{"id":14165,"date":"2019-03-20T10:13:32","date_gmt":"2019-03-20T08:13:32","guid":{"rendered":"https:\/\/www.dase-analytics.com\/blog\/?p=14165"},"modified":"2019-10-31T11:22:14","modified_gmt":"2019-10-31T09:22:14","slug":"ako-dostat-offline-interakcie-do-google-analytics","status":"publish","type":"post","link":"https:\/\/www.dase-analytics.com\/blog\/sk\/ako-dostat-offline-interakcie-do-google-analytics\/","title":{"rendered":"Ako dosta\u0165 offline interakcie do Google Analytics?"},"content":{"rendered":"

Pri zbieran\u00ed a n\u00e1slednom vyhodnocovan\u00ed d\u00e1t sa \u010dasto zab\u00fada na fakt, \u017ee n\u00e1v\u0161tevn\u00edkmi webu nie s\u00fa internetov\u00e9 prehliada\u010de, ale re\u00e1lni \u013eudia, ktor\u00ed s va\u0161im biznisom \u010di zna\u010dkou interaguj\u00fa aj mimo online sveta. So svojimi (bud\u00facimi) z\u00e1kazn\u00edkmi komunikujete viacer\u00fdmi kan\u00e1lmi <\/b>\u2013<\/b> telefonicky, mailom a v mnoh\u00fdch pr\u00edpadoch aj osobne.<\/b><\/p>\n

 <\/p>\n

Pre\u010do mera\u0165 offline interakcie?<\/span><\/h2>\n

Toto sa t\u00fdka najm\u00e4 tzv.<\/span> lead generation webov<\/b>. Ako u\u017e z n\u00e1zvu vypl\u00fdva, ich hlavnou \u00falohou je z\u00edska\u0165 lead (v\u00e4\u010d\u0161inou kontakt), po ktorom nasleduje komunik\u00e1cia zv\u00e4\u010d\u0161a mimo webu. Posla\u0165 inform\u00e1ciu do Google Analytics o tom, \u017ee pou\u017e\u00edvate\u013e vyplnil na webe kontaktn\u00fd formul\u00e1r, je jednoduch\u00e9. <\/span><\/p>\n

No \u010do s inform\u00e1ciou, ako sa tento lead vyv\u00edjal \u010falej v \u010dase? V\u00e4\u010d\u0161inou nasleduje jedno alebo viacero osobn\u00fdch stretnut\u00ed, emailov \u010di telefon\u00e1tov. A\u017e po nich ste schopn\u00ed ur\u010di\u0165, \u010di tento lead nakoniec <\/span>prekonvertujete na re\u00e1lneho z\u00e1kazn\u00edka<\/b>.<\/span><\/p>\n

Ak by ste boli schopn\u00ed tieto d\u00e1ta dosta\u0165 do Google Analytics, vedeli by ste vyhodnocova\u0165 nielen mno\u017estvo leadov, ktor\u00e9 web vyprodukoval, ale aj ich kvalitu.<\/span><\/p>\n

 <\/p>\n

\u010co je Measurement protokol?<\/span><\/h2>\n

Measurement protokol<\/b> je jedn\u00fdm zo sp\u00f4sobov, ako m\u00f4\u017eete posla\u0165 d\u00e1ta (hity) do Google Analytics. \u010eal\u0161\u00edmi dvomi sp\u00f4sobmi s\u00fa klasick\u00fd <\/span>Google Analytics k\u00f3d<\/b> (gtag.js) a spustenie Google Analytics tagu prostredn\u00edctvom <\/span>Google Tag Manager-a<\/b>. <\/span><\/p>\n

V\u00fdhodou Measurement protokolu je, \u017ee d\u00e1ta, ktor\u00e9 prostredn\u00edctvom neho po\u0161leme do Google Analytics, sa nemusia nutne vz\u0165ahova\u0165 na konkr\u00e9tnu interakciu pou\u017e\u00edvate\u013ea s webom. <\/span>Prostredn\u00edctvom Measurement protokolu sme schopn\u00ed posla\u0165 hit do Google Analytics z ak\u00e9hoko\u013evek zariadenia s pripojen\u00edm na internet.<\/b><\/p>\n

