{"id":16183,"date":"2020-06-10T10:06:35","date_gmt":"2020-06-10T08:06:35","guid":{"rendered":"https:\/\/www.dase-analytics.com\/blog\/?p=16183\/"},"modified":"2021-10-26T13:12:51","modified_gmt":"2021-10-26T11:12:51","slug":"gtm-tip-3-ako-merat-cta-prvky-v-google-analytics","status":"publish","type":"post","link":"https:\/\/www.dase-analytics.com\/blog\/sk\/gtm-tip-3-ako-merat-cta-prvky-v-google-analytics\/","title":{"rendered":"GTM TIP #03: Ako mera\u0165 CTA prvky v Google Analytics?"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Ako mera\u0165 efektivitu CTA prvkov priamo v Google Analytics? V tomto kr\u00e1tkom n\u00e1vode uk\u00e1\u017eem, \u010do a ako je potrebn\u00e9 nastavi\u0165 v Google Analytics a Google Tag Manager-i. Taktie\u017e prid\u00e1m p\u00e1r odpor\u00fa\u010dan\u00ed, ktor\u00e9 v\u00e1m pom\u00f4\u017eu pri vyhodnocovan\u00ed t\u00fdchto d\u00e1t a upozorn\u00edm na veci, na ktor\u00e9 je dobr\u00e9 myslie\u0165 e\u0161te pred t\u00fdm, ako d\u00e1ta za\u010dneme zbiera\u0165.<\/span><\/p>\n<h2><b>Pre\u010do je meranie CTA prvkov problematick\u00e9?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Probl\u00e9m je, \u017ee CTA prvky s\u00fa umiest\u0148ovan\u00e9 na r\u00f4znych \u010dastiach str\u00e1nky. Niekedy ich m\u00f4\u017eeme n\u00e1js\u0165 uprostred alebo na konci \u010dl\u00e1nkov, niekedy sa zobrazia v podobe vyskakovacieho okna, niekedy sa zase nemusia zobrazi\u0165 v\u00f4bec. <strong>Preto po\u010d\u00edta\u0165 CTR CTA prvkov na z\u00e1klade po\u010dtu zobrazen\u00ed str\u00e1nky \u010dasto vedie k nepresn\u00fdm \u010d\u00edslam.<\/strong> Navy\u0161e, ak sa CTA prvok zmen\u00ed, popr\u00edpade testujeme viacero CTA prvkov naraz, nebudeme ich vedie\u0165 poriadne porovna\u0165. Preto je lep\u0161ie spo\u010d\u00edta\u0165, ko\u013ekokr\u00e1t CTA prvok pou\u017e\u00edvate\u013e re\u00e1lne videl a vypo\u010d\u00edta\u0165 CTR z tejto hodnoty. <strong>Navy\u0161e, t\u00fdmto nastaven\u00edm budeme vedie\u0165 aj vy\u010d\u00edsli\u0165, ko\u013eko pou\u017e\u00edvate\u013eov, ktor\u00ed dan\u00fa str\u00e1nku nav\u0161t\u00edvili, sa k CTA prvku v\u00f4bec nedostali.<\/strong> To m\u00f4\u017ee by\u0165 taktie\u017e zauj\u00edmav\u00e1 inform\u00e1cia, ktor\u00e1 n\u00e1m ve\u013ea napovie o tom, ako pou\u017e\u00edvatelia s na\u0161im obsahom interaguj\u00fa.<\/span><\/p>\n<h2><b>\u010co nastavi\u0165 v Google Analytics?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\"><strong>V Google Analytics si vyhrad\u00edme dve vlastn\u00e9 metriky &#8211; jedna bude po\u010d\u00edta\u0165 ko\u013ekokr\u00e1t bol dan\u00fd CTA prvok zobrazen\u00fd a druh\u00e1 bude po\u010d\u00edta\u0165 v\u0161etky interakcie s CTA prvkom, napr. prekliky, vyplnenie formul\u00e1ra (z\u00e1le\u017e\u00ed od typu CTA).<\/strong> Z vlastnej sk\u00fasenosti viem, \u017ee sa vlastn\u00e9 metiky (Custom Metrics) takmer v\u00f4bec nepou\u017e\u00edvaj\u00fa (\u010do je \u0161koda), tak\u017ee vyhradi\u0165 dva sloty by nemal by\u0165 probl\u00e9m. V\u00fdhodou pri vytvoren\u00ed vlastn\u00fdch metr\u00edk je aj fakt, \u017ee ich viete pou\u017ei\u0165 pri defin\u00edcii kalkulovan\u00fdch metr\u00edk (ktor\u00e9 sa taktie\u017e ve\u013emi nevyu\u017e\u00edvaj\u00fa) &#8211; napr. CTR. Zauj\u00edmav\u00fd m\u00f4\u017ee by\u0165 aj pomer zobrazenia str\u00e1nky a zobrazenia CTA prvku &#8211; ko\u013eko percent pou\u017e\u00edvate\u013eov sa k CTA prvku v\u00f4bec nedostalo?