Artificial intelligence meets the world of digital advertising

ML cube, spin-off of the Politecnico di Milano and innovative startup that provides cutting-edge artificial intelligence solutions, launches AD cube, a platform for multi-channel optimization of online advertising campaigns that supports advertisers in defining the target to be reached, the budget to be used and its distribution.

The universe of digital advertising is constantly growing but there are still many problems to be solved. For example, still only 22% of companies are satisfied with conversion rates (Source: Econsultancy) and 57% of merketer (Source: Forrester) do not have the tools to make relevant decisions. Thanks to the artificial intelligence of AD cube, advertisers will have 360 ​​° support and will be able to manage a mix of campaigns on multiple channels (Google, Facebook, Instagram, Tik Tok, etc.) within the same platform. All this translates into time savings and, above all, greater efficiency. This is also confirmed by the data of the first applications on a group of 10 early adopters Italians and internationals, which have seen their ROI grow by + 30% and gained over + 40% in terms of time.

One of the great problems of advertising campaign management concerns the very high number of tasks it requires, especially when there are many campaigns. Precisely for this reason AD cube is based on AI algorithms, developed by the ML cube team, which every day they analyze the data and set the changes for an optimal result on every single platform. Simply create the new project, add your campaigns from all activated channels and AD cube will do the rest.

The new product of the Milanese start-up consists of three modules: SpendOpt, BudOpt and TargOpt. SpendOpt it’s aboutoptimization of the spending plan and answers the question: “how much should I invest?”. This module predicts the performance of campaigns in terms of revenues and ROI and provides an output in predictive curves that suggest to advertisers how much to invest to reach a certain goal, eliminating the problem of the Revenue / ROI trade-off. BudOpt, based on Machine Learning algorithms, concerns instead thebudget allocation and answers the question “how should I distribute the budget?”. This module distributes the budget daily between the different campaigns thus maximizing the returns or ROI. All this while always allowing the advertiser to set limits and customize the budget. TargetOpt instead, it harnesses the power of artificial intelligence algorithms for capture target segments that traditional data analysis fails to reach and answers the question: “what is the right target?”. The module processes the historical data of already existing campaigns in the background and returns a new set of campaigns when it identifies a promising segment. TargOpt can also automatically create new audiences for each platform.

«Artificial intelligence has all the potential to revolutionize our everyday life, especially in business models and digital advertising – declared Nicola Caporaso CEO of ML cube. With AD cube we provide advertisers with a unique tool, a workmate who will make every single phase of the advertising campaign simpler and more effective and will allow them to achieve the objectives of awareness, traffic and conversions set. We are proud that our project has already met the interest of some tech giants: it is the demonstration that we are on the right path. Now we want to continue to grow and play a key role by creating innovative and reliable AI tools with high and long-lasting performance. For this we are working on some new features such as attribution models, offline channel optimization, real-time bidding and creativity optimization. We are convinced that artificial intelligence represents the future and we want to make it available to our customers to develop their core business. ”

AD cube is not the only product made by the PoliMi spin-off. ML cube, in fact, is about to launch its flagship product, which takes the name of the start-up and is called ML cube Platform – a platform that is part of the “AI for AI” solutions, a trend that has been making a name for itself on a global level in the last period. The platform optimizes the life cycle of Machine Learning models already in production on different application domains, providing monitoring, analysis of performance, maintenance management (re-training, adaptation, decomissioning), the governance and the reporting for the cost management. Finally, ML cube is working on PriceIt, a dynamic price optimization system for e-commerce. With this platform it will be possible to optimize the pricing in a completely automatic way for e-commerce with different business models.

Source: RSS Innovazione by

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