Whether you are a marketer or a publisher, you aim to attract your most relevant audience’s attention to your product. Fast. This requires an accurate understanding - from a pool of marketing data - of how people behave, what interests them and what engages them. Marketers often find audiences based on past performance, relying on the results from prior campaigns. It is easier said than done. Traditionally, this process took weeks, if not months. Today, Information overload is everywhere. By minutes, marketing data is growing in size and complexity. Adapting to these changes is especially challenging considering the staggering amount of “Big Data” marketers need to organize, understand and act on.
While there are machine learning techniques that can automatically glean rules from patterns found in data, most still require these rules to be manually processed and explicitly coded. These predefined rule-based AI solutions are difficult to implement on a large scale because they need to be updated constantly, or they can quickly become obsolete.
In recent years the conversation around Big Data has moved towards the speed of access to data and the complexity related to processing the masses of data once received. The use of modern artificial intelligence is an urgent necessity given the amount of data to be exploited or the depth of analytical issues to be interpreted.
We recognised this long ago and in response developed advanced AI methodologies to provide our clients with a competitive advantage in today’s world. Advertisers are looking for audience segments that will help them develop their acquisition strategy through display and video advertising, and this is exactly what AI is expected from the marketers to achieve.
This change has led us to refocus on artificial intelligence capabilities in order to implement a solution to deal with organic mass data in an extremely rapid manner. The advantage of AI that enables the automation of a variety of tasks including: automatically optimizing you audience segmentation , finding the highest-value customers (e.g. those most likely to convert), and exploring new leads that closely match your best customers. AI speeds up the decision-making process as it enables real time processing of large volumes of data to accurately (and continuously) predict consumer behavior.
In early 2017, we launched our Nielsen AI, our artificial intelligence technology. It was designed to learn - in real time - from the near-constant changes in consumer behavior across devices, media channels and purchase behavior.
This is a big leap beyond batch or offline learning in the marketing cloud industry. Batch-learning requires data to be modeled at a later time resulting in significant - delays. Batch-learning models have no ability to adapt to consumer shifts, which means marketers are missing customer opportunities, wasting impressions and potentially losing customers.
In 2017 it was recognized by R & D Magazine’s R&D 100 Awards - as one of the most technologically significant products of the year. The R&D 100 Awards has served as one of the most prestigious innovation awards program in research and development for the past 55 years, honoring great pioneers and their revolutionary ideas in science and technology.
Today’s marketing environment requires that marketers are able to make sense of vast amount of consumer data from multiple sources. In response to this demand, Nielsen AI, one of the main pillars of the Nielsen Marketing Cloud platform, was built with global enterprise audience scale and speed to market in mind. Our platform enables marketers to turn marketing data into actionable insights in people’s behaviour. This means you’ll be responding to the shift in consumer behavior, faster and smarter.