Native Mobile Advertising
Mobile Advertising Watch is a leading technology media property dedicated to covering the rapidly evolving world of mobile advertising, reviewing new solutions, giving reliable and actionable tips and breaking important technology news.

ios-1091303_960_720The following is a guest contributed post to MAW from Israel Alverez, VP of technology for MobileFuse.

Every year, advertisers and various ad tech platforms gather more and more data about consumers, which, to date, has been largely used to inform how we target ads.

From the introduction of cookies and online retargeting, to the rise of mobile and leveraging location, to the latest push of uncovering more contextual data and layering findings into targeting, marketers have focused on taking a pre-existing message (designed by an agency) and using “big data” and machine learning to figure out who to send it to.

At the turn of the century, a popular concept took hold based on the confluence of computing power, large datasets and automated manufacturing: “Mass Customization.” The idea was to leverage these technologies in order to mass-produce goods that were still uniquely tailored to individual customers.

While we are just now starting to see mass customization in the hard goods sector, we in the mobile creative industry are in a unique position to exploit this notion. Rather than starting with a single message and finding ways to deliver it to people who may care about it, suppose we reverse the strategy? What if we start with the end recipient and then find ways to tailor the message in real time to that person based on the information we already have access to?

The truth is, we need to think about making a fundamental change in how we approach mobile creative. We should be using data to modularize ad units into something that functions in a completely new and different way. While we can all point to examples of the first step along this approach, we should be developing the tools and infrastructure to move much further down this path. The potential payoff of a finely-crafted, subtle and personally relevant message tailored to the recipient, not just in terms of space and time, but also in terms of individual history, is hard to overstate.

Until recently, creative units have been designed the same way for the last 50 years. Agencies work with their clients to create a campaign, write the copy, design the imagery, and then come up with a media plan that will deliver the desired kind of impressions. Whether on print, online, mobile or another medium, we’ve accepted this as the status quo, and haven’t really considered other options.

However, in the era of Big Data, the possibilities to change the status quo are practically endless. Rather than build a final product off the bat, we can create a shell that programmatically self-customizes in real time based on incoming signals. Even given a simple set of rules and signals, the range of customization available quickly becomes very refined and allows for narrow message targeting. This doesn’t just apply to standard dayparting, where different messages appear in the morning, afternoon and night; what if we could change the creative based on the specific moment in time as it relates to the particular end recipient?

So what does this mean from a tactical sense?

The first thing we’re seeing is a blending of jobs. Developers and designers are becoming one, as the creative team needs to be thinking about back-end code and making an ad malleable. Success in this area requires not just a combination of skillsets among traditional creative personnel – a merging of programming and design roles – it also necessitates collaboration with data science teams and possibly even input from psychoanalytical resources.

We’re also seeing a new combination of ad tech and more traditional marketing. If an ad unit can have many different messages and end results, the marketing team will need to ensure both teams are closing the loop and maximizing ROI depending an all the various scenarios in play. Additionally, these messages need to be tracked carefully, so that effective combinations can become the basis of future learnings. Establishing a feedback loop can deliver surprisingly large benefits in a short period of time.

For example, take an auto manufacturer advertising a new model of car. In the past, the advertising team would create the campaign, and while the marketing team may support the process to make sure the narrative and messaging fit into the core themes the company was pushing, that would basically be their role until the campaign was running and they then might help push out the content via social/email.

If the same unit was being created with this new, flexible style, the marketing team would need to be brought in much sooner. Let’s say the brand wanted to serve a different message to people who already own one of the cars, as opposed to those who don’t. In that case, the marketing team would step in much earlier, and would layer in the backend database of current owners to support the campaign. They could also look at responses to marketing emails (i.e. has a person clicked on a promotion in the past?), and use that to help create a campaign that would be tailored to those individual people, as one of the many different scenarios that could impact what the creative looks like.

The possibilities are almost endless when it comes to creating these customizable shells, and the best part is that all it really takes is a change in the way we think about setting up campaigns.

There is no denying the impact that the influx of data, and the shift to targeting moments, has made on the space, and the world of mobile creative is the next piece of the advertising puzzle that will soon change forever.

Leave a Reply