3 min.
Programmatic buying: 5 tactics to go beyond the Google Display Network
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Programmatic buying: 5 tactics to go beyond the Google Display Network

  • TECHNICAL LEVEL
Paid Media & SEM

Display marketing is changing rapidly with the growth of  programmatic buying . Google has contributed to this growth with the Google Display Network, but this platform remains limited in terms of control, targeting possibilities and variety of sites available.

 

In digital media, the sinews of war is  the audience . Audiences are those segments of users potentially available online to receive our advertising messages. Ultimately, in a performance model, we want to use all the tools and all the data available on users in order to present our advertisements only to those who are likely to be interested. The more we segment our users and the more we test a wide variety of tactics, the better equipped we are to maximize the effectiveness of a campaign.

By applying these 5 tactics, you will only pay to talk to users who have real conversion potential!

 

Third party data

 

1. PREDICTIVE AUDIENCE: IDENTIFY SEGMENTS THAT REACT TO YOUR ADS

There are a lot of third party data providers out there right now. Some DSPs are connected to more than 30 providers, which represents tens of thousands of audience segments at our disposal. It can be difficult to navigate and identifying the best performing segments quickly becomes a challenge. Predictive audience consists of using an algorithm to test different segments based on predetermined objectives. One can focus optimization on clicks and CTR or on conversions and CPA. The algorithm identifies the best segments and increases their budget, while it reduces the expenses of the underperforming segments.

Take the example of a museum launching an exhibit of historical war photographs. The museum wants to reach customers in its region who will be interested in the theme of the exhibition. So we tell the system that this is an exhibition and that we want to maximize online ticket sales. The algorithm will identify a quantity of segments to test and adjust spending based on performance. In the end, the results can be surprising such as a strong reaction from the foodie segments  or jazz music lovers. We can generally observe a correlation between our target customers and segments that are not directly related to our campaign. With this new information, we can adjust the creatives and test new avenues related to the interests of our target.

2. THE LOOK-ALIKE AUDIENCE : FINDING USERS SIMILAR TO YOUR VISITORS  

Along the same lines, here's a second tactic for selecting third-party segments objectively. For the look-alike tactic , you first need to build an audience. This may be the general audience of our website or a more specific segment of our users. The system will then compare the selected audience to third-party segments and identify those for which there is a strong correlation. We can then isolate look-alike segments and target users with online behaviors that resemble those of our users.   

This type of strategy applies, among other things, to e-commerce type sites. In the case of the museum, we can segment visitors to our site by identifying those who have browsed our entire site, those who have seen the page describing the exhibition we want to promote and those who have purchased a ticket online after visiting the exhibition page. The ideal is always to build the look-alike audience from our users who generated a conversion, therefore who bought a ticket. The look-alike tool will identify user segments that behave similarly to our users and all you have to do is choose those you want to target.    

The look-alike modulator requires different prerequisites depending on the platform you are using. In Facebook Marketplace, one can create a look-alike segment from a few hundred cookies, while in some RTB platforms, the minimum required can be more than ten thousand cookies. Certainly, the larger the initial audience size, the more accurate the look-alike model will be .     

 

3. SEARCH REMARKETING: TARGETING USERS BASED ON THEIR ONLINE SEARCHES

Although this tactic contains the term "remarketing", it is all about new user acquisition since it is based solely on third-party data. Search remarketing consists of targeting users who have used different keywords in search engines such as Google or Yahoo, but also portals such as MSN, About, WikiHow, etc. The advertiser must therefore build a list of keywords and group them together in a similar way to an SEM campaign. Audiences can be segmented according to keyword categories and optimized for performance. This type of targeting is particularly effective in environments where search marketing is very competitive. This is an effective way to circumvent the high stakes driven by the competition. This targeting is also more subtle, as competitors may not know that we are targeting their users after the search. It is therefore possible to target the Internet users of the competition without necessarily buying their branded keywords and risking a bidding war that could harm you.

For the case of our exhibition, we can build a category of keywords related to photography, war, ideas for going out and museums in general. We will first launch the four categories of keywords, and after a few days, we can identify one or two categories that show more interest in our ads. At that time, we will adjust our budget to maximize our conversions.

 

Primary data ( First Party Data )

 

4. COOKIE MATCHING  : FIND YOUR CRM CUSTOMERS ONLINE 

Beyond the remarketing of users who have visited our website, we can also target users based on their email address or postal address. We do business with third party vendors for this type of tactic. Our suppliers have huge banks of cookies against which they compare the list we send them. Although we are not able to identify each of the users of our lists, we can create a considerable audience and improve the performance of a campaign.

Museums generally have a list of subscribers to their newsletter, and to this can be added lists of emails or postal addresses of people who participated in a contest during their last visit. Since not all subscribers will open the museum's emails and we know that the participants of a contest have already visited the museum, we will have created audiences with a high potential for conversion. You can build an audience from each of the lists and maximize spending on those that perform best.

It should be noted that email remarketing is currently available on the Facebook platform and that the functionality should be available in the Google Display Network in the coming year . It generally takes a fairly large bank of emails or addresses to launch a campaign of this type, since match rates vary between 30% and 50%. 

 

5. IP ADDRESS REMARKETING: EXPAND YOUR REMARKETING POOL

When a user visits our website, their IP address is recorded in a database. With the lists of IP addresses of our users, we can target all users connecting to the same network as visitors to our site. This is particularly useful for households that have more than one computer, and for so-called cross-device retargeting. We can thus adapt the message, depending on whether a user is connected to his network via a smart phone, a tablet or a computer.

For the museum, we must first create an audience of IP addresses of visitors who have seen the page dedicated to the new exhibition. We can hypothesize that people living in the same household as these visitors have a good chance of accompanying them, or simply of being recommended to visit the exhibition. It therefore makes sense to support this behavior by serving ads to these users. We can also create a retargeting of IP addresses from users who have visited the shopping cart page on our site. This audience will be smaller than the first, but will have a higher conversion potential.

 

The next thing…

 

With the proliferation of screens around us, we can only expect these targeting tactics to continue to evolve. The growth of Smart TVs is a good example of where we can start adapting TV ads to consumers' online habits. And that's not all! More and more cars are now connected online and the destination is often saved in the GPS. Why not adapt radio advertisements to the destination of the user in these cases? Even when we walk, smart phones and smart watches follow our movements and record our exchanges. In short, the era of Big Data is just beginning and advertisers who embark on this adventure today will have a definite advantage in the years to come.