Kukurukurirana - 

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Kukurukurirana - 

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Attribution modelling ndiyo nzira yekuongorora kukanganiswa kwezviyero zvekushambadzira pakutendeuka. Mukupa kwekuenzanisira, data revatengi rinoongororwa kuongorora basa renzira dzakasiyana dzekutengesa mukuunza mari. Nhasi vatengesi vanobatana nevanotarisira vatengi kuburikidza nenzira dzakawanda senge Social Media (Facebook, Twitter, LinkedIn), Adwords, blogs, affiliate network, Websitena nezvimwe. Kana munhu wekupedzisira paanotendeuka zvinonetsa kuziva chero munhu anobata seye chete mari jenareta.

Mumazuva ekutengesa kwechinyakare, zvaive nyore kuyera kukanganisa kwekutaurirana kwekushambadzira. Kana iwe ukadhinda shambadziro mupepanhau uye ukaona iyo 20% inowedzera mukutengesa iwe unobva waziva kuti yaishanda. Ikozvino nematanho mazhinji, zvinova zvakafanira kushandisa yekumisikidza modelling kuyera iyo ROI yekushambadzira kuyedza.

Read More: Maitiro Ekufanofungidzira Anotevera Anotenga Ekutenga Kwekunaka Muchinjikwa-kutengesa?

Nei Ndichifanira Kufunga Nezve Attribution Modeling?

Attribution modelling yakakosha sezvo iriyo chete mhinduro kumubvunzo wakambobvunzwa - wakashanda here? Inopa mhinduro kune vashambadziri nekuongorora zvinoitika mukushambadzira zvirongwa uye nekuvabatsira kunatsa zano ravo. Hedzino nzira shoma idzo dzekufananidzira modelling dzinogona kubatsira.

  • Kuratidza iyo ROI yekushambadzira: Attribution modelling inogona kuyera kukanganiswa kwenzvimbo dzakasiyana dzevatengi ekubata uye kuratidza maitiro avanopindirana kuburikidza nenzira dzakasiyana vasati vazopedzisira kutenga chigadzirwa (kana sevhisi). Nenzira iyi iwe unogona kuratidza kuti kushambadzira kwako kuri kukanganisa sei rwendo rwevatengi.
  • Kuwana nzira dzinoshanda: Attribution modelling hairatidzi chete kuti kushambadzira kwakakosha asi zvakare kunoongorora chikamu chezana remakero akasiyana mukutendeuka. Nenzira iyi iwe uchazoziva zviri kushanda uye chii chisiri.
  • Kududzira Rwendo rweMutengi: Rwendo rwemutengi rwuri kuramba ruchioma. Maererano ne KISSMetrics98% yevashanyi vesaiti yako havazotenge pakushanya kwavo kwekutanga. Nekushandisa yekumisikidza modelling iwe haugone chete kuyera kukanganiswa kwenzira dzekutengesa asiwo mashandiro anoita mutengi anobatana neaya mageru munguva yese yekutenga.

Read More: Maitiro ekuwana chaiwo mitengo nekutarisa kwekugadzirisa?

Mhando dzeApa Attribution Models Sarudza kubva:

chii chinonzi Attribution Modeling

Sarudzo yemhando yemuenzaniso inogona kusiyana zvichienderana nerudzi rwe bhizimisi. Kana iwe uri kuronga kushandisa attribution modelling saka zvakanaka kuve nekunzwisisa kwakaoma kwe dzakasiyana mhando dzekupa mhando kuitira kuti iwe ugone kuita sarudzo kwayo.

1. Kubatana kwekutanga:

Kudyidzana kwekutanga kunopa kukosha kwese kune yekutanga kubata iyo yakaunza kusangana mukambani. Iyi modhi ine mhosva zvakanyanya nekuti iri kupa 100% kukosha kune imwe chiteshi. Kunze kwepamusoro pefunnel, nzira dzese dzakasara dzinorambwa kuzivikanwa mukuunza bhizimisi kukambani. Nekusimbisa kwakawanda pakushambadzira kwefunnel, nzira iyi haifanirwe kusarudzwa chero bhizimisi.

2.Kubatana kwekupedzisira:

Kudyidzana kwekupedzisira kwakapesana chaizvo kwekutanga kudyidzana. Inopa zvese kukosha kune chiteshi izvo zvakazoguma zvachinja vatengi. Nekupa 100% kiredhiti kuchiteshi chekupedzisira iyi nzira inoregeredza basa rakaitwa pamusoro nepakati peiyo faneli yekushambadzira. Iyi nzira ichiri kuita zvine musoro kana yako yakanangana nekuona chete nzira dzinoshandura uye nekudzisimudzira pane pekutanga.

3.Kupedzisira Kusina Kunanga Kutaurirana:

Muchiitiko chekudyidzana kwekupedzisira kusiri-kwakananga, tarisiro ichiri pane yekupedzisira inoshandura chiteshi kunze kwekushanya kwakananga. Iyi yekuenzanisira modhi inofuratira kushanya kwakananga nekuti inofungidzirwa kuti kana munhu achiuya akananga kune saiti kupfuura iye atoziva nezve ako masevhisi. Kunze kwekusiyana uku, iyi nzira zvakare inoisa kusimbisa kwakafanana pazasi peiyo fanera yekushambadzira.

