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Complex is a New York-based media platform for youth culture which was founded as a bi-monthly magazine by fashion designer Marc Ecko. Complex reports on trends in style, pop culture, music, sports and sneakers with a focus on niche cultures such as streetwear, sneaker culture, hip-hop, and graphic art. Complex currently reaches over 120 million unique users per month across its owned and operated and partner sites, socials and YouTube channels”



Digital ad sales is big business. How big? Well, we’re about to see digital ad spending in the US surpass TV for the first time, representing 37% of all US ad spending going in to 2017. That big! For publishers like Complex, engaged visitors means a greater exposure to ads, higher click rates and, as a result, they are able to generate a sustainable revenue stream across their publishing network.

A large, active and engaged target audience is exactly what advertisers like to see. As a result, publishers focus their efforts on providing unique, engaging and relevant content to their readers, which helps keep them active on their site, promotes future return visits and increases brand recognition.

The Challenge

The Complex Media Network welcomes more than 120 million unique visitors each month. Ultimately, the goal is to serve each and every individual user with relevant ads based on the content they are viewing and/or based on a number of other factors such as geographic location, demographic profile, device type, time of day and many more.

Complex offer varied ad-targeting features across their network, enabling ad partners to target readers based on the previously mentioned factors and triggers. However, until recently, they had little to offer partners on contextually placed advertisements.

A contextual advertising system analyzes website text for keywords and returns advertisements to the webpage based on those keywords. For example, if a visitor is reading an article about fashion, they can be targeted with ads for related products or services, such as clothes and sneakers.

The need for digital ads to become contextually relevant is greater than ever before as web users move away from engaging with online advertisements. These stats and figures certainly confirm the challenge faced by online publishers and emphasize the need for more targeted ad campaigns;

  • In a study, only 2.8% of participants thought that ads on websites were relevant to them.
  • A January 2014 study found that 18 to 34 year olds were far more likely to ignore online ads, such as banners and those on social media and search engines, than they were traditional TV, radio and newspaper ads.This is a huge chunk of the Complex target market.
  • The average clickthrough rate of display ads across all formats and placements is just 0.06%
  • Users who are retargeted to are 70% more likely to convert.

In particular, Complex were looking to automate video insertion in articles to help scale views across their sites. They already had an automatic video insertion widget in place, however the information being fed into it was the result of a manual process that ultimately proved to be unreliable. They required an intelligent automation of this process.

The Solution

With up to 70,000 web pages being analyzed on a daily basis, Complex needed to automate their processes by automatically categorizing and tagging articles based on topics, keywords and mentions of specific entities. This data could then be fed into their video insertion widget.

Complex display content-relevant videos towards the end of many of their articles. These videos contain pre-roll ads that are targeted specifically to the reader. For example, I was reading an article about Frank Ocean and at the bottom of this article I was offered a video related to singer.

If I’m reading a story about a certain person or topic, the chances are that I’ll be interested in viewing a related video. When I clicked play I was fed a pre-roll ad about mortgages from a bank here in Ireland. Yep, I’m currently house-hunting so this targeted ad was bang on the money!

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Complex display content-relevant videos towards the end of many of their articles

Endpoints used

Complex are using our Concept Extraction endpoint to extract and disambiguate mentions of celebrities, companies, brands and locations from online content and our Classification endpoint to then categorize this content for indexing among their various publications and channels. Let’s take a closer look at each endpoint and how Complex use them to improve their processes;

Concept Extraction

The Concept Extraction endpoint extracts named entities mentioned in a document, disambiguates and cross-links them to DBpedia and Linked Data entities, along with their semantic types (including DBpedia and types). By extracting concepts, Complex could easily understand what people, places, organizations and brands are mentioned in the articles they publish and were then able to produce a rich tagging system to assist with their ad targeting.

Here’s an example from our live demo. We entered the URL for an article about rappers Lil Wayne, Birdman and Tyga and received the following results;

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Originally, Complex were using keywords in their video insertion widget that were manually entered by editors via their CMS. However these proved to be unreliable and insufficient so they decided to automatically extract them using our Classification endpoint.

The Classification endpoint classifies, or categorizes, a piece of text according to your choice of taxonomy, either IPTC Subject Codes or IAB QAG. Complex classify their articles according to IAB QAG.

Using the same article, we analyzed the URL and received the following results;

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The first category returned was Celebrity Fan/Gossip which fits the bill perfectly in this instance. Note how confidence in the other categories gradually declines. While still somewhat relevant, we declare our lack of confidence in them. By providing confidence scores, users can define their own parameters in terms of what confidence levels to accept, decline or review.

