{"id":21468,"date":"2026-06-08T11:14:21","date_gmt":"2026-06-08T09:14:21","guid":{"rendered":"https:\/\/www.dase-analytics.com\/blog\/?p=21468\/"},"modified":"2026-06-08T11:14:21","modified_gmt":"2026-06-08T09:14:21","slug":"preco-sa-data-nezhoduju-a-ake-je-riesenie-meta-vs-ga4","status":"publish","type":"post","link":"https:\/\/www.dase-analytics.com\/blog\/sk\/preco-sa-data-nezhoduju-a-ake-je-riesenie-meta-vs-ga4\/","title":{"rendered":"Pre\u010do sa d\u00e1ta nezhoduj\u00fa a ak\u00e9 je rie\u0161enie: Meta vs. GA4"},"content":{"rendered":"

Ak sa akt\u00edvne venujete marketingu, ur\u010dite ste sa stretli so situ\u00e1ciou, kedy vid\u00edte stovky kliknut\u00ed v Meta, no v GA4 sa k danej kampani prip\u00ed\u0161e len zlomok rel\u00e1ci\u00ed.<\/strong><\/span><\/p>\n

Je prirodzen\u00e9 p\u00fdta\u0165 sa, \u010di m\u00e1te zle nastaven\u00e9 meranie, alebo \u010di niektor\u00e1 z platforiem klame. 😬\u00a0<\/span>Pravda je v\u0161ak tak\u00e1, \u017ee tento rozdiel nie je chyba, ale o\u010dak\u00e1van\u00fd v\u00fdsledok.<\/span><\/p>\n

Meta<\/strong> a Google Analytics 4<\/strong> s\u00fa dva samostatn\u00e9 syst\u00e9my s odli\u0161nou logikou merania.<\/strong> Ka\u017ed\u00e1 platforma sleduje interakcie, pripisuje konverzie a nar\u00e1ba s d\u00e1tami pod\u013ea vlastn\u00fdch pravidiel. Cie\u013eom tohto \u010dl\u00e1nku nie je n\u00e1js\u0165 sp\u00f4sob, ako tieto \u010d\u00edsla nasilu zos\u00faladi\u0165.<\/strong><\/span><\/p>\n

Cie\u013eom je pochopi\u0165, pre\u010do sa l\u00ed\u0161ia, predstavi\u0165 praktick\u00e9 kroky na zmiernenie nezrovnalost\u00ed<\/strong> a na\u010drtn\u00fa\u0165 strategick\u00e9 rie\u0161enie pre z\u00edskanie jednotn\u00e9ho poh\u013eadu na v\u00fdkonnos\u0165 marketingu.<\/span><\/p>\n

Pre\u010do sa \u010d\u00edsla nikdy nebud\u00fa zhodova\u0165: Hlavn\u00e9 pr\u00ed\u010diny<\/b><\/h2>\n

Rozdiely v d\u00e1tach pramenia z viacer\u00fdch k\u013e\u00fa\u010dov\u00fdch oblast\u00ed. Aj ke\u010f sa va\u0161e meracie k\u00f3dy sp\u00fa\u0161\u0165aj\u00fa na z\u00e1klade identick\u00fdch udalost\u00ed, nasleduj\u00face faktory sp\u00f4sobuj\u00fa nevyhnutn\u00e9 odch\u00fdlky.<\/strong> Pre lep\u0161iu preh\u013eadnos\u0165 sme ich zoskupili do troch kateg\u00f3ri\u00ed:<\/span><\/p>\n

1. Metodologick\u00e9 rozdiely: In\u00fd poh\u013ead na svet<\/b><\/h3>\n

Z\u00e1kladn\u00fd d\u00f4vod nezrovnalost\u00ed spo\u010d\u00edva v tom, \u017ee ka\u017ed\u00e1 platforma meria \u00faspech inak. Definuje vlastn\u00e9 metriky a pravidl\u00e1, ako priradi\u0165 z\u00e1sluhu za konverziu.<\/span><\/p>\n

