Vatengesi vari kunyura mune data. Asi kana zvasvika kune chaihwo, ruzivo rune musoro, rwakaoma. Iwe unoziva kunzwa. Kunyepedzera kuti zvese zviri pasi pesimba paunenge uchifamba pakati pemadhibhodhi asingaverengeki, akavhurika tebhu uye neshanduro dzespredishiti rimwechete, kupinza nhamba dzinopa kusimbiswa uye gwara. Tese tavepo. Vatungamiri havadi mamwe data kana madhibhodhi kuti vawane mhinduro dzavari kutsvaga. Vanoda hungwaru hunoratidza "nei" kuseri kwemaitiro evateereri kuitira kuti vasiye kukumbira ruregerero nekushandisa mari, uye vatange kuita nekukurumidza bhizinesi sarudzo nechivimbo. Izvo zvinotanga neiyo yakasimba, yakachena data hwaro. Iyo inoshanda martech stack haisi yekuunganidza nekugadzirisa zvisizvo maturusi anopira kutendeseka kwedata. Ndezvekubvisa izvo zvandinodaidza kuti "mutero wakaoma" -kupokana kwezvisarudzo zvishoma uye mikana yakarasika iyo inotambudza zvikwata zvekushambadzira kana data isingayerere seamless. Sezvineiwo, isu tiri kufamba kubva munyika yekungoita, yakarembera uye isina kurongeka data kuenda kunguva iyo hungwaru hwemagariro hunogonesa vatungamiriri kunzvenga mutero wakaoma, kuratidza ROI yavo uye kuwana sarudzo yekukurumidza. Chii chinonzi martech stack? Iyo yekushambadzira tekinoroji stack, kana martech stack, ndiyo sutu yezvishandiso uye matekinoroji anoshandiswa nevashambadzi kukwezva, kubatikana uye kuchengetedza vatengi. Kubva pane inotungamira chizvarwa uye email kushambadzira kusvika pasocial media manejimendi uye SEO, aya maturusi anofambisa mafambiro ebasa, otomatiki maitiro uye anopa yakakosha kuita kwekuita. Iyo yakanaka martech stack iri mune inogara ichiita iteration. Sezvo tekinoroji mamiriro achishanduka pamwe nekusimuka kweagent AI, zviri kuita kushandura akakura uye akapatsanuka metrics kuita inzwi rakajeka remutengi rondedzero. Yakabatana martech stack inofambiswa nehungwaru hwemagariro inomhanyisa kukurumidza-kune-njere, inopa masimba kuvaka, uye inopa vatengesi maonero akazara ebhizinesi uye zviri kuitika pamusika izvozvi. Iyo 'yakaoma mutero': Nei agile kushambadzira tekinoroji ichirova legacy masisitimu Kunyangwe paine mukana weAI-inotyairwa martech stacks, zvikwata zvakawanda hazvisi kuona madzoro emari avaitarisira. Sei? Nekuti makumi matatu nenhanhatu muzana evatungamiriri vanoti zvivakwa zvenhaka zvinopinda munzira, maererano neConstellation's 2025 Assessing Agentic Enterprise Readiness Report. Bloated legacy system inodzivirira data kubva mukuyerera kwemahara pakati pematashi, kugadzira silos uye manyore workaround anodonhedza timu zviwanikwa. Mutengo we bloat uyu unoshamisa. McKinsey akawana kuti 63% yeCMOs vakarasikirwa nemikana nokuti vakanga vasingakwanisi kuita sarudzo nokukurumidza zvakakwana, uye mushumo weConstellation wakawana kuti imwe 42% haigoni kubata inzwi remutengi. Mazhinji masangano ekushambadzira achiri kubhadhara mitengo yepamberi yehungwaru hwebhizinesi yechinyakare uye CRM masisitimu anongoteedzera rekodhi yakarongeka yekare (kureva, izvo zvakatoitika mukati mebhizinesi).
