The global ad industry is plagued by a big misconception at the moment: the idea that there’s a huge difference between buying and selling inventory programmatically on mobile versus desktop. But, according to Fyber’s co-founder and COO Janis Zech, and Erwin Plomp, Fyber’s VP of RTB (pictured below), the process, tools, and buying behaviours for programmatic on desktop and the mobile web are very similar – if not the same. It’s when you get to in-app versus desktop that there’s a real difference; and that’s where the biggest challenges and opportunities lie.

ExchangeWire: Buying inventory programmatically on mobile and on desktop – is there a difference?

Erwin Plomp: At a basic level, the programmatic buying process for inventory on the desktop and mobile web is the same. Advertisers choose their audiences, and how much they’re willing to pay to reach them, and media agencies create plans that target those audiences across desktop and mobile web properties.

In both cases, the DSP or trading desk bids on a per-impression basis on behalf of the advertiser, and an SSP – whether it’s desktop, mobile or cross-platform – offers up the inventory to the highest bidder. There’s no real difference when it comes to buying inventory like this.

Then why exactly does the misconception that programmatic mobile and desktop buying are different, still perpetuate?

Erwin: The process changes when it comes to buying in-app inventory versus mobile web or desktop inventory. That’s where the distinction is; and it’s an important concept to grasp because much of the growth in programmatic mobile is coming from apps.

Why is in-app so different to this world?

Erwin: It comes down to the data. Programmatic buying is driven by data, and on the desktop and mobile web, that data is currently delivered via cookies. Cookies are what give an advertiser the ability to identify that a unique visitor to their website is interesting, for whatever purpose, and then retarget them with a relevant message when they visit another site on their mobile browser.

With mobile apps, user data is provided through unique device identifiers – not cookies. These Apple IDFA and Google Ad IDs, specifically, can provide data like user location, device type, and the number of times an ad has been viewed within an app. But because the data is different, some of the programmatic trading platforms currently aren’t equipped to transact and target on a mobile-ad-ID basis, and that lack of data makes it more challenging to incorporate in-app inventory into a media plan.

What are the biggest barriers to advertisers looking to break into the in-app market?

Janis Zech: First, we need to make a distinction between different categories of advertisers. Performance advertisers, and mobile developers promoting their own apps, are already quite successful when it comes to in-app advertising. They know how to target mobile users effectively, as they’ve created large proprietary data pools themselves over the years, and are often experts at figuring out precise user acquisition costs. In the case of giants like Supercell, MZ, and King, these campaigns come with multi-million dollar budgets.

Brand advertisers are the ones that need different insight into who they’re reaching and when, and the limited visibility into the data behind mobile ad impressions is what’s currently hindering some of their success with programmatic mobile. In general, there is no shortage of valuable data assets available, but less clarity in how to apply them towards effective audience targeting, measurement and attribution.

As an industry, we’re working to solve this technical challenge; but, generally, the level of audience data and targeting for mobile in-app is still nascent. And that’s why you have reports that show that one out of every five advertisers isn’t sure whether mobile programmatic is effective.

How should advertisers go about budgeting desktop versus mobile versus in-app spend? Where are mistakes being made?

Janis: We’ve all seen the reports of the continuous increase in time spent with mobile apps, and that time comes at the expense of other mediums. In the US, for example, people spend an average of 3.3 hours with their apps every day. That’s more than the 2.8 hours they spend watching TV – meaning mobile apps have now eclipsed what previously was the most engaging and expensive way to consume content.

Depending on the audience, advertisers (and media agencies) that aren’t including in-app inventory in their plans are missing out on a huge opportunity.

Budget allocations obviously depend very much on the campaign objectives and channel performance; so there’s no set percentage or amount of spend that will work for every advertiser. But think about this fact: traditional media companies are seeing between 60-80% of their traffic coming from mobile, but only monetising a fraction of that revenue. That means even small increases in advertiser investment can have a major impact.

Once advertisers are able to leverage the strong data points that mobile publishers actually can provide – such as location, interest, and device type – they will definitely move towards programmatic buying across all screens.

And, while the mobile data ecosystem is still nascent, it is developing fast. There are a growing number of DSPs integrated with in-app-specific DMPs to empower advertisers to reach their audiences. The biggest mistake advertisers can make would be to not actively test, learn, and iterate on reaching users when they’re in apps.