These will be the major Data Trends of 2016

Collection and analysis of users’ data are turning into essential tools for marketers dabbling into digital advertising. Indeed, it is through users’ data that brands and advertisers are efficiently reaching their desired audiences. Retargetly tells you which are major the data implementations that will be trending this year, and helps you understand each one of them.

• Real Time Optimization (RTO)

RTO is an tool that evaluates and analyses user’s data on a constant basis and allows to make informed decisions within seconds. The information it process and the insights it delivers are key for optimizing the progress of ongoing campaigns. RTO is also applied through an automatization process which distinguishes it from other optimization methods.

RTO is often mistaken with programmatic buying’s RTB or Real Time Bidding, though, both tools are completely different. RTB is the one making the purchase decision while RTO is the process that analyzes the moment before, during and after the purchase is done. This ensures that the bid placement is accurately informed, and therefore leads to outstanding results.

RTO processes users data along with contextual information about the ad inventory before the purchase is made. It also analyses behavioural data after the bid has been placed so as to optimize the following purchases that will be operated throughout the campaign. RTO also allows to optimize campaign’s targeting by identifying the segments with better performance, which eventually leads to obtaining better results. Finally, RTO can analyze budget information in real time, which ensure the bidding price is always optimum.

• Dynamic creative optimization (DCO)

Dynamic Creative Optimization (DCO) automatically optimizes creativities based on A/B testing. It allows advertisers to fuel an ad’s creative process with user’s data — in real time. This way, the advertiser can go beyond reaching the right user in the right moment by also delivering the most accurate message.

In order to create a DCO ad a template subject to different variations (typo, copy, image, etc.) must be created. Once this is done, each creativity it’s adapted based on the user’s data contained on each ad impression.

Through DCO’s implementation unique creativities can be produced instantly, guaranteeing that the most appropriate message is delivered for each impression and taking the message’s customization to a whole new level. By delivering a powerful connection with users, DCO is becoming a major data trend this year. Such a high-end customization is allowing marketers to maximize their campaign’s ROI.

• Location-based targeting or LBA

More and more users surf the web through their mobiles. Comscore estimates that mobile navigation — mainly in-app — represents 65% of total navigation time in the US. In the LatAm the trend is similar. According to a study conducted by GSMA, the region will account 450 million smartphone users by 2020.

Advertisers are adapting to this new navigation method, and are therefore readjusting their targeting capabilities, basing audience segmentation in geo location. A recent study published by IAB UK reveals that 66% of advertisers in the region believe that location based targeting is the most exciting opportunity of 2016.

The reasons explaining the popularity of this targeting tool are pretty obvious. First, it grants a more accurate customization of the served ad as it can be modified based on user’s location, creating a relevant connection between the target and the delivered message. When combined with programmatic buying location based targeting promises to boost campaigns results on an unprecedented level as its real time implementation allows marketers to optimize ongoing campaigns.

In the following years we will see the investment in LBA burst. According to a report by Berg Insight it should reach US $15 millions by 2018, representing 39% of total mobile spent.

• Look-alike segmentation

Look-alike segmentation identifies new consumers with a high engagement potential with advertisers’ brand or product. In order to implement this trending segmentation, common characteristics of the advertiser’s real audience have to be defined on a first instance. Then the new target is created based on users sharing similar aspects.

The original client’s profile is determined thanks to the data collected by a CRM platform, or thanks to the 1st party data compiled by a DMP. Later a match — user with similar profile — is found.

By implementing look-alike segmentation, marketers can expand the reach of their message as it allows them to serve ads to potential clients that share common interests with real consumers.

The State of The Industry survey conducted by Digiday and Exelate reveals that the number of agencies and advertisers turning into look-alike segmentation is considerably growing. More than half of surveyed marketers assure the results obtained through standard targeting can be multiplied by two or three when using look-alike.