{"id":20266,"date":"2024-10-17T15:38:32","date_gmt":"2024-10-17T13:38:32","guid":{"rendered":"https:\/\/www.dase-analytics.com\/blog\/?p=20266\/"},"modified":"2024-10-17T15:38:32","modified_gmt":"2024-10-17T13:38:32","slug":"ako-merat-offline-konverzie-v-google-ads","status":"publish","type":"post","link":"https:\/\/www.dase-analytics.com\/blog\/sk\/ako-merat-offline-konverzie-v-google-ads\/","title":{"rendered":"Ako mera\u0165 offline konverzie v Google Ads?"},"content":{"rendered":"

Prech\u00e1dzaj\u00fa va\u0161e slu\u017eby z onlinu do offlinu? Obsahuje v\u00e1\u0161 web formul\u00e1re, ktor\u00e9 si vy\u017eaduj\u00fa \u010fal\u0161ie akcie, aby sa leady premenili na konverzie?<\/strong><\/p>\n

V tomto \u010dl\u00e1nku sa pozrieme na to, ako mo\u017eno zachyt\u00e1va\u0165 sp\u00e4tne aj tak\u00e9to akcie, ktor\u00fdch priebeh sa presunul mimo v\u00e1\u0161ho webu a optimalizova\u0165 tak kampane e\u0161te presnej\u0161ie.<\/p>\n

Pre ilustr\u00e1ciu si predstavme<\/strong> 2 kampane, ktor\u00e9 smeruj\u00fa na v\u00e1\u0161 formul\u00e1r na webe.<\/span><\/p>\n

\"Offline<\/a><\/p>\n

Povedzme, \u017ee sa tieto 2 kampane zobrazovali pribli\u017ene rovnak\u00e9mu po\u010dtu pou\u017e\u00edvate\u013eov v rovnakom \u010dasovom priebehu.<\/strong><\/span><\/p>\n

 <\/p>\n

👉 Kampa\u0148 A<\/b> vygenerovala <\/span>100 leadov<\/b> a teda 100 pou\u017e\u00edvate\u013eov vyplnilo tento formul\u00e1r a prejavilo tak z\u00e1ujem o va\u0161u ponuku.<\/span><\/p>\n

👉 Kampa\u0148 B<\/b> vygenerovala <\/span>80 leadov<\/b>.<\/span><\/p>\n

 <\/p>\n

Pod\u013ea t\u00fdchto v\u00fdsledkov mo\u017eno automaticky vyhodnoti\u0165 <\/span>Kampa\u0148 A<\/b> ako \u00faspe\u0161nej\u0161iu a prostriedky by sme tak alokovali pre t\u00fato kampa\u0148.<\/span><\/p>\n

\u010eal\u0161\u00ed krok v tomto procese by mohol predstavova\u0165 kontaktovanie z\u00e1kazn\u00edkov, ktor\u00ed prejavili z\u00e1ujem, s ostatn\u00fdmi detailmi ponuky, pr\u00edpadne in\u00fdmi vecami potrebn\u00fdmi zo strany z\u00e1kazn\u00edka pre uzavretie obchodu.<\/span><\/p>\n

\u010co teda, ak n\u00e1\u0161 funnel po odoslan\u00ed ponuky v\u0161etk\u00fdm potenci\u00e1lnym z\u00e1kazn\u00edkom vyzer\u00e1 takto?<\/strong><\/p>\n

\"Offline<\/a><\/p>\n

V pr\u00edpade <\/span>Kampane A<\/b> je to <\/span>40%<\/b> a v pr\u00edpade <\/span>Kampane B<\/b> je to <\/span>62,5%<\/b> z\u00e1kazn\u00edkov, ktor\u00ed sa dostali do \u010fal\u0161ieho kroku a teda pozit\u00edvne reagovali, pr\u00edpadne odoslali potrebn\u00e9 veci pre podpis.<\/span><\/p>\n