<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Vlastn\u00e9 metriky, podobne ako vlastn\u00e9 dimenzie, sa vytv\u00e1raj\u00fa na \u00farovni Vlastn\u00edctva (Property):<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image13-6.png\" data-rel=\"lightbox-image-0\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16185 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image13-6.png\" alt=\"Pridanie vlastnej metriky v Google Analytics\" width=\"478\" height=\"810\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image13-6.png 478w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image13-6-177x300.png 177w\" sizes=\"(max-width: 478px) 100vw, 478px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Obe vlastn\u00e9 metriky bud\u00fa ma\u0165 rozsah (scope) Hit, a form\u00e1t Integer.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image1-29.png\" data-rel=\"lightbox-image-1\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16186 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image1-29.png\" alt=\"Defin\u00edcia dvoch vlastn\u00fdch metr\u00edk v Google Analytics\" width=\"662\" height=\"582\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image1-29.png 662w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image1-29-300x264.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image1-29-600x527.png 600w\" sizes=\"(max-width: 662px) 100vw, 662px\" \/><\/a><\/p>\n<p>&nbsp;<\/p>\n<p><span style=\"font-weight: 400;\">Kalkulovan\u00e9 metriky sa na rozdiel od Vlastn\u00fdch metr\u00edk vytv\u00e1raj\u00fa na \u00farovni Zobrazen\u00ed (Views). To znamen\u00e1, \u017ee na rozdiel od vlastn\u00fdch metr\u00edk, kalkulovan\u00e9 metriky bud\u00fa pr\u00edstupn\u00e9 len v t\u00fdch Zobrazeniach, v ktor\u00fdch ich vytvor\u00edme. V na\u0161om pr\u00edpade vytv\u00e1rame metriku CTR a vo vzorci vyu\u017eijeme dve Vlastn\u00e9 metriky, ktor\u00e9 sme vytvorili v predo\u0161lom kroku: <strong>{{CM02 &#8211; CTA Interaction}} \/ {{CM01 &#8211; CTA Visible}}<\/strong><\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image2-29.png\" data-rel=\"lightbox-image-2\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16187 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image2-29.png\" alt=\"Kalkulovan\u00e9 metriky v Google Analytics\" width=\"946\" height=\"820\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image2-29.png 946w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image2-29-300x260.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image2-29-600x520.png 600w\" sizes=\"(max-width: 946px) 100vw, 946px\" \/><\/a><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12.png\" data-rel=\"lightbox-image-3\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16188 size-large\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12-1024x425.png\" alt=\"Defin\u00edcia kalkulovanej metriky v Google Analytics\" width=\"1024\" height=\"425\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12-1024x425.png 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12-300x125.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12-600x249.png 600w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image7-12.png 1185w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/p>\n<h2><b>\u010co nastavi\u0165 v Google Tag Manager-i?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">V GTM potom potrebujeme vytvori\u0165 dva tagy &#8211; jeden, ktor\u00fd sa bude odpa\u013eova\u0165 ke\u010f sa CTA prvok zobraz\u00ed, druh\u00fd, ktor\u00fd odo\u0161le d\u00e1ta do Google Analytics ak pou\u017e\u00edvate\u013e vykonal po\u017eadovan\u00fa akciu. <\/span><b>Nezabudnite v tagoch nastavi\u0165 aj vlastn\u00e9 metriky (indexy zvo\u013ete pod\u013ea indexov vlastn\u00fdch metr\u00edk v Google Analytics).