Odli\u0161n\u00e9 atribu\u010dn\u00e9 modely<\/b><\/h4>\n

Atribu\u010dn\u00fd model ur\u010duje, ktor\u00fd marketingov\u00fd kan\u00e1l z\u00edska z\u00e1sluhu za konverziu. Meta \u0161tandardne pou\u017e\u00edva model zalo\u017een\u00fd na poslednom dotyku v r\u00e1mci svojho ekosyst\u00e9mu s oknom <\/span>7 dn\u00ed od kliknutia a 1 de\u0148 od zobrazenia<\/b>.<\/span><\/p>\n

Ak pou\u017e\u00edvate\u013e videl reklamu na Instagrame a nesk\u00f4r klikol na reklamu na Facebooku a konvertoval, Facebook si prip\u00ed\u0161e pln\u00fa z\u00e1sluhu za konverziu. Naopak, Google Analytics 4 \u0161tandardne vyu\u017e\u00edva <\/span>d\u00e1tovo riaden\u00fd atribu\u010dn\u00fd model<\/b> s 90 d\u0148ov\u00fdm oknom, ktor\u00fd pomocou strojov\u00e9ho u\u010denia rozde\u013euje z\u00e1sluhu medzi v\u0161etky kan\u00e1ly na ceste z\u00e1kazn\u00edka.<\/span><\/span><\/p>\n

Pr\u00edklad:<\/b> Pou\u017e\u00edvate\u013e klikne na Meta reklamu, o dva dni nesk\u00f4r pr\u00edde na web cez organick\u00e9 vyh\u013ead\u00e1vanie a na tret\u00ed de\u0148 konvertuje cez emailov\u00fd newsletter. Meta si prip\u00ed\u0161e 100 % z\u00e1sluhy. GA4 v d\u00e1tovo riadenom modeli rozdel\u00ed z\u00e1sluhu medzi Meta kampa\u0148, organick\u00e9 vyh\u013ead\u00e1vanie a email.<\/span><\/p>\n

Kliknutia verzus rel\u00e1cie<\/b><\/h4>\n

Toto je jeden z naj\u010dastej\u0161\u00edch<\/strong> zdrojov zm\u00e4tku.<\/span><\/p>\n

Meta po\u010d\u00edta <\/span>kliknutia na reklamu<\/b>, \u010do je akcia, ktor\u00e1 sa udeje v jej ekosyst\u00e9me. Ka\u017ed\u00e9 kliknutie sa zapo\u010d\u00edta, aj ke\u010f pou\u017e\u00edvate\u013e okam\u017eite zavrie okno alebo sa str\u00e1nka nena\u010d\u00edta. GA4 na druhej strane meria <\/span>rel\u00e1cie<\/b>, ktor\u00e9 sa za\u010d\u00ednaj\u00fa a\u017e po \u00faspe\u0161nom na\u010d\u00edtan\u00ed webovej str\u00e1nky a spusten\u00ed meracieho k\u00f3du. D\u00e1ta z praxe \u010dasto ukazuj\u00fa dramatick\u00fd rozdiel:<\/strong> Meta Ads m\u00f4\u017ee reportova\u0165 3 248 kliknut\u00ed, zatia\u013e \u010do GA4 k tej istej kampani prirad\u00ed len 1 691 rel\u00e1ci\u00ed.<\/span><\/p>\n

Reportovanie viden\u00fdch konverzi\u00ed (View-through)<\/b><\/h4>\n

Meta do svojich reportov \u0161tandardne zah\u0155\u0148a konverzie od pou\u017e\u00edvate\u013eov, ktor\u00ed reklamu iba videli, neklikli na \u0148u, no nesk\u00f4r konvertovali inou cestou. GA4 sa prim\u00e1rne zameriava na interakcie zalo\u017een\u00e9 na kliknutiach<\/strong> a viden\u00e9 konverzie z platforiem mimo Google ekosyst\u00e9mu do atrib\u00facie nezah\u0155\u0148a.<\/span><\/p>\n

2. Technick\u00e9 faktory: D\u00e1ta straten\u00e9 cestou<\/b><\/h2>\n

Medzi kliknut\u00edm na reklamu a zaznamenan\u00edm rel\u00e1cie v GA4 stoj\u00ed mnoho technick\u00fdch prek\u00e1\u017eok<\/strong>, ktor\u00e9 sp\u00f4sobuj\u00fa stratu d\u00e1t.<\/span><\/p>\n