T\u00e1to inform\u00e1cia v\u00fdrazne upravuje p\u00f4vodn\u00fd v\u00fdsledok obidvoch kampan\u00ed, ke\u010f\u017ee <\/span>Kampa\u0148 B<\/b> vyzer\u00e1 by\u0165 v tomto pr\u00edpade v\u00fdkonnej\u0161ia, nako\u013eko vygenerovala o <\/span>22,5%<\/b> viac qualified leads – ktor\u00e9 z poh\u013eadu optimaliz\u00e1cie predstavuj\u00fa relevantnej\u0161ie publikum.<\/span><\/p>\n

Posledn\u00e1 f\u00e1za procesu predstavuje uzatvorenie dohody a teda skuto\u010dn\u00fa konverziu, ktor\u00e1 generuje revenue.<\/span><\/p>\n

\"Offline<\/a><\/p>\n

👉 Kampa\u0148 A<\/b> – zo 100 prejaven\u00fdch z\u00e1ujmov, len <\/span>5 konvertovalo<\/b> na re\u00e1lnu hodnotu (<\/span>CR – 5%<\/b>)<\/span><\/p>\n

👉 Kampa\u0148 B<\/b> – z 80 prejaven\u00fdch z\u00e1ujmov, len <\/span>10 konvertovalo<\/b> na re\u00e1lnu hodnotu (<\/span>CR – 12,5%<\/b>)<\/span><\/p>\n

A\u017e teraz m\u00f4\u017eeme skuto\u010dne predpoklada\u0165, \u017ee <\/span>Kampa\u0148 B<\/b> bola naozaj \u00faspe\u0161nej\u0161iou (<\/span>2,5x<\/b>).<\/span><\/p>\n

Custom CRM<\/b><\/h2>\n

Tak\u00e9to lieviky si spolo\u010dnosti v\u00e4\u010d\u0161inou dokumentuj\u00fa vo svojich CRM syst\u00e9moch<\/strong>, ktor\u00fdch integr\u00e1cie s reklamn\u00fdmi syst\u00e9mami s\u00fa \u010dasto kr\u00e1t nere\u00e1lne<\/strong> (najm\u00e4 pre men\u0161ie firmy), \u010di u\u017e kv\u00f4li technick\u00fdm, alebo finan\u010dn\u00fdm d\u00f4vodom.<\/span><\/p>\n

V \u010fal\u0161ej \u010dasti si uk\u00e1\u017eeme ako je mo\u017en\u00e9 prepoji\u0165 tak\u00e9to interakcie, ktor\u00e9 poch\u00e1dzaj\u00fa z onlinu, no konvertuj\u00fa offline,<\/strong> a ktor\u00e9 m\u00f4\u017eeme priamo pomocou identifika\u010dn\u00fdch parametrov vyu\u017ei\u0165 pre optimaliz\u00e1ciu kampan\u00ed napr. v Google Ads.<\/strong><\/span><\/p>\n

Pre tak\u00e9to \u00fa\u010dely si jednoduch\u00e9, plnefunk\u010dn\u00e9 CRMko vieme vytvori\u0165 s vyu\u017eit\u00edm 3 n\u00e1strojov<\/strong> <\/span><\/p>\n

👉 Google Sheets<\/span><\/p>\n

👉 Google Tag Manager<\/span><\/p>\n

👉 Zapier (data streamline).<\/span><\/p>\n

Na webe sa nach\u00e1dza formul\u00e1r, alebo in\u00fd element, ktor\u00fd zachyt\u00e1va a odosiela leady.<\/span><\/p>\n

\"Offline<\/a><\/p>\n

Pomocou GTM dok\u00e1\u017eeme tieto interakcie zachyt\u00e1va\u0165 a uklada\u0165 ich do pred-vytvoren\u00e9ho CRMka<\/strong>, kde sa parametre automaticky roztriedia.<\/span><\/p>\n

