How did the idea for Simplaex come about?
You might call it destiny. Moti (Co-founder/CTO) and I met in an Ad Tech company in Berlin late 2014. He joined as CTO, and I was hired as a trouble-shooter by the advisory board. We both felt that the market would soon make another turn and thus we were challenging the company’s status and future prospects. We decided to talk to all of the company’s clients (advertisers) and were strengthened in our belief that digital advertising would fully center around the extent in which audiences can be precisely and correctly classified from both ends of the advertising supply chain. It took us an hour to convince the shareholders and before we knew it, we found ourselves in a large transformation phase as founders of a new company.
Tell us more about Wallace, your Artificial Intelligence officer.
Today, four years after we started, we have come to a point where AI is no longer part of our value proposition. It has become our value proposition. Therefore we decided to give “him” a name: Wallace.
Analogous to a human brain, Wallace acts like a central nervous system that consumes information for a large number of sensory organs, i.e. supervised and unsupervised ML-algorithms. In order to take effective real-time decisions, this Bayesian-based core makes optimal autonomous actions to adapt to changes in significant factors governing the demand and supply in the advertising market.
At the same time, it keeps up to speed with dynamically evolving user behavior, constantly updating user valuation while minimizing exploration costs.
How can Simplaex help advertisers increase ROMI?
The platform is designed to give advertisers full transparency on where and when the ads are being served to the audience that is most relevant to their advertising objectives. The powerful AI classifies existing and potential users based on multiple data points and accordingly builds an understanding of their preferences and behavior. Based on the user’s interaction with the Ad and beyond (e.g. usage of the App), predictive bidding is applied to target only the most receptive audiences. This results in a highly effective media investment with maximum return.
How does Simplaex help advertisers as well as publishers?
At Simplaex, we have a fundamental belief that advertising works best when all parties win; the advertiser, the publisher and, of course, the consumer. In parallel, the supporting technology must assist advertisers and publishers by providing both with consistent audience insight, act media independent and offer full transparency.
This summer, Simplaex will be the first to launch such technology, enabling the supply side to sell the same way that programmatic buyers want to buy. As ads move through the programmatic supply chain, the new product aligns the ROI interests of the demand and supply side by creating a unified insight in understanding and valuing consumer behavior. It is the first of its kind to align the interests of the two sides of the ecosystem, and empowers them to step beyond the control of the walled gardens.
What, according to you, are the biggest challenges that digital advertisers are facing in 2018?
In my view, advertisers will have to make a strategic choice this year about to what extent they will remain depended on Google and Facebook. The duopoly forces advertisers to pay and play by their rules for as long as viable alternatives remain absent. Yet, advertisers should not underestimate their own influence. After all, they own the wallet in this industry. And as such, they have the power to change the status quo. The open programmatic ecosystem provides them with numerous opportunities to regain a healthy marketing/channel-mix. As always, any change comes with challenges, such as selecting the right technology or product whilst ensuring transparency, efficiency and ROI. In the end, it is all about advertisers moving closer to their most valuable partners, the publishers, with a technology layer that is as thin and transparent as possible.
How does Simplaex enable in-app retargeting?
Since we serve different verticals and clients with different business models, we apply different strategies and algorithms to maximize ROAS . What all campaigns have in common is how Simplaex’s AI is evaluating the existing user base and their in-app behavior according to the lifecycle of the app. After a short period of in-app evaluation, audiences are classified according to the advertising objectives. The AI engine is then setting up its initial bidding parameters and tracks the interaction between the Ad and the targeted audience. What follows is a continuous AI-driven optimization to identify the most receptive audience and to serve this audience the highest converting ads across the highest converting publishers, and all within the bandwidth of what the advertiser is willing to pay per engagement.
Simplaex recently announced that they were GDPR compliant, but with keeping in mind the recent Facebook data breach, do you think AI companies are more vulnerable to data threats?
At Simplaex, we had the advantage that the German regulations were already as strict as the forthcoming European GDPR. Therefore, the design of our platform and the way we have built our algorithms already considered all of the requirements that will become effective by May 25th. As for AI companies in general, like all data-driven companies, they will face their own specific challenges. After all, Artificial Intelligence and the protection of personal data are intertwined. For instance, Article 5 of the GDPR lists the principles relating to processing of personal data. It namely holds that the personal data must be processed in a transparent manner in relation to the data subject. But how can Artificial Intelligence ensure transparency for the users? This, and many more issues, such as the limitation of the amount of data which can be legally processed, will need to be addressed in the design of the AI product. And for many AI companies this will be a very challenging job.
Could you tell us about a standout digital campaign of yours?
I would like to refer to our first successful programmatic campaign shortly after we started. Not many companies at that time had much experience with app retargeting. During our stay in San Francisco, we met the team of Kabam and they were willing to give it a go with one of their Marvel games. We already had some success with earlier campaigns, but never could test our algorithms at such a large scale. Armed with a precise understanding of their players and their in-game behavior, we were able to predict the likelihood of players returning to the game at various game levels. The results were beyond our customer’s expectation in terms of how many players reengaged versus the net media spend. We ourselves were thrilled that our algorithms could pass the biggest stress-test thus far.
Originally Published on AIthority