<\/b><\/p>\n<p><span style=\"font-weight: 400;\">Ak chcete mera\u0165 nejak\u00fd element na str\u00e1nke, potrebujete ho nejak\u00fdm sp\u00f4sobom vybra\u0165. Na to sa pou\u017e\u00edvaj\u00fa <\/span><a href=\"https:\/\/www.w3schools.com\/cssref\/css_selectors.asp\"><span style=\"font-weight: 400;\">CSS selektory<\/span><\/a><span style=\"font-weight: 400;\">. Vyu\u017eit\u00edm CSS selektorov dok\u00e1\u017eeme ozna\u010di\u0165 ak\u00fdko\u013evek element na str\u00e1nke. Vyu\u017e\u00edvaj\u00fa sa na to ich atrib\u00faty, ako id alebo trieda (class), alebo ich usporiadanie vzh\u013eadom na in\u00e9 HTML elementy. Nastavenie si uk\u00e1\u017eeme na pr\u00edklade na\u0161ich CTA prvkov, ktor\u00e9 n\u00e1jdete na konci ka\u017ed\u00e9ho \u010dl\u00e1nku. V na\u0161om pr\u00edpade CTA prvok obsahuje formul\u00e1r s ID <\/span><b>ebookform<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8.png\" data-rel=\"lightbox-image-4\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16189 size-large\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8-1024x288.png\" alt=\"CTA prvok pre newsletter\" width=\"1024\" height=\"288\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8-1024x288.png 1024w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8-300x84.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8-1536x432.png 1536w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8-600x169.png 600w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image10-8.png 1572w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Ak chceme vytvori\u0165 CSS selektor, ktor\u00fd ozna\u010d\u00ed tento formul\u00e1r, pou\u017eijeme CSS selektor <\/span><b>form#ebookform<\/b><span style=\"font-weight: 400;\">.<\/span> <span style=\"font-weight: 400;\">Tento CSS selektor potom vyu\u017eijeme pri definovan\u00ed Element visibility sp\u00fa\u0161\u0165a\u010da.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image11-6.png\" data-rel=\"lightbox-image-5\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16191 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image11-6.png\" alt=\"Sp\u00fa\u0161\u0165a\u010d pre vidite\u013enos\u0165 HTML elementu\" width=\"937\" height=\"407\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image11-6.png 937w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image11-6-300x130.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image11-6-600x261.png 600w\" sizes=\"(max-width: 937px) 100vw, 937px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Podobn\u00fd pr\u00edstup aplikujeme pre sp\u00fa\u0161\u0165a\u010d, ktor\u00fdm budeme mera\u0165 interakcie s CTA prvkom. V na\u0161om pr\u00edpade to teda bude udalos\u0165 Form Submit, ktor\u00e1 bola vyvolan\u00e1 formul\u00e1rom s ID\u010dkom <\/span><b>ebookform<\/b><span style=\"font-weight: 400;\">.<\/span><\/p>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image3-27.png\" data-rel=\"lightbox-image-6\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16190 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image3-27.png\" alt=\"Sp\u00fa\u0161\u0165a\u010d na vyplnen\u00fd formul\u00e1r\" width=\"937\" height=\"255\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image3-27.png 937w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image3-27-300x82.