\"Offline<\/a><\/p>\n

Najpodstatnej\u0161ie s\u00fa pre n\u00e1s v tomto pr\u00edpade identifika\u010dn\u00e9 parametre<\/strong> ako GCLID<\/strong> (pr\u00edpadne WBRAID\/GBRAID<\/strong> – pre iOS\/app pou\u017e\u00edvate\u013eov), ktor\u00e9 google vyu\u017e\u00edva pre atrib\u00faciu kampan\u00ed. Odosiela sa v URL adrese alebo ako cookie _gcl_aw.<\/strong><\/span><\/p>\n

Tento parameter nemus\u00ed by\u0165 v\u0161ak v\u017edy dostupn\u00fd,<\/strong> preto je vhodn\u00e9 ho doplni\u0165 in\u00fdmi parametrami, ako je napr\u00edklad email alebo telef\u00f3nne \u010d\u00edslo, ktor\u00e9 taktie\u017e podporuj\u00fa presnos\u0165 atrib\u00facie.<\/span><\/p>\n

D\u00f4le\u017eitou inform\u00e1ciou je tie\u017e d\u00e1tum a \u010das, kedy pou\u017e\u00edvate\u013e vykonal interakciu (Timestamp resp. \u201cCONVERTED\u201d) a hodnota – v pr\u00edpade, \u017ee prich\u00e1dzaj\u00face leady maj\u00fa rozdielnu hodnotu.<\/span><\/p>\n

V praxi to bude vyzera\u0165 tak, \u017ee ke\u010f z\u00e1kazn\u00edk odo\u0161le formul\u00e1r, v CRMku sa zobraz\u00ed nov\u00fd riadok so statusom \u201cNew\u201d<\/strong> – pri \u00faprave prv\u00e9ho st\u013apca a teda zmene statusu z\u00e1kazn\u00edka sa odo\u0161le konverzia do Google Ads (pre ka\u017ed\u00fd krok je ide\u00e1lne ma\u0165 pripraven\u00fa samostatn\u00fa importovan\u00fa konverziu v Google Ads).<\/span><\/p>\n

Presun inform\u00e1ci\u00ed po splnen\u00ed podmienok v Google Sheets zabezpe\u010d\u00ed Zapier, ktor\u00fd automaticky za\u0161ifruje citliv\u00e9 d\u00e1ta a odo\u0161le konverziu v po\u017eadovanej forme<\/strong> do Google Ads..<\/span><\/p>\n

\"Offline<\/a><\/p>\n

..kde je mo\u017en\u00e9 s konverziami \u010falej pracova\u0165 a optimalizova\u0165<\/span>.<\/span><\/p>\n

\"Offline<\/a><\/span><\/p>\n

A samozrejme nezabudnite, ak potrebujete s analytikou pom\u00f4c\u0165, alebo m\u00e1te nejak\u00e9 ot\u00e1zky, nap\u00ed\u0161te n\u00e1m na cibula@dase.sk 🖖<\/strong><\/p>\n","protected":false},"excerpt":{"rendered":"

Prech\u00e1dzaj\u00fa va\u0161e slu\u017eby z onlinu do offlinu? Obsahuje v\u00e1\u0161 web formul\u00e1re, ktor\u00e9 si vy\u017eaduj\u00fa \u010fal\u0161ie akcie, aby sa…<\/p>\n","protected":false},"author":80,"featured_media":20284,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[639,1],"tags":[997,620,663,998,999],"_links":{"self":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/20266"}],"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=20266"}],"version-history":[{"count":3,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/20266\/revisions"}],"predecessor-version":[{"id":20285,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/posts\/20266\/revisions\/20285"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media\/20284"}],"wp:attachment":[{"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/media?parent=20266"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/categories?post=20266"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.dase-analytics.com\/blog\/sk\/wp-json\/wp\/v2\/tags?post=20266"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}