Mar­ket­ing In The Era Of Ma­chine Learn­ing

Dr. A.M. Sakk­thivel, Pro­fes­sor, Sky­line Univer­sity Col­lege, dis­cusses how com­pa­nies can use ma­chine learn­ing to at­tract and re­tain new cus­tomers.

Forbes Middle East - - GLOBAL MEETS LOCAL - www.sky­line­u­ni­ver­sity.ac.ae FORBESMID­DLEEAST.COM

Mar­ket­ing to­day is be­com­ing ex­tremely com­plex due to mount­ing com­pe­ti­tion and the dy­namic be­hav­ior of con­sumers. Com­pa­nies are al­ways look­ing for ways to man­age this and to reach out to tar­get con­sumers for their sur­vival, sus­tain­abil­ity, and of course, growth. How­ever, such meth­ods are eas­ily im­i­tated by com­peti­tors, lead­ing to the com­pany’s fail­ure to cre­ate ex­cite­ment and value to tar­get con­sumers.

To­day’s con­sumers are en­joy­ing the ben­e­fits of­fered by com­pa­nies and they move around to wher­ever they can get bet­ter bar­gains and ben­e­fits. Such a move forces com­pa­nies to con­stantly cre­ate and of­fer pro­mo­tions to at­tract con­sumers to gen­er­ate much-needed rev­enues to run their busi­nesses. Such con­sumers are called “price war­riors” and com­pa­nies can’t profit and grow when they fo­cus too much on them.

In­stead, com­pa­nies should cre­ate a loyal and con­tribut­ing con­sumer base to achieve their ex­pected profit and growth. Cre­at­ing a loyal con­sumer base is a her­culean task, as com­pet­ing com­pa­nies will con­stantly tar­get and at­tract con­sumers through their con­tin­u­ous pro­mo­tional of­fers. How­ever, com­pa­nies should hold on to their ex­ist­ing con­sumers and con­vert them into loyal cus­tomers by cre­at­ing con­stant ex­cite­ment, sur­prises, and ben­e­fits.

How does a com­pany cre­ate con­tin­u­ous ex­cite­ment and sur­prises to make sure that its ex­ist­ing con­sumers come back and spend more money? This is where the role of tech­nol­ogy in mar­ket­ing comes in. Com­pa­nies can use tech­nol­ogy for ad­ver­tise­ments, com­mu­ni­ca­tions, events, and ser­vices to at­tract con­sumers and re­tain their loy­alty.

With peo­ple’s ever-short­en­ing at­ten­tion span, com­pa­nies need to use tech­nol­ogy that is highly in­ter­ac­tive and mul­ti­fac­eted. This re­quires com­pa­nies to de­sign an in­te­grated sys­tem of mar­ket­ing that in­cludes cap­tur­ing con­sumer data, an­a­lyt­ics, and the de­vel­op­ment of AI sys­tems that in­cludes ma­chine learn­ing de­signed to de­velop and act on its own with the right train­ing and in­struc­tions.

Nu­mer­ous com­pa­nies are ex­per­i­ment­ing with ma­chine learn­ing and us­ing it in dif­fer­ent mar­ket­ing as­pects such as the mon­i­tor­ing and mea­sur­ing of off­line and on­line con­sumer buy­ing be­hav­ior, de­cid­ing on prof­itable dy­namic pric­ing, en­sur­ing sales, tar­get­ing ef­forts to­wards rel­e­vant mar­ket, gen­er­at­ing per­son­al­ized pro­mo­tional of­fers, mea­sur­ing web­site ex­pe­ri­ences, iden­ti­fy­ing sen­ti­ments of tar­get con­sumers, and pre­dict­ing and gen­er­at­ing counter-mea­sures to cus­tomers’ churn rate, among oth­ers.

Ma­chine learn­ing could be of more use in prod­ucts and ser­vice-ori­ented or­ga­ni­za­tions that re­quire fre­quent foot­fall from con­sumers to gen­er­ate rev­enues for their sur­vival, sus­tain­abil­ity, and growth. It is, there­fore, im­por­tant to gen­er­ate clean and enor­mous amounts of data because it will help the ma­chine learn­ing sys­tem train and un­der­stand pat­terns of pur­chase of prod­ucts and ser­vices and for it to make prediction­s and alert the com­pa­nies of what is com­ing.

It’s also im­por­tant to set the pri­or­i­ties and func­tions while train­ing the ma­chine learn­ing sys­tem to suit the re­quire­ments of a com­pany, such as pre­dict­ing con­sumer churn, pre­dict­ing their next big spend­ing, pre­dict­ing most fa­vor­able prod­ucts/ser­vices to make per­son­al­ized pro­mo­tions, and even per­son­al­ized pric­ing to at­tract con­sumers.

Al­though the ma­chine learn­ing sys­tem is an au­tonomous one, it is im­por­tant to have con­tin­u­ous hu­man in­ter­ac­tions and in­ter­ven­tions to align ma­chine learn­ing with the on­go­ing strate­gic and op­er­a­tional as­pects of a com­pany. Such align­ment will en­able the sys­tem to in­her­ently un­der­stand re­quire­ments and pat­terns of the com­pany’s strate­gic and op­er­a­tional as­pects to aptly gen­er­ate suit­able and use­ful re­sponses. Hence, com­pa­nies need to fo­cus on us­ing sys­tems like ma­chine learn­ing for their mar­ket­ing strate­gies and de­sign them for greater use. Do­ing this will help com­pa­nies suc­cess­fully nav­i­gate the tur­bu­lent wa­ters of the mar­ket with its ever-mount­ing com­pe­ti­tions and the ever-chang­ing con­sumer be­hav­ior.

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