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image3-27-600x163.png 600w\" sizes=\"(max-width: 937px) 100vw, 937px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Defin\u00edcia sp\u00fa\u0161\u0165a\u010da pre meranie interakcie bude z\u00e1visie\u0165 od typu CTA. Ak sa jedn\u00e1 iba o tla\u010d\u00edtko, vysta\u010d\u00edte si s Click trigger-om. Ak je CTA formul\u00e1r (tak ako v na\u0161om pr\u00edpade),\u00a0 vyu\u017eijeme Form Submit trigger. Tento sp\u00fa\u0161\u0165a\u010d v\u0161ak \u010dastokr\u00e1t nefunguje presne tak, ako by mal, tak\u017ee formul\u00e1re odpor\u00fa\u010dam dobre otestova\u0165 a uisti\u0165 sa, \u017ee v\u0161etko funguje tak ako by malo. Alternat\u00edvne m\u00f4\u017eete pou\u017ei\u0165 \u010fal\u0161\u00ed Element Visibility trigger, ktor\u00fd sa odp\u00e1li ak sa zobraz\u00ed potvrdzuj\u00faca spr\u00e1va (napr. \u010fakovn\u00e1 spr\u00e1va po \u00faspe\u0161nom zap\u00edsan\u00ed do newslettra).<\/span><\/p>\n<h2><b>Ako na r\u00f4zne verzie a typy CTA?<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Ak chcete testova\u0165 viacero verzi\u00ed CTA prvkov, je dobr\u00e9 ich nejak\u00fdm sp\u00f4sobom odl\u00ed\u0161i\u0165. Na to m\u00f4\u017eete bu\u010f vyu\u017ei\u0165 tri dimenzie, ktor\u00e9 sa odosielaj\u00fa s ka\u017edou Udalos\u0165ou (Event) do Google Analytics &#8211; Event Category, Event Action a Event Label. \u010castokr\u00e1t sa stret\u00e1vam s predstavou, \u017ee Event Category by mal obsahova\u0165 typ eventu, Event Action akciu, ktor\u00fa pou\u017e\u00edvate\u013e urobil (click, form submit) a Event Label bli\u017e\u0161ie detaily o vykonanej akcii. Je to v\u0161ak \u00faplne na v\u00e1s, ak\u00e9 d\u00e1ta do t\u00fdchto dimenzi\u00ed odo\u0161lete. Mali by ste si v\u017edy ujasni\u0165, ak\u00e9 inform\u00e1cie chcete v Google Analytics vidie\u0165 a na z\u00e1klade toho prisp\u00f4sobi\u0165 obsah t\u00fdchto troch dimenzi\u00ed. V mojom pr\u00edpade som sa do Event Category rozhodol posiela\u0165 dve hodnoty:<\/span><\/p>\n<ul>\n<li style=\"font-weight: 400;\"><b>cta_visible<\/b><span style=\"font-weight: 400;\"> &#8211; pre udalosti, ktor\u00e9 sa odo\u0161l\u00fa pri zobrazen\u00ed CTA prvku,<br \/>\n<\/span><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image5-17.png\" data-rel=\"lightbox-image-7\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16192 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image5-17.png\" alt=\"Tag na meranie vidite\u013enosti CTA prvku\" width=\"936\" height=\"763\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image5-17.png 936w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image5-17-300x245.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image5-17-600x489.png 600w\" sizes=\"(max-width: 936px) 100vw, 936px\" \/><\/a><\/li>\n<\/ul>\n<ul>\n<li style=\"font-weight: 400;\"><b>cta_interaction<\/b><span style=\"font-weight: 400;\"> &#8211; pre udalosti, ktor\u00e9 sa odo\u0161l\u00fa po interakcii s CTA prvkom.<\/span><\/li>\n<\/ul>\n<p><a href=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image6-15.png\" data-rel=\"lightbox-image-8\" data-rl_title=\"\" data-rl_caption=\"\" title=\"\"><img decoding=\"async\" loading=\"lazy\" class=\"aligncenter wp-image-16193 size-full\" src=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image6-15.png\" alt=\"Tag na meranie interakcie s CTA prvkom\" width=\"940\" height=\"767\" srcset=\"https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image6-15.png 940w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image6-15-300x245.png 300w, https:\/\/www.dase-analytics.com\/blog\/wp-content\/uploads\/image6-15-600x490.png 