Blog Article
October 11, 2023
In a fast-changing digital world, marketers need transformative tools to maximize — and measure — profitability and Return on Investment (ROI). Machine Learning (ML) is increasingly pivotal in steering the course of advertising. Big Tech's success, from brand to performance to a blend of both, was made possible by their ability to develop and leverage advanced ML to drive measurable outcomes. And now, advanced ML is moving outside these Big Tech walled gardens, expanding its horizons into the vast open internet and unlocking new possibilities for advertisers.
Let's explore the applications of machine learning and how advertisers can take their performance to the next level.
Machine learning is everywhere, fueling the breakthrough experiences reshaping our daily lives — from the generative AI in ChatGPT to the recommendation engine in Amazon to the generative fill in Adobe Photoshop.
At its core, Machine learning (ML) operates as the processor, or “brain,” behind Artificial Intelligence (AI). AI is seen as the user experience (UX), designed and directed to perform narrow tasks, while ML is the engine that understands our needs and determines how to meet them.
We go even further with operational machine learning, a specialized subset of ML. It deploys models that make autonomous decisions, impacting the business in real time. Operational machine learning drives tangible outcomes with speed, scalability, and adaptability. When change is constant in advertising — whether it's user behavior, policies, or macroeconomic headwinds — systems need to adapt to these changes on the fly. That's where operational machine learning can unlock immense value.
For advertisers, leveraging ML takes more than understanding advanced technology; it's about activating and connecting the potential to tangible advertising outcomes. Done right, ML enables:
While the benefits of machine learning are clear, building an in-house ML solution is extremely hard for most organizations. It takes massive investment in terms of time, talent, and resources. That's why many marketers seek out dedicated ML-driven advertising platforms to deploy solutions quickly. However, advertisers need clear criteria to evaluate partners and solution providers based on their capabilities and fit with specific goals.
The burning question is, how do you cut through the buzz around ML and determine if a solution would be truly effective? Here are three key considerations to keep in mind:
At Moloco, operational machine learning is core in everything we do. Whether for a mobile app developer, a retail site, or a streaming platform, our vision remains the same: to harness the power of ML to drive growth and monetization for companies of all sizes. To date, we're serving customers in numerous businesses and verticals:
We've built our engine with a dedication to outcomes, and all of our solutions are predicated on the following:
Ready to evolve your advertising strategy with operational machine learning? Contact us to explore solutions.
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