Kufambisa kukura, izvo zvikwata zvinoda huchenjeri hwemagariro: iyo chaiyo-nguva, isina kurongeka mamiriro emusika (kureva, chii chiri kuitika izvozvi). Sekureva kweSprout Social's 2025 Impact yeSocial Media Report, hafu yevatungamiriri vanoda zvikwata mubhizinesi rese senge ruzivo rwevatengi uye kubudirira, kutarisirwa kwevatengi nerutsigiro, uye kusimudzira bhizinesi kushandisa ruzivo rwemagariro kuzivisa sarudzo dzavo. Hungwaru hwemagariro huchabatsira zvikwata izvi kuti zvifambe kubva pakuongorora zvakapfuura kuenda kune remangwana nekuona zvine hungwaru. Zvikamu zvakakosha zvemartech stacks zvinotamisa iyo data firehose Kune akawanda maturusi emhando (kunyanya mabhureki emabhizinesi) anoshandisa kuunganidza nekuchengetedza data. Nhau dzakanaka ndedzekuti mabhureki ane data rakawanda-kutenderedza gumi petabytes, paAssessing Agent Enterprise Report. Nhau dzakaipa ndedzekuti iyo data firehose yakaiswa pakakwirira, uye masisitimu enhaka haana kuvakwa kuti abvise zvinyorwa zvitsva zve data isina kurongeka. Chirevo chimwechete chakawana kuti 70% yedata rekushambadzira haina kurongeka, kusanganisira nhaurirano dzemagariro, mavhidhiyo uye mifananidzo. Maturusi echinyakare emartech anongogadzirirwa data rakarongeka (senge fomu rinozadza uye nekudzvanya) uye kutadza kutora iyo yakachena, isina kusefa yevateereri inowanikwa pamatanho senge kushamwaridzana uko kwakavanda mikana chaiyo. Magadzirirwo emartech stack yako anoenzanisa yakarongeka uye isina kurongeka dhata zvinoenderana nesangano rako zvakasarudzika zvinodiwa uye zvinonyanya kukosha, asi mamwe maturusi ane hwaro mumaindasitiri. Heano zvimwe zvakakosha izvo zvinofanirwa kuverengerwa mune inoshanda martech stack:
Maturusi ehungwaru ezvemagariro enhau: Demokrasi inogonesa kuwana ruzivo rwemagariro, uyeinopa iyo martech ecosystem ine mamiriro ebhizinesi data uye chaiyo mutengi nzwisiso inoshandura ruzha kuita inobatika bhizinesi masaini, uye inodyisa iyo chaiyo-nguva mamiriro kumashure muCRM. Inobvumira vashandisi kuita chiito mune imwe yepakati, yakagadziridzwa chikuva. Kushambadzira otomatiki software: Inofambisa kudzokorora mabasa uye kutumirwa kwedanidziro, kusunungura zvikwata kuti zvitarise pane zvine hungwaru zvirongwa. Mutengi wehukama manejimendi (CRM) maturusi: Inoisa pakati data yevatengi uye inopa ruzivo rwekuti kuedza kwekushambadzira kunokanganisa sei mhedzisiro yekutengesa. Zvemukati manejimendi masisitimu (CMS): Masimba mawebhusaiti uye mablogiki, anoshanda sedhijitari yekumberi gonhi rekuita kwevatengi. E-mail ekushambadzira mapuratifomu: Inogonesa kugadzirwa kweemail, otomatiki uye analytics kurera inotungamira uye kugara yakabatana nevateereri. Generative injini optimization (GEO) maturusi: Inobatsira nekuwedzera AI-powered kutsvaga masimba. Kutsvaga injini optimization (SEO) maturusi: Aids ane kiyi yekutsvagisa, chinzvimbo chekutevera uye backlink ongororo yekusimudzira kuoneka kwehupenyu. Kushambadzira tekinoroji: Inovhara maturusi ekutsvaga injini yekushambadzira (SEM), inoratidza ads uye mamwe anobhadharwa chiteshi kutyaira traffic. Mapuratifomu eAnalytics: Inopa nzwisiso yakakosha mukuita kwewebhusaiti uye kushambadzira ROI kutungamira sarudzo dzinofambiswa nedata. Digital asset manejimendi (DAM) masisitimu: Inoronga uye inochengeta midziyo yedhijitari, zvichiita kuti zvive nyore kuwana uye kushandisa zvakare zvirimo mukati memishandirapamwe.
Maitiro ekugadzira martech stack inopa sarudzo velocity Ndisati ndagovera dhizaini inoshanda yekuongorora uye kuvaka patsva yako martech stack, ndinofanira kujekesa mutsauko wakakosha pakati pekumhanya uye velocity. Kumhanya kunoreva kuti ndava kupinda mumota ndichipomba gasi. Ndiri kuenda nekukurumidza sezvandinogona kwenguva yakareba sezvandinogona. Asi ndicho chinhu pamusoro pekukurumidza. Hazvidi gwara kana kukanganisa. Velocity inoita. Velocity = kumhanya + kutungamira. Zvinoreva kuti iwe unonyatsoziva kwauri kuenda, uye iwe unogona pivot ipapo ipapo zvichibva pamasaini emusika. Kana iwe uchifamba nevelocity, unoenda kumberi nechinangwa, uchishingairira kutsvaga maitiro uye kushandura njere kuita chiito. Iwe une zvishandiso zvaunoda kuongorora uye kudzokorora sezvaunoenda. Mukuita, izvo zvinotaridzika senge martech stack yakavakirwa kugadzirisa zvese nhoroondo uye chaiyo-nguva ruzivo kuti vatungamiriri vagone kuita nekukurumidza, sarudzo dziri nani. Heano