Nowadays, larger bid-phrases, in online advertising campaigns, represent a huge challenge (the so called “long tail challenge”) because there can be millions of combinations of keywords, resulting in less relevant matches (insufficient ROIs achieved). To understand the current challenge, the only possible way to optimize these online campaigns is mostly manual but digital advertising campaigns must manage massive data, impossible to cope effectively manually. This reduces the quality of targeting, the cross-platform Ads and Keyword Management and as a result, diminishes the marketing performance (ROIs: 1-3%). Our company has developed OrbitalAds, the first machine learning-based technology focused on automating Digital Marketing Campaigns to increase ROI of Advertisers. Basically, the implementation of OrbitalAds suppose the easy compilation of huge quantity of data and algorithms using machine learning and deep learning tasks are adjusted in real-time to improve business results (maximizing ROI). OrbitalAds creates, manages and optimizes thousands of ads automatically and in any language, saving time and money. It can be easily implemented being compatible with existing SEM management tools and it can find new terms that can be included as keywords into SEM strategies. The operational and financial feasibility assessment has allowed us to define the price policy and the investment needed to reach a go-to-market stage for OrbitalAds project. Online Advertising is a huge market (€ 230 bn in 2018) that keeps on growing at a frantic pace, hoping to reach € 297 bn by 2020 and hence growing at a Projected CAGR of 13.5%. In this context, OrbitalAds will play an essential role based on its potential to increase the online ROI of campaigns ROI and its improved advertising management versus the manual systems. We have evaluated under three economic perspectives our financial projections, considering different possible scenarios regarding our share of wallet and managed spent. Our OrbitalAds algorithms technology will be profitable even under the most pessimistic scenario we have analysed. The more realistic case will provide a ROI of 671% in 3 years. Hence, the positive feedback obtained from the feasibility study have encouraged us to apply for EC funding through Phase 2, which is aimed at completing the fine tuning of our tool and at the development of our SaaS model for the large-scale implementation of our technology.