Sledovanie naprie\u010d zariadeniami<\/b><\/h4>\n

Meta exceluje v sp\u00e1jan\u00ed aktivity jedn\u00e9ho pou\u017e\u00edvate\u013ea na viacer\u00fdch zariadeniach v\u010faka <\/span>prihl\u00e1sen\u00fdm pou\u017e\u00edvate\u013eom<\/b> vo svojom ekosyst\u00e9me. Ak niekto vid\u00ed reklamu na mobile a nak\u00fapi na po\u010d\u00edta\u010di, Meta to dok\u00e1\u017ee spoji\u0165. GA4 sa spolieha na kombin\u00e1ciu met\u00f3d ako Google Signals a User ID, no ak pou\u017e\u00edvate\u013e nie je prihl\u00e1sen\u00fd do Google \u00fa\u010dtu, jeho cesta m\u00f4\u017ee by\u0165 fragmentovan\u00e1 a konverzia nespr\u00e1vne priraden\u00e1.<\/strong><\/span><\/span><\/p>\n

Blok\u00e1tory a nastavenia s\u00fakromia<\/b><\/h4>\n

N\u00e1stroje ako AdBlock alebo funkcie prehliada\u010dov (napr\u00edklad Intelligent Tracking Prevention v Safari) akt\u00edvne br\u00e1nia sp\u00fa\u0161\u0165aniu merac\u00edch skriptov.<\/strong> Ak sa k\u00f3d GA4 nespust\u00ed, rel\u00e1cia sa nezaznamen\u00e1, zatia\u013e \u010do Meta u\u017e svoje kliknutie zapo\u010d\u00edtala.<\/span><\/span><\/p>\n

Strata UTM parametrov<\/b><\/h4>\n

Pre spr\u00e1vnu atrib\u00faciu v GA4 s\u00fa k\u013e\u00fa\u010dov\u00e9 UTM parametre v URL adrese.<\/strong> Niektor\u00e9 prehliada\u010de, emailov\u00e9 klienty alebo samotn\u00ed pou\u017e\u00edvatelia m\u00f4\u017eu tieto parametre z URL odstr\u00e1ni\u0165. V takom pr\u00edpade GA4 nedok\u00e1\u017ee priradi\u0165 rel\u00e1ciu spr\u00e1vnej kampani a \u010dasto ju zarad\u00ed pod zdroj direct.<\/strong><\/span><\/span><\/p>\n

Filtrovanie nechcenej n\u00e1v\u0161tevnosti<\/b><\/h4>\n

Ka\u017ed\u00e1 platforma pou\u017e\u00edva vlastn\u00e9 algoritmy na identifik\u00e1ciu a odfiltrovanie aktivity botov<\/strong> a in\u00e9ho nechcen\u00e9ho trafficu.<\/strong> Ke\u010f\u017ee s\u00fa tieto mechanizmy odli\u0161n\u00e9, fin\u00e1lny po\u010det „\u010dist\u00fdch“ interakci\u00ed sa bude l\u00ed\u0161i\u0165.<\/span><\/p>\n

3. Nastavenia a spracovanie d\u00e1t: \u00dapravy v z\u00e1kulis\u00ed<\/b><\/h3>\n

Nakoniec, aj ke\u010f d\u00e1ta dorazia do oboch syst\u00e9mov, ka\u017ed\u00e1 platforma ich m\u00f4\u017ee spracova\u0165 a zobrazi\u0165 inak.<\/span><\/p>\n

Vzorkovanie d\u00e1t v GA4<\/b><\/h4>\n

Pri komplexn\u00fdch reportoch s ve\u013ek\u00fdm mno\u017estvom d\u00e1t m\u00f4\u017ee bezplatn\u00e1 verzia GA4 aplikova\u0165 <\/span>vzorkovanie<\/b>. Report potom nie je vytvoren\u00fd zo 100 % d\u00e1t, ale len z men\u0161ej vzorky<\/strong> a v\u00fdsledn\u00e9 \u010d\u00edsla s\u00fa aproximovan\u00e9. Reporty v Meta Ads s\u00fa vo v\u0161eobecnosti nesamplovan\u00e9.<\/strong><\/span><\/span><\/p>\n

