Real-Time Optimization: The Next Frontier of Performance Marketing

Introduction

In a world now reliant on digital marketing, marketers cannot wait for weekly reports, or post campaign analyses to make their advertising decisions. In a matter of seconds consumer behaviour changes, platforms roll-out new algorithms, and there will always be a competitor one click away. Enter Real Time Optimization powered by Artificial Intelligence.

Since Real Time Optimization allows marketers to have instant access to live data, they are able to analyse and make immediate adjustments to marketing campaigns, including traffic distribution, creative budgets, and other campaign variables without manual input. Real Time Optimisation is the transformation of the marketing process from reactive to predictive and proactive.

What is Real Time Optimisation?

Real Time Optimisation is the continuous use of machine learning models, predictive analytics, and automated decision engines in order to monitor user interactions on an ongoing basis and dynamically adjust marketing strategies while an advertising campaign is running. Typically, Advertising campaigns are set-up in a static manner, but with the advent of Real Time Optimisation, systems use live data to automatically take instant action in order to increase conversions, revenue, and return on investment.

In essence, the purpose of Real Time Optimisation is to combine Machine Learning Models, Predictive Analytics, and Automated Decision Engines to ensure that Brand X delivers the correct message, to the correct user, at the correct time.

How Real-Time Optimization is Transforming Performance Marketing

The Transformation of Performance Marketing with Real-Time Optimization

1. Intelligent Traffic Allocation and Budget Allocation
   AI systems are developed to detect which traffic sources perform well and automatically move budget to channels and publishers that generate the most conversions. As a result, wasted spend is removed, and every marketing dollar is optimized for maximum impact.
   
2. Dynamic Content/Creative Optimization
   Real-time algorithms can test different creatives, offers, and messaging for users based on their behavioral data and their intent. As a result, the personalization boosts engagement with users and significantly improves conversions.
   
3. Advanced Attribution and Funnel Optimization
   By following user journeys across devices and platforms, AI-powered optimization models are able to identify drop-off points and automatically adjust targeting, offer, or retargeting to recover lost conversions.
   
4. Fraud Detection/Traffic Quality Control
   Real-time monitoring is used to discover abnormal patterns, including bot traffic, fraudulent clicks or conversions, etc. AI models can instantly block suspicious activity protecting brands and publishers from wasted dollars and inaccurate reporting.

The Role of Real-Time Optimization in Social Commerce and Creator Economy

As commerce grows through the use of social platforms and creator-led channels, the need for real-time optimization increases significantly. The intent of users within social platforms evolves quickly, and therefore AI-based technology can connect products with creators and their intended audiences in real time; thus, maintaining relevancy and increasing purchase intent.

As a result, brands will be able to go beyond traditional “vanity” metrics to deliver measurable outcomes from commerce on social platforms. At the same time, creators will be able to access enhanced monetization opportunities by providing optimized product recommendations and delivering customized shopping experiences for their followers.

The next generation of marketing powered by AI

Real-time data optimization will serve not only as an efficiency tool but also as the foundation for today’s marketing landscape. With improvements in the sophistication of AI models, these systems will be able to predict consumer behavior, automate complete marketing strategies, and learn directly from each interaction with consumers.

The companies that are a part of the Admitad ecosystem are beginning to utilize both automation and AI-driven insights to assist their brand and publisher customers with growing through improved transparency and performance in an increasingly complex digital environment.