matching of ads to visual content. Plastream, however, goes one step further, in real time responding to changes in the assortment, if the product is unavailable at the moment. Search for the closest replacement regarding many features, such as colour, shape or material.

The system can recognise not only the objects but also the characteristics assigned to them (colour, fabric, length, pattern), faces and material context. Such tagging allows for the quick and automatic creation of new content. If we need celebrity photos in long dresses, thanks to the appropriate tags, you can search for them in a short time and prepare the content.

Many marketers think that in-video commerce is the future of advertising. However, thanks to advanced and continuously developed technology, this format is available today.

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