Originally published on MindNews.fr on June 26, 2020.
By Pierre Chappaz, Executive Chairman, Teads
For advertising to start again, the economy has to reopen, and brands that begin investing again must see immediate positive results. This is what will restore their confidence and create a ripple effect.
Among the countries that have best controlled the pandemic, the economy is picking up quickly, as is advertising. We can cite Germany, Switzerland, Japan, Singapore, Hong-Kong, and Korea, where our media platform recorded revenue growth in June. In the US, after a deep dip at the beginning of the quarter, things are improving quickly, despite the still active epidemic situation in several states, and the civil unrest.
With the crisis, brands will favor performance
But this will not be enough. For the advertising market to return to sustainable growth, it must be understood that the behavior of advertisers has changed: they want to buy guaranteed outcomes.
This expectation of brands is certainly not new, but it will clearly accelerate.
The programmatic market – which suffered a lot with the crisis – still works on the CPM model. When an advertiser buys on a CPM basis, they are the ones who are shouldering the risk of whether that ad spend will convert into business. Hence their legitimate concerns: will my advert be visible? Will my video be seen and for how long? Will clicks generate real visits, new prospects, engagement, leads and sales?
So many concerns which the model of purchase on a CPM basis does not answer.
What we are seeing with this crisis is the sharp rise in purchases based on guaranteed-outcome billing methods: CPCV (Cost Per Completed View), CPiV (Cost Per Incremental Visitor), and CPA (Cost Per Action, including leads and transactions).
“More and more brands are asking us to use their CRM data to feed our AI. This is a sign of a change in practices”
If advertisers want to buy on a guaranteed outcome basis, it is because technology allows it, thanks to the combination of data and machine learning. A combination that delivers its potential provided you have a massive volume of data available. Our interest graph, based on the semantic analysis of media articles from publishers that take part in our platform, determines the interest of 1.5 billion people worldwide, including 85% of American internet users. The role of machine learning is then to automatically find the right combinations of data, which will allow the advertiser to target the right people and reach the desired KPIs.
It is also significant that more and more brands are asking us to use their CRM data to feed our AI. It is a sign of a change in practices.
Premium publishers have an advantage: The quality of the context
Publishers have the privilege of the quality of their content versus the FAANG. This captivates the reader’s attention, and translates into excellent visibility of the advertisements placed at the heart of the articles. When it comes to monetizing this content produced by journalists, our outcome-oriented billing technology leverages this high quality context and delivers their full potential.
The wealth of professional editorial content also allows a precise understanding of the reader’s interests, offering contextual advertising targeting possibilities in cookieless environments.
The effectiveness of in-article placements, combined with data and machine learning technology, is second to none. In a Marketing Week interview, Mark Pritchard, Chief Brand Officer of P&G, indicated that they measured an average duration of 1.7 seconds in view for his group’s video advertising placed in the newsfeed of a large social network. The figure is much higher when ads are placed in quality media environments: the average in-view time is 11.6 seconds for the videos inserted in articles on our media platform, a duration measured by Moat.
Premium publishers are therefore well placed to meet the new expectations of advertisers. Let’s change our culture and business model, and adopt outcome-based billing models!