Blended reporting identity v GA4<\/b><\/h4>\n

Pou\u017e\u00edvanie tzv. \u201eblended reporting identity\u201c, ktor\u00e1 kombinuje viacero identifik\u00e1torov pou\u017e\u00edvate\u013ea<\/strong> (User-ID, Google Signals a device-based identifik\u00e1tory). Ak nie je k dispoz\u00edcii jednozna\u010dn\u00fd identifik\u00e1tor, GA4 vyu\u017e\u00edva modelovanie na dopo\u010d\u00edtanie pou\u017e\u00edvate\u013eov a konverzi\u00ed naprie\u010d zariadeniami.<\/span><\/span><\/p>\n

To znamen\u00e1, \u017ee \u010das\u0165 d\u00e1t nie je priamo nameran\u00e1,<\/strong> ale dopo\u010d\u00edtan\u00e1 na z\u00e1klade pravdepodobnostn\u00fdch modelov. Meta Ads naopak pracuje prim\u00e1rne s deterministick\u00fdmi d\u00e1tami zo svojej platformy (prihl\u00e1sen\u00ed pou\u017e\u00edvatelia).<\/span><\/span><\/p>\n

R\u00f4zne \u010dasov\u00e9 p\u00e1sma<\/b><\/h4>\n

\u00a0Jednoduch\u00e1, no \u010dasto prehliadan\u00e1 pr\u00ed\u010dina. Ak m\u00e1te v \u00fa\u010dtoch Meta Ads a Google Analytics 4 nastaven\u00e9 odli\u0161n\u00e9 \u010dasov\u00e9 p\u00e1sma,<\/strong> konverzie, ktor\u00e9 nastan\u00fa okolo polnoci, m\u00f4\u017eu by\u0165 prip\u00edsan\u00e9 k rozdielnym d\u0148om.<\/strong><\/span><\/p>\n

\u010co m\u00f4\u017eete urobi\u0165 hne\u010f teraz?<\/b><\/h2>\n

Hoci dokonal\u00e1 zhoda je nedosiahnute\u013en\u00e1,<\/strong> nieko\u013ek\u00fdmi praktick\u00fdmi krokmi m\u00f4\u017eete zmierni\u0165 nezrovnalosti a z\u00edska\u0165 jasnej\u0161\u00ed poh\u013ead na d\u00e1ta.<\/span><\/p>\n

    \n
  1. Zjedno\u0165te z\u00e1kladn\u00e9 nastavenia<\/b>
    \n<\/b>Skontrolujte \u010dasov\u00e9 p\u00e1sma, menu a d\u00e1tov\u00e9 filtre. Aj mal\u00e9 rozdiely m\u00f4\u017eu skresli\u0165 denn\u00e9 reporty.<\/span><\/span><\/span><\/li>\n
  2. Majte pod kontrolou meranie<\/b>
    \n<\/b>Overte spr\u00e1vne sp\u00fa\u0161\u0165anie eventov, eliminujte duplicity a r\u00e1tajte so stratou d\u00e1t kv\u00f4li consent mode \u010di adblockom.<\/span><\/span><\/span><\/li>\n
  3. Bu\u010fte d\u00f4sledn\u00ed s UTM parametrami<\/b>
    \n<\/b>Nastavte jasn\u00fa \u0161trukt\u00faru a pravidelne kontrolujte, \u010di sa parametre nestr\u00e1caj\u00fa alebo neprepisuj\u00fa.<\/span><\/span><\/span><\/li>\n
  4. Pracujte s jednou \u201epravdou\u201c<\/b>
    \n<\/b>Meta vyu\u017e\u00edvajte na optimaliz\u00e1ciu kampan\u00ed, GA4 na celkov\u00fd poh\u013ead. Porovn\u00e1vanie 1:1 \u010dasto ned\u00e1va zmysel.<\/span><\/span><\/span><\/li>\n
  5. Zapojte backend alebo server-side d\u00e1ta<\/b>
    \n<\/b>CRM alebo sGTM pom\u00f4\u017eu z\u00edska\u0165 stabilnej\u0161\u00ed a presnej\u0161\u00ed zdroj d\u00e1t.<\/span><\/span><\/span><\/li>\n
  6. Sledujte trendy, nie absol\u00fatne \u010d\u00edsla<\/b>
    \n<\/b>D\u00f4le\u017eit\u00e9 je, \u010di sa d\u00e1ta vyv\u00edjaj\u00fa rovnak\u00fdm smerom, nie \u010di sa presne zhoduj\u00fa.<\/span><\/li>\n<\/ol>\n