600w\" sizes=\"(max-width: 940px) 100vw, 940px\" \/><\/a><\/p>\n<p><span style=\"font-weight: 400;\">Zostali n\u00e1m dve dimenzie &#8211; Event Action a Event Label, ktor\u00e9 m\u00f4\u017eeme vyu\u017ei\u0165 na zaslanie detailov, napr\u00edklad typ CTA prvku. Ak potrebujete posla\u0165 viacero hodn\u00f4t a dve dimenzie v\u00e1m nesta\u010dia, m\u00f4\u017eete ich posla\u0165 prostredn\u00edctvom Vlastn\u00fdch dimenzi\u00ed, alebo ich zl\u00fa\u010di\u0165 do jednej (odpor\u00fa\u010dam pou\u017ei\u0165 odde\u013eova\u010de, v\u010faka ktor\u00fdm potom m\u00f4\u017eete tak\u00fato vlastn\u00fa dimenziu rozbi\u0165 na jednotliv\u00e9 hodnoty &#8211; napr\u00edklad v Google Data Studiu s vyu\u017eit\u00edm kalkulovan\u00fdch pol\u00ed). Pri zl\u00fa\u010den\u00ed viacer\u00fdch hodn\u00f4t do jednej dimenzie by to mohlo vyzera\u0165 napr\u00edklad takto: position:center|color:red|text:subscribe now|variant:4&#215;4<\/span><\/p>\n<h2><b>Reportovanie a vyhodnotenie<\/b><\/h2>\n<p><span style=\"font-weight: 400;\">Po \u00faspe\u0161nej implement\u00e1cii potrebujeme nazbieran\u00e9 d\u00e1ta vizualizova\u0165. Ke\u010f\u017ee sme vyu\u017eili Vlastn\u00e9 metriky, potrebujeme si taktie\u017e vytvori\u0165 Vlastn\u00fd report v Google Analytics (alebo ak sa chcete pohra\u0165 aj s vizu\u00e1lnou str\u00e1nkou, m\u00f4\u017eete report pripravi\u0165 v Google Data Studiu). <strong>V\u00fdhodou pri pou\u017eit\u00ed Vlastn\u00fdch metr\u00edk je, \u017ee sa na ne viete pozrie\u0165 z r\u00f4znych dimenzi\u00ed, bez nutnosti vytv\u00e1rania komplikovan\u00fdch segmentov alebo filtrov<\/strong>. Ako dimenziu m\u00f4\u017eete napr\u00edklad vyu\u017ei\u0165 kan\u00e1l, typ zariadenia, konkr\u00e9tnu str\u00e1nku alebo typ CTA prvku. V z\u00e1vislosti od zvolenej dimenzie potom budete vedie\u0165 o va\u0161ich CTA prvkoch vyvodi\u0165 r\u00f4zne z\u00e1very. Navy\u0161e testovanie r\u00f4znych CTA prvkov bude ve\u013emi r\u00fdchle a efekt\u00edvne a po nazbieran\u00ed dostato\u010dn\u00e9ho mno\u017estva d\u00e1t sa budete vedie\u0165 ve\u013emi r\u00fdchlo rozhodn\u00fa\u0165 pre t\u00fa spr\u00e1vnu alternat\u00edvu.<\/span><\/p>\n<p><span style=\"font-weight: 400;\">Ak m\u00e1te ot\u00e1zku oh\u013eadom merania na webe, nap\u00ed\u0161te ju dolu do koment\u00e1rov a v \u010fal\u0161om \u010dl\u00e1nku by som sa mohol venova\u0165 pr\u00e1ve tej va\u0161ej.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Ako mera\u0165 efektivitu CTA prvkov priamo v Google Analytics? V tomto kr\u00e1tkom n\u00e1vode uk\u00e1\u017eem, \u010do a ako je&#8230;<\/p>\n","protected":false},"author":62,"featured_media":16184,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[809,639],"tags":[788,602],"_links":{"self":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/16183"}],"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\/62"}],"replies":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/comments?post=16183"}],"version-history":[{"count":5,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/16183\/revisions"}],"predecessor-version":[{"id":17898,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/16183\/revisions\/17898"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media\/16184"}],"wp:attachment":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media?parent=16183"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/categories?post=16183"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/tags?post=16183"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}