Israeli Content Marketing

Instructions

Israeli Media Landscape

Key outlets: Geektime (tech blog), Calcalist Tech (business+tech), The Marker (business), Globes (business), ynet Digital (general consumer tech, the section is ynet.co.il/digital, there is no /tech section), CTech (English). NoCamels has ceased operations: its About page states it was active from 2011 to 2024 and that operations are paused, and its last post is from October 2024. Do not pitch it. Israeli web traffic splits 48.76% mobile / 49.79% desktop (StatCounter, August 2026), so design for both screens, desktop now slightly leads and neither is a rounding error. Facebook groups are a major content discovery channel.

Hebrew SEO Content Strategy

Use Google Keyword Planner with Israel location. Check Google Trends Israel. URL slugs: transliterated Hebrew or English (avoid encoded Hebrew). Structure: break the page with an H2 roughly every 200-300 words and keep paragraphs to 2-3 sentences. These are editorial conventions for scannability, not ranking thresholds published by Google, so treat them as defaults to adapt rather than rules to enforce.

Hebrew Keyword Research

Hebrew keyword research is not English keyword research translated. The language behaves differently:

• Root-based morphology. Hebrew words are built from 3-4 letter roots. A single root generates many surface forms (verb conjugations, noun patterns, gendered and plural forms). Research the root family, not just one inflection, and cover the high-volume forms users actually type.
• Attached prefixes. The letters ב, ל, ה, ש, ו, מ, כ attach directly to the next word (בתל-אביב, לשיווק, השיווק). The same concept appears with and without a prefix. Account for both; do not treat "שיווק" and "השיווק" as unrelated.
• Ktiv male vs ktiv haser. Hebrew has two spelling conventions (full vs defective spelling), so the same word has variant spellings (for example מנהל vs מנהל with an extra yud). Users search both. Include the common variants.
• No capitalization. Hebrew has no upper/lower case, so brand names and proper nouns are not visually distinct. This removes one disambiguation signal; rely on context words instead.
• Nikud stripping. Almost nobody types vowel points (nikud). Strip nikud from keyword lists and target the unpointed forms.
• Final-letter (sofit) normalization. The letters כ/ך, מ/ם, נ/ן, פ/ף, צ/ץ are the same letter in final vs non-final position. Normalize sofit forms when comparing or deduplicating keyword variants.