{"id":18811,"date":"2016-05-24T00:00:00","date_gmt":"2016-05-23T22:00:00","guid":{"rendered":"https:\/\/trilogi.com\/blog\/models-datribucio-de-vendes\/"},"modified":"2016-05-24T00:00:00","modified_gmt":"2016-05-23T22:00:00","slug":"models-datribucio-de-vendes","status":"publish","type":"post","link":"https:\/\/trilogi.com\/blog\/ca\/models-datribucio-de-vendes\/","title":{"rendered":"Models d\u2019atribuci\u00f3 de vendes"},"content":{"rendered":"

Imagina una jugada del F.C. Barcelona. Despr\u00e9s d\u2019un c\u00f3rner de l\u2019equip rival, el porter inicia el contraatac amb una bona sacada de porteria a mig camp; despr\u00e9s Iniesta agafa velocitat i arriba a tres quarts de camp, i finalment fa una passada a Neymar, que centra a Messi i marca. A qui atribu\u00efm el gol: a Trilogi<\/a>? Nooo, a Messi!<\/strong> Per\u00f2 en realitat no tot el m\u00e8rit \u00e9s seu<\/strong>, sin\u00f3 de tots els jugadors que han participat en la jugada. Ara b\u00e9, el problema sorgeix a l\u2019hora de decidir quina intervenci\u00f3 ha estat m\u00e9s important, si \u00e9s que n\u2019hi ha una que ho sigui m\u00e9s que una altra. Aquest \u00e9s el mateix problema que hem de resoldre per decidir a quin canal donem l\u2019atribuci\u00f3 de vendes.<\/p>\n

\"models<\/p>\n

En l\u2019anal\u00edtica web passa una cosa molt semblant en l\u2019an\u00e0lisi dels canals amb qu\u00e8 l\u2019usuari ha interactuat abans de finalitzar la compra.<\/p>\n

Qu\u00e8 s\u00f3n els models d\u2019atribuci\u00f3 de vendes?<\/strong><\/h2>\n

Segons Google, un model d\u2019atribuci\u00f3 \u00e9s una regla o conjunt de regles<\/strong> que determina com s\u2019assigna el valor de vendes i conversions als punts de contacte de les rutes de conversi\u00f3.
\nD\u2019aquesta manera podem donar rellev\u00e0ncia als diferents canals d\u2019adquisici\u00f3 de tr\u00e0nsit en funci\u00f3 de com definim la contribuci\u00f3 de les conversions a cadascun.
\nHi ha diferents models d\u2019atribuci\u00f3 de les vendes a Google Analytics (GA).
\nPer explicar-los posarem un exemple d\u2019interacci\u00f3 abans d\u2019una venda i l\u2019assignaci\u00f3 que fa GA segons cada model d\u2019atribuci\u00f3.<\/p>\n

Un usuari accedeix per primera vegada al nostre web des d\u2019un anunci d\u2019AdWords. La setmana seg\u00fcent hi torna a accedir, per\u00f2 aquesta vegada fent clic en una xarxa social. Aquell mateix dia torna per tercera vegada al nostre web a trav\u00e9s d\u2019una campanya d\u2019email m\u00e0rqueting i, finalment, una hora m\u00e9s tard torna a entrar al nostre web de manera directa i fa una compra.<\/p>\n

\"models\"<\/p>\n

A continuaci\u00f3 veurem com es reflecteix aquesta conversi\u00f3 segons el model d\u2019atribuci\u00f3 que fem servir.<\/p>\n