Navy\u0161e, tak\u00fdto hit nemus\u00ed by\u0165 odoslan\u00fd z webov\u00e9ho prehliada\u010da. Na to, aby ste pochopili, ako measurement protokol funguje, mus\u00edte vedie\u0165, ako sa vlastne d\u00e1ta do Google Analytics posielaj\u00fa.<\/span><\/p>\n

 <\/p>\n

Ako sa posielaj\u00fa d\u00e1ta do Google Analytics?<\/span><\/h2>\n


\n<\/span>D\u00e1ta sa do Google Analytics posielaj\u00fa prostredn\u00edctvom <\/span>tzv. requestov<\/b>. Tieto requesty a ich \u0161trukt\u00faru si viete prezrie\u0165 napr\u00edklad v prehliada\u010di Chrome. Po <\/span>otvoren\u00ed Dev (Ctrl+Shift+I) a otvoren\u00ed Network tabu<\/b>. Po odfiltrovan\u00ed requestov, ktor\u00e9 obsahuj\u00fa <\/span>\u2018\/collect\u2019<\/b>, by sa v\u00e1m mali zobrazi\u0165 v\u0161etky requesty, ktor\u00e9 smerovali do Google Analytics (dom\u00e9nu www.google-analytics.com). Po rozkliknut\u00ed tak\u00e9hoto requestu uvid\u00edte zoznam parametrov, ktor\u00e9 boli odoslan\u00e9 do Google Analytics.<\/span><\/p>\n

\"\"<\/p>\n

Tieto requesty s\u00fa \u00faplne rovnak\u00e9 bez oh\u013eadu na to, ak\u00fdm sp\u00f4sobom sa tieto d\u00e1ta do Google Analytics odoslali (gtag.js, Google Tag Manager \u010di Measurement protokol).<\/span><\/p>\n

M\u00f4\u017eeme teda poveda\u0165, \u017ee <\/span>measurement protocol je v pozad\u00ed za ka\u017ed\u00fdm jedn\u00fdm odoslan\u00fdm hitom do Google Analytics<\/b>. Tag v Google Tag Manageri alebo funkcia klasick\u00e9ho Analytics-u (gtag.js) je len akousi nadstavbou, ktor\u00e1 n\u00e1s do zna\u010dnej miery odbreme\u0148uje pri pr\u00edprave a implement\u00e1cii samotn\u00e9ho merania, ke\u010f\u017ee mno\u017estvo atrib\u00fatov sa dopln\u00ed automaticky, bez nutnosti ich definovania. <\/span><\/p>\n

To ale neplat\u00ed v pr\u00edpade, ak si tak\u00fdto hit sklad\u00e1te sami <\/span>\u2013 <\/span>v takomto hite odo\u0161lete presne to, \u010do si v \u0148om zadefinujete.<\/span><\/p>\n

Tie\u017e by som zd\u00f4raznil, \u017ee vzh\u013eadom na sp\u00f4sob, ak\u00fdm Google Analytics sprac\u00fava d\u00e1ta, <\/span>nie je mo\u017en\u00e9 zmeni\u0165 \u010das, kedy bol tak\u00fdto hit zaznamenan\u00fd<\/b>. To znamen\u00e1, \u017ee ak dnes po\u0161lete \u00fadaje o transakcii, ktor\u00e1 sa stala 1. marca, v Google Analytics reportoch sa t\u00e1to transakcia zobraz\u00ed pri dne\u0161nom d\u00e1tume. <\/span><\/p>\n

Do istej miery sa to d\u00e1 <\/span>\u201e<\/span>ob\u00eds\u0165\u201d <\/span>vyu\u017eit\u00edm vlastnej dimenzie<\/b>, no aj v takomto pr\u00edpade budete odk\u00e1zan\u00ed na vlastn\u00e9 reporty, popr\u00edpade Data Studio \u010di in\u00fd reportovac\u00ed n\u00e1stroj.<\/span><\/p>\n

