The way in which digital media is bought and sold has changed dramatically in recent years. The programmatic advertising ecosystem has gone from being an experimental technology, to being the epicenter of all decisions that are made in advertising transactions.
Artificial Intelligence (AI) and Machine Learning (ML) have begun appearing on the cover of and trending in almost all magazines, blogs and technological articles taking off as the most fashionable concept in the digital world where technological evolution is exponential. More specifically, these new concepts represent a revolution in the present and the near future in the world of advertising and marketing. AI allows machines to perform tasks with a high procedural and computational load so that people can be free to provide maximum added value in matters such as creativity or strategic management.
All this intelligence is key due to the boom, which is increasingly established, of programmatic advertising. And the new digital trends are placing the user as the axis of their actions, posing a new paradigm in the advertising market. To date, the great effect of branding and awareness offered by offline media hasn’t been interconnected, with the deep capacity for segmentation, interaction and measurement of digital media, especially the mobile medium. Little by little, we’re seeing the great value that mobile-centric strategies offer in order to interact with users in all phases of the purchase funnel, and through any media. These interactions are cross-media and cross-device, but are increasingly digital in nature. In turn, all this allows us to move from less effective mass-media communication (1 to N), to a more personalized one that impacts the user at the most appropriate time (1 to 1) reaching a communication or interaction that’s more effective and relevant.
In an ecosystem where personalization in communication begins to be key to optimizing the return on investment in media, these techniques allow us to know the context and mindset of users more accurately in order to increase relevance and usefulness of the message. We’ve evolved towards an expert system that, in real time, analyzes the probability that a user converts, buys or interacts with a brand or an advertisement based on a multitude of different data sources, among which is the location, the context, the demographic profile, or digital and behavioral interests, among others.
In Sonata (our proprietary DSP & DMP), thanks to having our own technology, we’ve evolved our processes of analysis and data processing, in order to build audience profiles and pre-bid systems with a greater degree of specialization depending on the concrete moment of the purchase process each user is in. We start from unsupervised models of machine learning (clustering) to later refine algorithms based on supervised machine learning models, where we include real data samples, as well as real advertising interactions for each vertical or category and, of course, all the brand’s research and knowledge of the user. It’s important to know how to incorporate and weigh other quality sources of certified, guaranteed external data so we can implement systems that allow us to identify low-quality or fraudulent inventory and advertising traffic. This is a key objective in order to minimize losses and optimize results in an environment, where fraud is increasingly complex and difficult to detect. Big Data analysis, AI and process automation allow us to refine and certify, with pinpoint accuracy, the signals and decisions we make when activating advertising and reaching consumers.
A key variable of immense value, both in carrying out the segmentation, activation and attribution of audiences at digital and offline levels, and in implementing mobile-centric strategies, is the location. To do this, Sonata has an audit and classification system for the location signals available in the advertising ecosystem called LQI (Location Quality Index). Thanks to artificial intelligence and the daily analysis of billions of pieces of data on a global scale, the expert system is able to discard all data of fraudulent origin or of low quality, taking into account not only the user's location, but also dozens of additional variables, such as advertising interactions (clicks, videos...), viewability, ad placement, origin and quality of the media, etc.
This has allowed us to continue innovating and developing different systems in the field of Geospatial Intelligence. This new evolution towards knowledge and the development of expert systems that make intelligent decisions based on the study of different data variables in the hyperlocal environment allows us to help brands, and especially retailers, make the most optimal decisions while increasing the ROI of their investments in advertising or marketing. You can know, in real time, which are the most compatible zones or areas in which to carry out an activation or communication depending on the audience, traffic, competition analysis or the arrangement of offline media such as OOH.
Artificial Intelligence not only helps us in the engineering of intelligent systems focused on decision-making when buying or serving advertising, or for the creation of more complex and accurate audience profiles, but it’s also key to the optimization of results and maximization of the KPIs and ROI of each strategy. Through the execution of Machine Learning models and algorithms that analyze millions of pieces of historical data, our platform evaluates and executes decisions in real time that allow us to optimize different variables at the same time, knowing and acting at each moment based on probabilities and forecasts of success or conversion. All this, in order to provide the best possible results to advertisers and provide the greatest utility and relevance to consumers who receive the content, which is increasingly adapted.
Artificial intelligence is here to continue to revolutionize industries such as advertising with the aim of optimizing results and reducing costs, both on the supply side and on the demand side. But it not only gives us a purely financial or statistical approach, consumers will increasingly benefit and will receive more and more personal, relevant and useful messages.
In short, Sonata, like the market, is evolving along with programmatic advertising trends so it can implement solutions and strategies beyond the borders between digital and offline. But it’s not about completing or unifying a vision about the media, it’s about concentrating the media around their natural link, the user. Being able to identify this user as the fundamental axis of any conversion or sale process, we began to abandon the language of advertising to make way for models oriented to real business objectives.