RTB House Editorial Team

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The calendar year is full of marketing events that brands can ride like waves to elevate results. But the increased conversions that retail holidays inspire are more likely to be seen as largely expected rather than genuinely additive to growth. So, how can your brand’s digital marketing go from “expectations met” to “expectations exceeded” and leverage promo periods to a greater extent than competitors?

One way to do this is by outplanning your rivals. Because planning and preparedness is as important as having the right technology in place.

Performance marketing teams using Deep Learning and AI-powered optimization are seeing significant improvements in marketing conversion rates through greater campaign effectiveness. Here's how to increase conversion rates using the latest technology.

Generative AI applications are reshaping how organizations tackle marketing, product innovation, and user engagement. From generating new content to analyzing complex datasets, these advanced systems reduce repetitive tasks and unlock fresh perspectives. In this article, we explore key Generative AI examples and outline practical steps to deploy GenAI applications in different sectors, including marketing, healthcare, and finance.

Artificial intelligence (AI) tools are productivity game changers, but not every AI is suited for every type of task. Some excel at writing copy, others can generate incredible images, and some can help researchers predict the weather. Understanding different types of AI is the key to successfully implementing AI into your workflow. This article will dive into the differences between two of the most commonly used types of AI: Generative AI vs. Predictive AI.

Creating an effective customer targeting strategy is a challenge that marketers have consistently faced over the years. A dynamically changing market, evolving consumer behavior and preferences, and the rapid development of new technologies are factors that constantly create challenges. On the one hand, they require a continuous modification of the assumptions and developed strategies, and on the other hand, they open up completely new possibilities – i.e. allow for a better and more effective reach of the target group with the message. Why is it worth diversifying strategies and reaching for both contextual and behavioral targeting? What will the cookieless future bring?