Vytvorenie hitu cez Measurement protokol teda znamen\u00e1 <\/span>vytvorenie sledu parametrov a hodn\u00f4t t\u00fdchto parametrov, ktor\u00e9 s\u00fa posp\u00e1jan\u00e9 do jedn\u00e9ho request-u<\/b>. Samozrejme, existuj\u00fa pravidl\u00e1, ak\u00e9 parametre s\u00fa v takomto hite potrebn\u00e9. Podrobnej\u0161ie inform\u00e1cie o jednotliv\u00fdch parametroch si m\u00f4\u017eete na\u0161tudova\u0165 tu<\/a>. <\/span><\/p>\n

N\u00e1sledne tento hit m\u00f4\u017eete odosla\u0165 prostredn\u00edctvom <\/span>POST alebo GET requestu<\/b> (ak v\u00e1m toto ni\u010d nehovor\u00ed, m\u00f4\u017eete si sk\u00fasi\u0165 posla\u0165 tak\u00fdto hit cez n\u00e1stroj Hit Builder<\/a>, ktor\u00fd v\u00e1m aj pom\u00f4\u017ee tento hit posklada\u0165). <\/span><\/p>\n

Hit cez Measurement protokol sa d\u00e1 posla\u0165 napr\u00edklad aj cez <\/span>Google Sheet<\/b>, \u010do m\u00f4\u017ee by\u0165 pomerne jednoduch\u00fd sp\u00f4sob, ako posielanie tak\u00fdchto hitov automatizova\u0165 (ak by ste chceli vedie\u0165, ako na to, dajte vedie\u0165 dole v koment\u00e1roch a ur\u010dite to zahrniem v pokra\u010dovan\u00ed tohto \u010dl\u00e1nku \ud83d\ude42 ).<\/span><\/p>\n

Zameral by som sa v\u0161ak na jeden d\u00f4le\u017eit\u00fd parameter a to <\/span>Client ID (cid)<\/b>. Aby sme boli schopn\u00ed sp\u00e1rova\u0165 offline hit s pou\u017e\u00edvate\u013eom v Google Analytics (a jeho predch\u00e1dzaj\u00facimi rel\u00e1ciami), je nesmierne d\u00f4le\u017eit\u00e9, aby sme v hite odoslanom cez Measurement protokol, <\/span>priradili spr\u00e1vne Client ID<\/b>. Ako toto Client ID z\u00edska\u0165?<\/span><\/p>\n

Najjednoduch\u0161\u00edm sp\u00f4sobom je <\/span>zaznamen\u00e1va\u0165 t\u00fato hodnotu v\u017edy, ke\u010f pou\u017e\u00edvate\u013e na webe vypln\u00ed kontaktn\u00fd formul\u00e1r<\/b>. Tak, ako odo\u0161lete meno, email a \u010fal\u0161ie hodnoty, ktor\u00e9 pou\u017e\u00edvate\u013e pri vyp\u013a\u0148an\u00ed formul\u00e1ru zad\u00e1, m\u00f4\u017eete prostredn\u00edctvom skryt\u00e9ho pol\u00ed\u010dka odosiela\u0165 aj jeho Client ID. A ke\u010f\u017ee ur\u010dite n\u00e1\u0161 blog \u010d\u00edtate pravidelne, asi tu\u0161\u00edte, \u017ee <\/span>Client ID sa d\u00e1 jednoducho z\u00edska\u0165 z hodnoty cookie _ga<\/b> (tak, ako sme o tom p\u00edsali u\u017e v nieko\u013ek\u00fdch predch\u00e1dzaj\u00facich \u010dl\u00e1nkoch<\/a>).<\/span><\/p>\n

