Maitiro ekuwana mukana wekukwikwidza mune diki eCommerce neBig Data

Maitiro ekuwana mukana wekukwikwidza mune diki eCommerce neBig Data

Kuongororwa kwedata rakapihwa ne Big Data uye kushandisa kwavo kunogona kupa vatengesi muCommerce chikamu chakakosha competitive advantage. Big Data ishoko rinoshandiswa kune ese akarongeka uye asina kurongeka data seti ayo akakurisa zvekuti zvinonetsa kugadzirisa uchishandisa echinyakare dhatabhesi uye software software. Kunyangwe pakutanga zvingaite sekunge kushandiswa kweBig Data kunongowanikwa kune vatengesi vakuru, muchokwadi ese eCommerce inogona kubatsirwa, kunyangwe iri diki sei.

ari data rakarongeka ye Big Data ndiwo masisitimu akasarudzika mukati me database, semuenzaniso, data remunhu wese revatengi kana nhoroondo yavo yekutenga. isina kurongeka data vanoreva email, mavhoti, maTweets, "likes" kana "share" pasocial media. Hapana imwe yeiyi data isina kurongeka inogara mune yakagadziriswa dhatabhesi inogona kuwanikwa nevatengesi; zvisinei, iwo anobatsira kwazvo ekutsvaga kwekushandisa kumakambani.

Vatengesi vanogona kushandisa mavhoriyamu makuru e data muzviitiko zvakawanda zvakasiyana. Izvi zvinogona kusanganisira kuenzanisa traffic iyo chimwe chigadzirwa chinogashira kuhuwandu hwekutengesa hweichi chigadzirwa. Kana chigadzirwa chikagamuchira kushanya kwakawanda asi kushoma kwekutengesa, kuongororwa kwedata rakawanikwa kunogona kupa tsananguro inotungamira mukuchinja kwesarudzo kana kuwanikwa kweimwe mhando yekukanganisa.

Iyo 4V's yeBig Data

ari matambudziko inosangana neBig Data inopfupikiswa mune izvo zvave kunzi ma4V's: vhoriyamu, kumhanya, kwakasiyana uye kukosha.

  • Dambudziko re volume Iripo nekuti makambani mazhinji anogadzira yakawanda yakawanda data kupfuura avo masisitimu anokwanisa kubata.
  • Dambudziko re  velocity Izvo zvinonetsa kana ongororo yedata kana yekuchengetedza ichinonoka kupfuura chizvarwa chayo (semuenzaniso, kana usina chitoro chepamhepo uine huwandu hukuru hwekutengeserana kamwechete).
  • Dambudziko re zvakasiyana-siyana Izvo zviripo nekuda kwekuda kwekugadzirisa mhando dzakasiyana dze data kuti dzibudise izvo zvinodiwa (zvemagariro enhau dhata, nhare yebasa revatengi, shanyira data, chiyero chekutenga, nezvimwewo)
  • Dambudziko re kukosha  Izvo ndezvekuti tinoita sei kuti ruzivo rwunopihwa rwakakosha, nekuti chete nekubvunza mibvunzo chaiyo ndipo patinowana mhinduro dzinobatsira.

Iyo diki eCommerce inogona kushandisa sei Big Data

Vazhinji vatengesi vanotenda kuti hombe data analytics inongowanikwa kumakambani makuru. Nekudaro, kuongororwa kwedata kwakanyanya zvakare yakakosha kumabhizimusi madiki zvigadzirwa zvemagetsi uye zvakakosha kuti kukwikwidza neakakura kwazvo, kunyanya avo vanogona kudyidzana nevatengi vavo munguva chaiyo.

Para tora mukana wekushandisa kweBig DataVatengesi vadiki vanofanirwa kuzvishandisa kugadzirisa zviito, kugadzira mitengo ine simba, kupa vatengi zvirinani, kubata hunyengeri, kurondedzera nezvekuwanikwa chaiko kwechigadzirwa uye chinzvimbo chekutenga kwakaitwa, uye kufanotaura nezveramangwana.

Kuita somunhu

Mutengi wese ane nzira dzakasiyana dzekutenga. Yechokwadi-nguva dhata inofanirwa kushandira kukupa iwe wakasarudzika chiitiko icho chinongedzera zviri zviviri zvirimo uye kukwidziridzwa, kusanganisira kupa mubayiro vatengi vakavimbika uye vanodzoka vatengi.

Mitengo ine simba

Kuita izvi ndiko kuwana mukana wakakura kana uchikwikwidza mutengo mumusika. Kwavari zvakakosha kufunga nezve mutengo wemakwikwi, huwandu hwekutengesa, izvo zvinodiwa nevatengi zvinoenderana nedunhu, nezvimwe.

Basa remutengi

Yakanakisa basa revatengi muzvikamu zvese zvakakosha kuti ubudirire eCommerce. Iyo kudyidzana yevatengi kuburikidza nemafomu ekutaurirana kana makomendi pasocial network zvinogona kushandiswa kuwedzera kuvandudza sevhisi inopihwa kumutengi mumwe chete iyeye. Mhinduro yacho inokurumidza uye mutengi achanzwa zvirinani kushandirwa.

Kubiridzira

Kutenda kune Big Data zvinokwanisika kuona kubiridzira pakutanga, kunyangwe munguva chaiyo. Zvivakwa zvinodiwa izvi zvinoshandura chitoro chepamhepo kuita nharaunda yakachengeteka yekusimudzira bhizinesi uye ichavandudza purofiti yako.

Kuonekwa kwedata yechigadzirwa uye chinzvimbo chekutenga

Vatengi vanotarisira kuzoziviswa nezve iyo kuwanikwa chigadzirwa chaicho kana iwe uchafanirwa kumirira uye, kana zvirizvo, kwenguva yakareba sei. Uye zvakare, zvakakosha kuti muchengeti azive nezve echimiro chekutenga kwako, saka unogona kugara uchiziva kuti zvigadzirwa zvako zviripi uye uve nechokwadi chekuti zvinodzorwa.

Kufungidzira kweramangwana

Izvo zvakakosha kuti bhizimusi rikwanise kufungidzira kutengesa kwayo zvakanyanya sezvinobvira kuti ive zvakachengetwa uye zvakare ndakagadzirira ku logistics nhanho.

CONCLUSIONS

Zvinogona kutaridza sebasa rinotyisa, asi kufambira mberi muhunyanzvi uye makwikwi makuru akagadzwa pakati pevanopa e-commerce uye kushambadzira mhinduro zvinoreva kuti matambudziko aya anogona kutarisana nediki eCommerce. Iko kiyi haisi yekuzvidza bhizinesi diki nekuti iri online, asi tora mukana chaiwo wehukuru hwayo hudiki kumira kunze uko ma greats anonyanya kuomerwa. Asi pane izvi iwe unofanirwa kupinda mumutambo wevakuru uye shandisa zvombo zvavo.

Mamwe mashoko - Mazano ekugadzirisa nekuvandudza eCommerce muna 2014


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  1. Inotarisira iyo data: Miguel Ángel Gatón
  2. Chinangwa cheiyo data: Kudzora SPAM, manejimendi manejimendi.
  3. Legitimation: Kubvuma kwako
  4. Kutaurirana kwedata
  5. Dhata yekuchengetedza: Dhatabhesi inobatwa neOccentus Networks (EU)
  6. Kodzero: Panguva ipi neipi iwe unogona kudzora, kupora uye kudzima ruzivo rwako