AntiCon DialUp: How to power Netflix-level personalisation in your lifecycle marketing
Watch on-demand | Everyone knows Netflix has mastered personalisation. But how do they actually do it?
AI has made it easier than ever for marketers to produce high-quality content quicker, ensuring they can fulfil more requests and meet every demand. In fact, according to Forbes Advisor, 64% of business owners expect AI to increase productivity. But implementing AI to increase productivity and create more assets could backfire if you aren’t properly prepared.
With this increase in content production, you may find yourself swimming in a sea of images, videos and other digital assets — scattered across different storage systems or hard drives. While this cornucopia of content serves your every need, it’s no use if you can’t easily organise, find and distribute your digital assets with increasing efficiency.
Turn your content and creative teams into well-oiled machines by ensuring ensure you have a proper foundation in place — enhanced with AI technology — to connect teams, increase content ROI and stay on-brand at scale.
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Watch on-demand | Everyone knows Netflix has mastered personalisation. But how do they actually do it?
In this guide, we will explore the key components of effective sales enablement and efficient sales operations, and provide practical advice for those looking to implement a sales enablement strategy.
LXA's State of Data-Driven Marketing & Advertising Report looks at some key issues and trends around data-driven marketing.
Every enterprise AI transformation runs on two plans. The technology plan is funded, governed and owned. The talent plan rarely gets the same weight, even though it's the talent side that determines what the technology can actually deliver.
This report sets out how to close that gap: how to redefine your competency framework for two workforces rather than one; run a diagnostic that scores your team and AI side by side, task by task; govern agents as digital employees through the full employee lifecycle; and rebuild your academy around delivery modes suited to an AI era where content ages in months, not years.
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