    \n
  1. \u00daltima interacci\u00f3 (4a interacci\u00f3 del gr\u00e0fic)<\/strong>
    \nAssigna el valor de la venda a l\u2019\u00faltim punt de contacte amb el web abans de la venda. A l\u2019exemple, l\u2019assignaci\u00f3 seria 100% al canal directe.<\/li>\n
  2. \u00daltim clic indirecte (3a interacci\u00f3 del gr\u00e0fic)<\/strong>
    \nS\u2019exclou tot el tr\u00e0nsit directe durant la interacci\u00f3, i tot el cr\u00e8dit de la venda s\u2019assigna a l\u2019\u00faltim canal en qu\u00e8 el client ha fet clic abans de la conversi\u00f3. A l\u2019exemple, l\u2019assignaci\u00f3 seria 100% a email m\u00e0rqueting (correu electr\u00f2nic).<\/li>\n
  3. \u00daltim clic d\u2019AdWords (1a interacci\u00f3 del gr\u00e0fic)<\/strong>
    \nS\u2019assigna tot el valor de la venda a l\u2019\u00faltim clic que fa un usuari en una campanya d\u2019AdWords. A l\u2019exemple hi ha un primer i \u00faltim clic a AdWords que s\u2019enduria el 100% del cr\u00e8dit de la venda.<\/li>\n
  4. Primera interacci\u00f3 (1a interacci\u00f3 del gr\u00e0fic)<\/strong>
    \nEl primer punt de contacte s\u2019emporta el 100% del cr\u00e8dit de la conversi\u00f3. A l\u2019exemple tamb\u00e9 seria la cerca de pagament (AdWords).<\/li>\n
  5. Lineal<\/strong>
    \nEn aquest model s\u2019assigna el mateix percentatge de la venda a cada punt d\u2019interacci\u00f3 des de l\u2019inici fins que es produeix la venda.
    \nA l\u2019exemple s\u2019assignaria un 25% a cadascun dels 4 canals: cerca de pagament, xarxa social, correu electr\u00f2nic i directe.<\/li>\n
  6. Deteriorament del temps<\/strong>
    \nEn aquest model s\u2019assigna un percentatge m\u00e9s elevat als punts de contacte m\u00e9s propers en el temps al moment de la venda o conversi\u00f3.
    \nA l\u2019exemple, els canals que rebrien el m\u00e0xim cr\u00e8dit s\u00f3n correu electr\u00f2nic (3a interacci\u00f3) i directe (4a interacci\u00f3), ja que s\u00f3n els canals amb qu\u00e8 l\u2019usuari ha interactuat hores abans de produir-se la venda.<\/li>\n
  7. Segons la posici\u00f3<\/strong>
    \nEn aquest cas s\u2019assigna un 40% a la primera i a l\u2019\u00faltima interacci\u00f3, i el 20% restant es distribueix de manera uniforme entre les interaccions interm\u00e8dies, \u00e9s a dir, un 10% al canal que correspon a xarxa social i un altre 10% al canal que a l\u2019exemple correspon a correu electr\u00f2nic.<\/li>\n<\/ol>\n

    Seguint amb l\u2019exemple, si tenim en compte que la venda que s\u2019ha produ\u00eft \u00e9s d\u2019un import de 2.000 \u20ac, l\u2019atribuci\u00f3 es faria de la manera seg\u00fcent:<\/p>\n

    \"taula-exemples\"<\/p>\n

    Per defecte, Google Analytics (GA) t\u00e9 en compte 30 dies en l\u2019an\u00e0lisi de les interaccions. De tota manera, aquesta configuraci\u00f3 es pot canviar de manera f\u00e0cil i r\u00e0pida, dins del l\u00edmit de 0 a 90 dies. \u00c9s important saber que per defecte GA sempre ens mostra els informes amb el model d\u2019atribuci\u00f3 d\u2019\u00faltim clic indirecte, \u00e9s a dir, \u00faltim clic menys el tr\u00e0nsit directe. Tamb\u00e9 hem de tenir en compte que es poden atribuir vendes al canal offline mitjan\u00e7ant el Measurement Protocol<\/strong> d\u2019Analytics.<\/p>\n

    Models personalitzats<\/strong><\/h2>\n

    Si no ens conven\u00e7 cap dels models d\u2019atribuci\u00f3 definits per GA, podem crear un model nou totalment diferent o b\u00e9 seleccionar-ne un dels existents com a base i modificar-lo.
    \nEs pot crear un model personalitzat des de l\u2019Eina de models d\u2019atribuci\u00f3, modificant la finestra de temps (dies abans de la conversi\u00f3), ajustant el cr\u00e8dit assignat segons la interacci\u00f3 (temps al lloc, nombre de p\u00e0gines vistes o aplicant una regla personalitzada) i altres elements addicionals relacionats, com la posici\u00f3 a la ruta, la campanya, la paraula clau, etc.<\/p>\n

    Aquesta eina no nom\u00e9s serveix per comparar resultats de diferents models d\u2019atribuci\u00f3 \u2014fins a un m\u00e0xim de tres\u2014, sin\u00f3 que tamb\u00e9 avalua l\u2019efic\u00e0cia dels diferents canals. Aix\u00f2 ens permetr\u00e0 prendre millors decisions d\u2019inversi\u00f3 en funci\u00f3 dels resultats obtinguts.<\/p>\n

    I tu, quins models d\u2019atribuci\u00f3 fas servir?<\/strong><\/p>\n

    Si tens qualsevol consulta, pots posar-te en contacte <\/a>amb nosaltres: a Trilogi<\/a> estarem encantats d\u2019assessorar-te i ajudar-te.<\/p>\n","protected":false},"excerpt":{"rendered":"

    Imagina una jugada del F.C. Barcelona. Despr\u00e9s d\u2019un c\u00f3rner de l\u2019equip rival, el porter inicia el contraatac amb una bona sacada de porteria a mig camp; despr\u00e9s Iniesta agafa velocitat i arriba a tres quarts de camp, i finalment fa una passada a Neymar, que centra a Messi i marca. A qui atribu\u00efm el gol: […]<\/p>\n","protected":false},"author":2,"featured_media":12671,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1739],"tags":[],"class_list":["post-18811","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-tecnologia"],"yoast_head":"\nModels d\u2019atribuci\u00f3 de vendes | Blog Trilogi \u2013 The Digital Agency<\/title>\n<meta name=\"description\" content=\"Imagina una jugada del F.C. Barcelona. 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