    Pokro\u010dil\u00e9 rie\u0161enie: Jednotn\u00fd zdroj pravdy<\/b><\/h2>\n

    Je zrejm\u00e9, \u017ee snaha o zos\u00faladenie \u010d\u00edsel z Meta a GA4 je m\u00e1rna. Platformy s\u00fa navrhnut\u00e9 na in\u00e9 \u00fa\u010dely a meraj\u00fa svet odli\u0161n\u00fdm sp\u00f4sobom. Namiesto porovn\u00e1vania neporovnate\u013en\u00e9ho by sa mali pokro\u010dil\u00e9 firmy zamera\u0165 na vytvorenie <\/span>jednotn\u00e9ho zdroja pravdy (single source of truth)<\/b>.<\/span><\/p>\n

    Tento pr\u00edstup spo\u010d\u00edva v dvoch hlavn\u00fdch krokoch:<\/strong><\/span><\/p>\n

    1. Centraliz\u00e1cia surov\u00fdch d\u00e1t<\/b><\/h4>\n

    Prv\u00fdm krokom je zhroma\u017e\u010fovanie surov\u00fdch, neagregovan\u00fdch d\u00e1t<\/strong> zo v\u0161etk\u00fdch marketingov\u00fdch a obchodn\u00fdch zdrojov do jedn\u00e9ho centr\u00e1lneho \u00falo\u017eiska, ktor\u00fdm je <\/span>centralizovan\u00fd d\u00e1tov\u00fd sklad<\/b>. Sem pr\u00fadia udalosti z Meta Ads, Google Ads, Google Analytics 4, CRM syst\u00e9mu, emailovej platformy a \u010fal\u0161\u00edch.<\/span><\/span><\/span><\/span><\/p>\n

    O d\u00e1tovom sklade nap\u00edsal \u010dl\u00e1nok n\u00e1\u0161 kolega Julo.<\/strong> 👇<\/p>\n\n\t

    \n\t
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    <\/div>\n\t\t<\/a>\n\t\t
    \n\t\t
    \n\t\t\t\n \t\t Marketing Data Warehouse: Ch\u00fdbaj\u00faci dielik vo va\u0161ej d\u00e1tovej strat\u00e9gii<\/span>\t\n\t\t\t<\/a>\n\t\t\t
    \n\t\t\t Novinky<\/a> | \n\t\t\t J\u00falius Selnekovi\u010d<\/a> |\n\t\t\t \n\t\t\t \t
    \n\t\t \t

    Pre market\u00e9rov a marketingov\u00fdch mana\u017e\u00e9rov je \u201cdata-driven\u201d rozhodovanie \u010dasto iba fr\u00e1za. Probl\u00e9mom nie je nedostatok d\u00e1t, ale ich...<\/p>\n\t\t <\/article>\n\t\t<\/div>\n\t <\/div>\n\t<\/section>\n\t\n

    2. Vytvorenie vlastn\u00e9ho atribu\u010dn\u00e9ho modelu<\/b><\/h4>\n

    Na z\u00e1klade t\u00fdchto zjednoten\u00fdch d\u00e1t si m\u00f4\u017eete vytvori\u0165 <\/span>vlastn\u00fd atribu\u010dn\u00fd model<\/b>.<\/span><\/p>\n

    Namiesto toho, aby ste sa spoliehali na prednastaven\u00e9 modely platforiem<\/strong>, ktor\u00e9 prirodzene favorizuj\u00fa samy seba, si definujete vlastn\u00e9 pravidl\u00e1.<\/strong> Tento model m\u00f4\u017ee by\u0165 jednoduch\u00fd, zalo\u017een\u00fd na pravidl\u00e1ch, alebo sofistikovan\u00fd, vyu\u017e\u00edvaj\u00faci \u0161tatistick\u00e9 met\u00f3dy. Odr\u00e1\u017ea va\u0161u unik\u00e1tnu obchodn\u00fa logiku a skuto\u010dn\u00fa z\u00e1kazn\u00edcku cestu.<\/strong><\/span><\/p>\n