4. Linear:

Mune mitsara ine modhi, ese nzira dzekushambadzira dzinopihwa kukosha zvakaenzana zvisinei nenzvimbo yavo mune yekushambadzira fanera. Izvi zvinoreva kuti kana mutengi akapfuura nemana kutaurirana kwekushambadzira asati atendeuka ipapo idzi nzira ina dzichapihwa kukosha kwe4% imwe neimwe. Iyi inzira inoshanda kana iwe uchida kuyera kukosheswa kwekushambadzira seyakazara. Izvo hazvinyatso kushanda kuyera kugona kwemataneru akasiyana ega.

5. Nguva Yekuora:

Munguva yekuora kwemuenzaniso, iyo yekubata padyo padyo neshanduro inopihwa kukosha kwakanyanya. Zorora ese mageru akagoverwa muzana chikamu mukutendeuka zvichienderana nedaro ravo kubva pakushandura chiteshi. Semuenzaniso, kana paine mana chiteshi ipapo chinoshandura chechina chiteshi chinogoverwa 4% chinzvimbo nepo 4rd, 40 ne3 chiteshi chakapihwa 2%, 1%, uye 30% basa zvichiteerana. Uyu muenzaniso wakanaka wekuona nzira dzekushandura uchipa kukosha kwakakodzera kune vechipiri masvikiro.

6.Position Kubva:

Mune chinzvimbo-chakavakirwa modhi, zvimwe zvinzvimbo zvinopihwa kukosha kupfuura vamwe. Kazhinji, chiteshi chekutanga chinounza mutengi uye chiteshi chekupedzisira chinochishandura chinopihwa kusimbiswa ukuwo nzira dzekutengesa dziri pakati pefaneli dzichipihwa kukosha kwakaderera Panyaya yedu yemakiteshi mana ekushambadzira, yekutanga uye yekupedzisira chiteshi inogona kupihwa 40% kukosha imwe neimwe apo yasara 20% inogona kugoverwa pakati pechipiri & chechitatu chiteshi. Uyu muenzaniso unoshanda kwazvo sezvo zviine musoro kupa kukoshesa kumatanho ane mabasa akakosha kupfuura mamwe masvikiro.

Basa reBig Data mune Attribution Modeling:

Munyika yose rwendo rwevatengi, tarisiro inotaurirana neakawanda renji yedhijitari. Izvi zvinosanganisira organic yekutsvaga, kuratidza kushambadza, kuratidzwa, evanhu vezvenhau kutaurirana nezvimwewo Kupa kuzivikanwa kwese kune ekupedzisira kushandura nzira kunodzikisira kumwe kushambadzira kutaurirana. Asi iri harisi kana iro dambudziko chairo. Haisi iyo chete yekushambadzira chiteshi asi zvakare iyo frequency, kudzokorora, uye kuteedzana kweaya ekubata mapoinzi anobatsira kutendeuka. Saka unoongorora sei huwandu hwakakura hwedata uye nekushandisa modhi yekupa?

Ikoko ndiko kuongorora kukuru kwedata inouya yekutamba. Big data maturusi ekuongorora akadai Hadoop inogona kuunza simba rekufananidza kugadzirisa nekwaniso yekubata huwandu hwakawanda hweasina kurongeka data. Maturusi aya anouyawo nekwaniso yekusimudzira iyo data iri mu Bvisa-Shanduko-Mutoro (ETL) nhanho uye gadzira composite metrics inogona kufanotaura zvirinani bhizimisi performance. Nokushandisa Hadoop, mamodheru emhando anogona kugadzirwa kuti averenge chikonzero-uye-mhedzisiro pese pakawanda zviitiko kana zviitiko zvinoitika zvinogona kukanganisa chimwe mhedzisiro.

Read More: Mashandisiro ekushandisa nzvimbo-based kushambadzira kuita yako mutengi kutaurirana?

Zvinoita sei NewGenApps Gadzira Attribution Models:

At NewGenApps, isu takanangana nekugadzira iyo Dhijitari Media Attribution Model iyo inokonzeresa kune ese organic traffic, zvinowoneka uye PPC kushambadza kudzvanya kwakaitika pamberi pechiitiko chekushandurwa, uye kugadzira matriki matsva (frequency, kudzokorora uye kuteedzana) izvo zvinogona kuyera kushanda kweakasiyana dhijitari midhiya zviitiko mukupindura kudyidzana neayo ekutengesa kutaurirana. Nerubatsiro rweiyi ongororo, isu tinokurudzira kurudziro yekumisikidza midhiya kushandisa pamatanho akawanda ekutengesa

Izvi ndizvo zvatakaita kune mamwe macustomer chaiwo. Zvichienderana nezvako bhizimisi modhi, nzvimbo yekutarisa uye nzira yekushambadzira isu tinogara tichikurudzira kuti uwane yakasarudzika maitiro emhando yakagadzirirwa yako bhizimisi. Nekugadzira chimiro chetsika iwe unogona kuve nechokwadi chekuti iwe unogadzira uye kuongorora data yakakosha kune yako bhizimisi uye kwete kutevera mamwe maitiro nekuda kwayo chete. Kana uri kutsvaga vanoongorora bhizinesi ndiani anogona kugadzira zvirevo zvemhando dzakananga kune yako bhizimisi modhi wobva wakasununguka kutibata nesu.

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