8 of the 10 largest publishing houses in Germany are working to create a single database of their readers. In parallel, user data is joined by The Guardian, CNN, Financial Times, Reuters and The Economist.

1000 sites, including the largest tabloid Bild, began to exchange arrays of data. Axel Springer, Gruner + Jahr, Bertelsmann Group and Der Speigel have postponed traditional rivalry and share with each other (read - with direct competitors) valuable information about their readers. So publishers are responding to Google and Facebook: corporations now control 85% of the digital advertising market , while the rest of the players have to share the leftovers.
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“Our biggest competitors are not conservative publishers. Together we must unite our forces against Google, Amazon, Apple and Facebook, ”says Carsten Schweke, general manager of Media Impact, a sales house owned by Axel Springer.

How did the idea

To sell advertising in the media without analyzing big data is very difficult. Yes, each publisher has a certain amount of information about users in terms of targeting, segmentation and behavioral factors. But today this is not enough. Requests advertisers are constantly growing. They want to get the coverage of the desired segment of the audience at the same time on multiple sites. A separate media outlet and even a publishing house do not have the necessary data for such a framing. In other words: to make money in a market where advertising is targeted by segment, modern media needs big data. At the same time, not all media can boast the presence of specialists with sufficient technical expertise in analyzing big data. Yes, and contain a similar service to many simply can not afford.

Participants in the Pangea Alliance project, created last year by leading media companies around the world: The Guardian, CNN International, Financial Times, Reuters and The Economist, also came to the need to merge their data for successful advertising targeting.

“Data is critical,” says project manager Pangea , director of revenue for Guardian News & Media, Tim Gentry. According to him, exchanging primary information about their users, media companies create "unique and attractive audience segments." For example, subscription information from one publisher may be combined with behavioral information received from another. As a result, a detailed user profile is created, for which advertisers are willing to pay.

How does the new database in Germany

Raw information from publishers enters a single platform called Emetriq , which is managed by Europe’s largest telecommunications company Deutsche Telekom . The latter sifts and clears data to create highly targeted, high-quality audience segments, using which publishers will improve their advertising offers.

For the use of data segments, each publisher pays a fixed amount of from € 4,000 ($ 5,000) to € 15,000 ($ 17,000). The price depends on the page impressions on the sites and the amount of data used from the general “bank” when displaying advertisements.

Such projects are being launched in Germany not for the first time. In 2010, the seven largest publishing houses in the country, including Axel Springer, created a joint venture AdAudience, which sells advertising on the principle Programmatic direct. This is how Emetriq accesses publisher data, each of which preserves anonymity. Publishing houses can use social and demographic information about users, data about their behavior on the Internet, purchases made, as well as about the semantic core and the context of websites. So publishers create high-quality reader profiles and advertising segments that are attractive to advertisers.

All segments created by Emetriq are reconciled with the consumer panels of the GfK research team. Deutsche Telekom also adds some of its own data in exchange for the opportunity to be the only advertiser with access to them. Together, this gives an accuracy rate of 87%, says Daniel Neuhaus, CEO of Emetriq.

Segmented data is returned to publishers who can select a particular segment to run through their own data management systems (DMP).

Why share data

Combining data helps to reduce the dependence of publishers on Google and Facebook, which now dominate the market thanks largely to big data. "Drain" resources into a single bank, publishing houses in Germany create an alternative and relatively large set of data that will allow them to earn more, notes Business Insider .

According to Daniel Neuhaus, German publishers are still far from the level of media giants, although they are getting closer in quality and quantity of data: “No one suffers more than publishers and sales houses in Germany, because they have insufficient data and their arrays of unstructured information users can never even compare closely with Google and Facebook. ”

“The concept of Emetriq is to help people be innovative wherever data is needed, and to make it a reality,” said Neuhaus. According to him, the fact that Google, Facebook, Amazon and Apple collect data and keep it at home without sharing with anyone “will ultimately kill innovation”.

“The real benefit of the merger is to create better segments that customers really need at the same time with high coverage,” said Stefan Kreutz, CEO of the joint venture AdAudience. According to him, it is not so difficult to get a good quality of an advertising campaign with low coverage or, on the contrary, high coverage with poor quality. “But to do both at the same time is a difficult task,” added Stefan Kreutz.

Ultimately, the benefits to the publishers are obvious. They get extended, anonymous data segments from a “common pot”, which is much larger than their own brand portfolio. Due to this, publishers can increase their CPM (cost per thousand impressions of the ad unit). Since the project was launched quite recently, AdAudience does not provide figures showing CPM growth, but, according to Stefan Kreutz, there are already the first signs that it will be “significant”.

How data aggregation will change the market

Combine data and many commercial brands engaged in direct sales. This allows them to target and retarget customers, get information about their purchasing interests and the time when they are ready to shop, as well as about gadgets and equipment that they have.

For example, at the end of last year, the British partner network Skimlinks launched a “data cooperative” called Audiences by Skimlinks , in which more than 55,000 publishers and about 20,000 sites of retailer companies participate. Based on information about the behavior of users, segments are created that allow you to successfully target advertising.

Alicia Navarro, the CEO and one of the Skimlinks founders, explained the advantages of participating in the project. For example, a certain user on the website of the publisher, after reading the article, clicks on the link about the women's bag and is redirected to the website of the store selling this product. If the purchase is finally made, the following chain occurs: page view> click> conversion. Even if the user ultimately does not buy anything, the publishers and retailers participating in the project receive a pattern of behavior (pattern) for a specific user. When it appears on another publisher’s site, it can be sent back to the page that sells women's bags, thanks to the cookie file that Skimlinks leaves on the user's computer. According to the creators of the project, led to an "almost incredible" increase in conversion.

According to Marketing Land , advertisers pay for segmented CPM data. Income is distributed among the members of the “cooperative” on the basis of the data they provide: the more valuable the data, the greater the profit. For example, information about page impressions costs less than information about clicks.

Alicia Navarro notes: "The more data we have, the more accurately we can be." According to her, the Audiences by Skimlink project is also unique in that the participants in this “cooperative” see “all the way from content to a commercial transaction,” while other data providers, as a rule, have only data from retailers or only customer data. intentions.

Another project of this kind is successfully developing in the United States. Based in New York, Bombora monitors search queries, document uploads, webinars, trade show registrations, article views and blogs, video consumption, likes and share in social networks and other evidence of the activity of entrepreneurs who are looking for certain goods and products. Forbes, Aberdeen Group and about 2,500 other sites that provide data on more than a billion monthly interactions with their visitors are involved in this project - as a rule, these are business buyers. Then advertisers and agencies use this information for marketing and sales, offering it based on targeting to interested business companies.

Bombora claims that it was their company that became the “first aggregated source of behavioral data for B2B, which created“ the first of its kind “data cooperative” of premium class media companies. ”

Is media cooperation possible in Russia?

On such initiatives of Russian publishers have not heard. Experts note that the media environment in Russia is not yet ready for such projects. We can tell you about our experience with big data in the media on the Russian market by our own example - Relap.io .

More than 2,000 media in RuNet use the Relap.io advisory widget, more than 100 of them earn on personalized native advertising Relap.io . We know how users behave and what texts they read. This helps us create user interest segments. We can recognize the user on any site and show him an advertisement, regardless of what he is viewing - a specialized website about tourism or news.

We divide the money from advertising in half with the site. The better we allocate segments, that is, the more accurate data on user behavior on different resources we collect, the more money the native advertising will bring to the site and the more we earn ourselves.

So knowledge of the user's behavior on different resources helps us increase media revenue.

Read the material on Habré , where our leading developer talks about how we analyze the texts of media platforms.