"Keywords were once the best we had. Now, keyword-based targeting is fundamentally inaccurate - and it's time we admit it. In English-speaking markets, its flaws are easy to miss. Take it globally across multilingual Europe, Africa, Asia or the Middle East, and it breaks almost instantly. A phrase that feels empowering in English might sound sarcastic in Indonesian, for example. Humor doesn't always translate, and nuance disappears."
"The main issue with today's contextual advertising is its focus on a small part of the internet - mostly the English-speaking Western world. That approach ignores how meaning shifts across languages, cultures and even emotions. In many emerging markets, context isn't just linguistic; it's cultural and situational. Yet most contextual systems still rely on static keyword lists and fixed audience categories. They can't recognize these nuances."
Most contextual advertising still relies on keyword logic, often replacing single keywords with clusters rather than improving comprehension. Keyword-based targeting fails across multilingual and multicultural markets because meaning, tone and humour shift between languages and contexts. Current systems focus on the English-speaking Western internet and depend on static keyword lists and fixed audience categories that cannot capture cultural or situational nuance. Artificial intelligence can enable contextual solutions to read full pages, interpret structure, tone and sentiment, and allow advertisers to build flexible, nuanced targeting that reflects intent rather than isolated words. AI must address four long-standing limitations to succeed.
Read at AdExchanger
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