 <\/p>\n

Offline interakcie a atrib\u00facia<\/span><\/h2>\n

Samozrejme, probl\u00e9m s hitmi posielan\u00fdmi prostredn\u00edctvom Measurement protokolu m\u00f4\u017ee nasta\u0165, ke\u010f rie\u0161ite ich atrib\u00faciu. K ak\u00e9mu kan\u00e1lu alebo kampani by sme mali tak\u00fdto hit atribuova\u0165? <\/span><\/p>\n

Ke\u010f\u017ee Google Analytics pou\u017e\u00edva <\/span>last non-direct atribu\u010dn\u00fd model<\/b>, v praxi to znamen\u00e1, \u017ee offline interakcia by bola prip\u00edsan\u00e1 rovnak\u00e9mu zdroju, ako posledn\u00e1 rel\u00e1cia. Probl\u00e9m v\u0161ak je, \u017ee pou\u017e\u00edvate\u013e mohol od vyplnenia formul\u00e1ru po okamih, ke\u010f sme zaslali offline interakciu, nav\u0161t\u00edvi\u0165 va\u0161u str\u00e1nku nieko\u013ekokr\u00e1t a z r\u00f4znych zdrojov.<\/span><\/p>\n

Neexistuje teda univerz\u00e1lny sp\u00f4sob, ako vyrie\u0161i\u0165 atrib\u00faciu. Zrejme najlep\u0161ou mo\u017enos\u0165ou je <\/span>vyhodnoti\u0165 si atrib\u00faciu pre z\u00edskanie leadu<\/b> (lead sme z\u00edskali online) a od tohto okamihu budeme <\/span>\u201e<\/span>ignorova\u0165\u201d v\u0161etky rel\u00e1cie, ktor\u00e9 sme od dan\u00e9ho pou\u017e\u00edvate\u013ea zaznamenali (v obdob\u00ed od leadu po offline interakciu). In\u00fdmi slovami <\/span>\u2013 <\/span>\u00a0v\u0161etky<\/span> offline interakcie by sme mali atribuova\u0165 k rovnak\u00e9mu zdroju, ktor\u00fd m\u00e1 rel\u00e1cia<\/b>, po\u010das ktorej sme lead z\u00edskali.<\/span><\/p>\n

 <\/p>\n

Z\u00e1ver<\/span><\/h2>\n

Hoci je implement\u00e1cia merania s Measurement protokolom \u00a0v porovnan\u00ed s napr. GTM v\u00fdrazne komplikovanej\u0161ia, umo\u017e\u0148uje v\u00e1m dosta\u0165 do Google Analytics d\u00e1ta, ktor\u00e9 in\u00fdm sp\u00f4sobom nez\u00edskate . Odosielanie offline interakci\u00ed (alebo vo v\u0161eobecnosti d\u00e1t z in\u00fdch zdrojov ako v\u00e1\u0161 web) v\u00e1m poskytne <\/span>kompletnej\u0161\u00ed a ucelenej\u0161\u00ed poh\u013ead na spr\u00e1vanie va\u0161ich pou\u017e\u00edvate\u013eov<\/b>. <\/span><\/p>\n

A o ak\u00e9 d\u00e1ta by ste vy obohatili v\u00e1\u0161 Google Analytics \u00fa\u010det? Pode\u013ete sa s va\u0161imi n\u00e1padmi v koment\u00e1roch. \ud83d\ude42<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Pri zbieran\u00ed a n\u00e1slednom vyhodnocovan\u00ed d\u00e1t sa \u010dasto zab\u00fada na fakt, \u017ee n\u00e1v\u0161tevn\u00edkmi webu nie s\u00fa internetov\u00e9 prehliada\u010de,…<\/p>\n","protected":false},"author":62,"featured_media":14166,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[639,200],"tags":[],"_links":{"self":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/14165"}],"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=14165"}],"version-history":[{"count":6,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/14165\/revisions"}],"predecessor-version":[{"id":14634,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/14165\/revisions\/14634"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media\/14166"}],"wp:attachment":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media?parent=14165"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/categories?post=14165"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/tags?post=14165"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}