“Since working with the AYLIEN Text Analysis API, we have seen great improvement in CTRs on our video widget, which translates to preroll revenue.” – Ronit Shaham, Complex

The outcome

Understanding content at this depth has enabled Complex to place pin-point accurate videos and creative ads throughout their content in a semantic, less intrusive way. The concepts, categories and data points extracted are used to organize this content while being fed into an intelligent contextual ad recommendation engine and video insertion widget, which has led to a significant improvement in Click Through Rates from videos embedded within the content. This increase in CTRs has naturally boosted pre-roll revenues for Complex.

In particular, Complex found the extracted keywords to be most accurate among a number of solutions they trialled, which ultimately led them to choosing the AYLIEN Text Analysis API.

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As consumers of online content become more and more immune to the effects of online ads, marketers and publishers are having to find ways to connect with them on a more personal level. Through a combination of data collection, text analysis and machine learning techniques, highly-personalized and targeted ads can now be served instantly, based on the content itself and viewer demographics. This really is a win-win for all involved as the visitor sees useful material, the publisher sees higher CTRs and the advertiser receives more traffic coming in from these clicks.

Wanna learn more semantics in advertising? Check out our blog post – Semantic Advertising and Text Analysis gives more targeted ad campaigns


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Brands are investing more in digital marketing today than ever before. Digital ad revenues hit a record high in the first half of 2014, surging to $23.1 Billion, suggesting ad spend is growing steadily and not slowing down anytime soon. The Ad-Tech sector is definitely, “hot right now”, innovation and disruption within the industry is primarily focused on Programmatic Advertising, Cross Platform Advertising, Social Advertising and Mobile.

But are we missing something? Are we forgetting that web users don’t like ads and that ad targeting, in general, is less than satisfactory?

The digital ad space today is made up of display ads, banners, pop-ups, search ads and so on that are targeted on the actions or behaviours of an internet user which can all be placed under the Behavioural Advertising umbrella.



Behavioural vs Semantic Advertising

Behavioural Advertising, is what most of us are used to and quite frankly, are sick of. It’s a form of display advertising that takes into account the habits of a web user. It focuses on the behaviours of a web user and usually relies on cookies to track the actions or activity of a user, whether that’s a search made, a visit to a site or even the geolocation of a user.

Semantic advertising is different. It applies semantic technologies to online advertising solutions. The function of semantic advertising technology is to contextually analyze, properly understand and classify the meaning of a web page to ensure the most appropriate advert is displayed on that page. Semantic advertising increases the chance that the viewer will ‘click-thru’ because only ads that are relevant to what the user is viewing and, therefore, interested in, will be displayed.

Why is Semantic Advertising important?

Unfortunately, digital ads online are pretty poor, often times they’re just annoying and sometimes they can be damaging for a brand. In a nutshell, as the amount of content published and consumed online increases, ads are becoming less targeted, more intrusive and a lot less effective. Don’t believe me? Check out some of these sound bites and stats gathered by HubSpot CMO Mike Volpe. (My favourite has to be this one: “You are more likely to summit Mount Everest than click a banner ad.” )

Who should care?


The publisher, for the most part, will own the web pages the ads are displayed on. Their goal is to maximize advertising revenue while providing a positive user experience.

Today more than ever there are more people browsing privately, privacy laws are tougher than ever and advertisers are looking for more bang for their buck. Publishers need to embrace moves away from traditional cookie-based targeting to more semantic-based approaches.


The advertiser provides the ads. These ads are usually organized around campaigns which are defined by a set of ads with a particular goal or theme (e.g. car insurance) in mind. The goal of the advertiser is to promote their given product or service in the best way possible to the right audience at the right time.

Reaching a target audience for advertisers is harder than ever before online.  The main issue limiting the display market is context or the disconnect between ad placement and content on the webpage: misplaced ads can often impact negatively on an ad campaign and its effectiveness. Advertisers, need to focus on more strategic targeting methods, in order to meet their target customers where and when is most effective.

Ad Networks

An ad network acts as a middle-man between the advertiser and publishers. They select what ads are displayed on what pages. Ad networks need to care about keeping their advertisers happy and providing ROI. Brands and advertisers do their best to avoid wasting ad spend on misplaced or poorly targeted ad campaigns. That’s why Ad networks need to differentiate themselves by offering alternative targeting options like semantic targeting to improve ad matching and the overall return they provide.

In our next blog, we’ll focus on the basics of how semantic advertising works, for more on the benefits of Semantic Ads check out our previous blog post Semantic Advertising and Text Analysis gives more targeted ad campaigns.