matanho aungatora kuti ufambe nekukurumidza uine chivimbo. Tsanangura dambudziko kana chinodiwa chauri kuedza kugadzirisa Vanhu havaunganidze zvakare matekinoroji avo nekuti vanoda. Vanozviita nokuti pane dambudziko rinoda kugadziriswa. Nyatsojeka pane chaizvo kuti timu yako inogona kubatsirwa sei kubva kune yakasanganiswa social media intelligence mhinduro, ingave iyo yakanyatso tarisisa yeako yekutengesa funnel, mugove wezwi kana hukama hwevatengi. Izvi zvichabatsira yako IT timu kunzwisisa zviri nani zvaunokoshesa uye zvaunoda. Ongorora maturusi ako uye kugona kwedata Ongorora yako yazvino martech stack nekutarisa zvakanyanya pachishandiso chega chega, kuongorora kuti inopinza sei uye ongorora isina kurongeka data. Kana iwe usingakwanise kusvika kune "nei" kuseri kwema data data, yako data nheyo haina kusimba seimba yemakadhi uye haina kusimba zvakakwana kuti iwe uvake zano kutenderedza. Kubatanidzwa uye kutendeseka kwedata ndiwo mafuta anoita sarudzo velocity inogoneka. Kana suite yako ichibata manzwisisiro emagariro seyekuwedzera yakavharirwa kana dhibhodhi rakavharika, uri kurasikirwa ne70% yezwi remutengi wako. Data yemagariro inofanirwa kunge yakaita sematishu akabatana anoyerera muCRM yako uye bhizinesi rehungwaru maturusi ekugadzira yakazara hungwaru ecosystem. Tsanangura mhedzisiro yebhizinesi yakatarisana nemhedzisiro Kwenguva yakareba, vatengesi vane intuitively vanozivikanwa data isipo iyo yaizoratidza zvizere mabatiro ebasa ravo. Takashaya mufananidzo uzere, tisingakwanise kuona kuti mishandirapamwe yedu yakapesvedzera sei kugoverana kwezwi nemanzwiro. AI-inotungamirwa nehungwaru hwemagariro inoita kuti zvikwanise kusanganisa kwakasiyana data masosi uye kubvunza mibvunzo mitsva. Sekuti, ndakasvika ani uye vakaita sei? Takabudirira kupi? Takatadza papi? Yemazuva ano martech stack inofanirwa kupa iwo manzwisisiro aunoda kuti ukurumidze nguva kubva pakubuda kuenda kumari, kushandura sarudzo kuita chiito ine laser-yakatarisana mhedzisiro mupfungwa. Rongedza pane zvakachinjika-zvinoshanda zvinodiwa uye zvakakosha Rongedza stack uko masaini emagariro anokonzeresa zviito mune mamwe madhipatimendi. Kana yakagovaniswa zvinobudirira, data yemagariro inofanirwa kuvhara mukaha pakati pekushambadzira, kutengesa, sevhisi uye kutengeserana. Somuenzaniso, funga nezve e.l.f. Cosmetics 'ichangoburwa chigadzirwa innovation iyo yakaziviswa nemutengimaitiro paTikTok. Iyo mhando yakaona vatengi vachigovana ma hacks ekubvisa lipgloss mabhodhoro kuti vagone kugadzirisa avo. Panzvimbo pekuti timu yemagariro ingotaura "kuda izvi," nzwisiso yakakwidziridzwa kune zvigadzirwa nezvikwata zvekutengesa, uye mhando yakatanga kukwidziridzwa kutsva. Pamadhora gumi nemashanu ega ega akashandiswa pa e.l.f. zvigadzirwa, vatengi vakagamuchira yemahara isina lipgloss mudziyo, inonzi (S) e.l.f. Yakagadzirwa Halo Gloss Bhodhoro. Chigadzirwa chacho nokukurumidza chakatengeswa kunze. Ndiko kumhanyisa kwekuita sarudzo.
Vakira ramangwana Hazvina mhosva kuti uripi parwendo rwako rwekushandisa kweAI, unofanirwa kuve nechokwadi chekuti stack yako ndeye agent AI-yakagadzirira. AI chikara chisingaguti chinoda kugara uchidya kwedata revanhu kuti rirambe richibatsira, uye hungwaru hwemagariro hunopa chirongwa chekudya chakakwana. Izvo zvakakoshawo kukwidziridza hungwaru hwemagariro saka iwe uripo apo vatengi vako vari kutaura uye vachibvunza mibvunzo nezve brand yako, indasitiri nezvimwe, kuti mhando yako ive mhinduro inemvumo yeLLMs. Sezvo isu tichifamba kubva kuSEO kuenda kunguva inotongwa neGEO, chiremera chinozove mari yebhizimusi 'yakanyanya kuwanikwa. Famba nekumhanya, kwete kuomarara “Shumba haifaniri kudzvova kuratidza kuti ishumba.” Ndiwo chirevo chandinoda kuti mushambadzi wese atende, vakabata musoro wavo kumusoro vachiziva nechivimbo kuti vane hungwaru hwezvivakwa zvekugadzira zvinofungidzirwa, kukura kwakanyanya. Hapasisina kukumbira ruregerero nekushandisa mari, kunyangwe isu tichiziva bhizinesi redu, indasitiri uye mutengi pamwe nemunhu wese. Yave nguva yekushandura data redu uye dashboards kubva kune reactive scorecard kuenda kune yekufungidzira mukana wemari. Bvunza Sprout's Social Media Buyer's Guide kuti uve nechokwadi chekuti une zvivakwa zvekuwana izwi rechokwadi remutengi. The post Kuvaka martech stack: Kubvisa mutero wakaoma wesarudzo velocity yakatanga kutanga Sprout Social.