    Tento pr\u00edstup je technicky a zdrojovo n\u00e1ro\u010dn\u00fd a nie je to r\u00fdchle rie\u0161enie. Pre firmy, ktor\u00e9 to s d\u00e1tovo riaden\u00fdm marketingom myslia v\u00e1\u017ene, je to v\u0161ak jedin\u00e1 cesta k spo\u013eahliv\u00e9mu a holistick\u00e9mu poh\u013eadu na v\u00fdkonnos\u0165.<\/strong><\/span><\/p>\n

    Z\u00e1ver: Ako pristupova\u0165 k reportingu v praxi<\/b><\/h2>\n

    Presta\u0148te sa tr\u00e1pi\u0165 h\u013eadan\u00edm dokonalej zhody medzi reportmi jednotliv\u00fdch platforiem. Namiesto toho ich pou\u017e\u00edvajte na to, v \u010dom s\u00fa najlep\u0161ie.<\/span><\/p>\n

    Reporty v <\/span>Meta Ads<\/b> s\u00fa neocenite\u013en\u00e9 pre optimaliz\u00e1ciu kampan\u00ed v r\u00e1mci Meta ekosyst\u00e9mu. V\u010faka metrik\u00e1m ako s\u00fa kliknutia a reportovaniu viden\u00fdch konverzi\u00ed je Meta ide\u00e1lna na hodnotenie kreat\u00edv, cielenia a celkov\u00e9ho z\u00e1sahu a povedomia o zna\u010dke.<\/span><\/p>\n

    Google Analytics 4<\/b> je zasa bezkonkuren\u010dn\u00fd n\u00e1stroj na anal\u00fdzu spr\u00e1vania pou\u017e\u00edvate\u013eov na va\u0161om webe. V\u010faka metrike rel\u00e1ci\u00ed a detailnej anal\u00fdze ciest z\u00e1kazn\u00edka je nenahradite\u013en\u00fd na pochopenie re\u00e1lneho spr\u00e1vania na webe a interakci\u00ed medzi v\u0161etk\u00fdmi marketingov\u00fdmi kan\u00e1lmi.<\/span><\/p>\n

    Ak sa dostanete do bodu, kedy v\u00e1s limit\u00e1cie a nepresnosti reportov jednotliv\u00fdch platforiem brzdia v strategick\u00fdch rozhodnutiach,<\/strong> je \u010das zv\u00e1\u017ei\u0165 pokro\u010dilej\u0161ie rie\u0161enie. Vybudovanie centralizovan\u00e9ho d\u00e1tov\u00e9ho skladu a vlastn\u00e9ho atribu\u010dn\u00e9ho modelu je invest\u00edcia, ktor\u00e1 v\u00e1m umo\u017en\u00ed presta\u0165 h\u00e1da\u0165 a za\u010da\u0165 robi\u0165 rozhodnutia na z\u00e1klade jednotn\u00e9ho a d\u00f4veryhodn\u00e9ho poh\u013eadu na va\u0161e marketingov\u00e9 d\u00e1ta.<\/strong><\/span><\/p>\n

    Ak m\u00e1te ak\u00e9ko\u013evek ot\u00e1zky, pokojne n\u00e1m nap\u00ed\u0161te na cibula@dase.sk<\/strong> , pr\u00edpadne si s na\u0161im Marekom rovno booknite bezplatn\u00fa 30min konzult\u00e1ciu tu.<\/strong><\/a> 🖖<\/p>\n","protected":false},"excerpt":{"rendered":"

    Ak sa akt\u00edvne venujete marketingu, ur\u010dite ste sa stretli so situ\u00e1ciou, kedy vid\u00edte stovky kliknut\u00ed v Meta, no…<\/p>\n","protected":false},"author":80,"featured_media":21507,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[639,637],"tags":[964,799,963,967],"_links":{"self":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/21468"}],"collection":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/users\/80"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/comments?post=21468"}],"version-history":[{"count":10,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/21468\/revisions"}],"predecessor-version":[{"id":21512,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/21468\/revisions\/21512"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media\/21507"}],"wp:attachment":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media?parent=21468"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/categories?post=21468"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/tags?post=21468"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}