Ivy Liu
• October 11, 2022 •
- 01 Key findings
- 02 The building blocks of personalization: In-house or vendor-supported?
- 03 Contextual customization is easier to execute, but falls short of the dream
- 04 Hyper-personalization provides precise targeting while presenting a privacy risk
- 05 Publishers skirt AI data privacy concerns by focusing on behavior
- 06 Publishers' largest use of NLP: Still chatbots
- 07 Social listening, voice-to-text translation and text enhancement use AI to accelerate workflows
- 08 Publishers largely outsource NLP application building, especially chatbots
- 09 Publishers face cost, tech and ethical challenges with AI adoption
This research is based on unique data collected from our proprietary audience of publisher, agency, brand and tech insiders. It’s available to Digiday+ members. More from the series →
This is the third part of a research series on the most popular emerging technologies. The series follows up on a report Digiday produced five years ago to discover how technologies previously reported on have evolved and to explore new technologies that have since emerged, including blockchain and robotics. In this segment, we look at how publishers are using the artificial intelligence tools of natural language processing and data-driven personalization.
Read Digiday’s 2023 report The State of AI: The paradigm shifts toward data for marketers.
