DATA RE­ALLY IS BET­TER

THE RISE OF ALL THINGS DIG­I­TAL IS DRIV­ING EX­PO­NEN­TIAL GROWTH IN THE IN­FOR­MA­TION AVAIL­ABLE TO COM­PA­NIES AND THE ABIL­ITY TO PROCESS IT. IT’S EAS­IER AND MORE EX­CIT­ING THAN YOU THINK.

The Australian - The Deal - - Extra - An­drew Bax­ter is the chief ex­ec­u­tive of Ogilvy Aus­tralia. Fol­low him on Twit­ter: @an­drew­bax­ter3.

THE MAR­KET­ING CATCH­PHRASE of the past 12 months has been “big data”. Two sim­ple words that are both daunt­ing and ex­cit­ing. Daunt­ing in that there are 2.5 quin­til­lion bytes of data cre­ated glob­ally ev­ery day. Ex­cit­ing in that it can be a game-changer for busi­nesses, with pro­duc­tiv­ity and profit gains of be­tween 5 per cent and 6 per cent bet­ter than com­peti­tors, ac­cord­ing to re­cent re­search.

The term big data was orig­i­nally coined in Sil­i­con Val­ley nearly 20 years ago as film houses raced into the world of com­puter-gen­er­ated im­agery and spe­cial ef­fects, and needed ma­jor leaps in data stor­age to do so.

At the same time, di­rect mar­keters be­came more so­phis­ti­cated, and em­braced busi­ness in­tel­li­gence and an­a­lyt­ics, al­beit in a very man­ual and time-con­sum­ing way. In more re­cent times, the rise of all things dig­i­tal has driven ex­po­nen­tial growth in avail­able data, both within com­pa­nies and ex­ter­nally. And when you add to­day’s abil­ity to au­to­mate pre­dic­tive mod­el­ling, it is no won­der busi­ness in­tel­li­gence and an­a­lyt­ics folk have adopted Sil­i­con Val­ley’s far sex­ier term.

Still, the fun­da­men­tals of data an­a­lyt­ics have not changed. Col­lect data on your cus­tomers, pay at­ten­tion to what that data is say­ing, and with that knowl­edge or in­sight, de­liver a rel­e­vant so­lu­tion. But mar­keters face an in­creas­ingly com­plex data en­vi­ron­ment in the quest to drive busi­ness growth. And con­sumers have a far higher ex­pec­ta­tion of com­pa­nies get­ting those so­lu­tions right, and of re­ceiv­ing them im­me­di­ately. But is it as daunt­ing as busi­nesses are mak­ing out?

While there has been in­cred­i­ble growth in avail­able data, there have been even big­ger leaps in com­put­ing stor­age and power. Data an­a­lyt­ics pro­grams that took hours to run five years ago take min­utes to­day. And al­though there are­many more sources of in­for­ma­tion be­yond a com­pany’s own data­bases, such as so­cial me­dia, smart­phones and the web, most have been cre­ated in the dig­i­tal age where there is a far more stan­dard­ised data struc­ture. So bring­ing that data to­gether to as­sem­ble a sin­gle view of the cus­tomer, the holy grail for mar­keters, is much eas­ier than a fewyears ago.

The wealth of ex­ter­nal data we are gath­er­ing about our­selves is a ma­jor fac­tor in the big data equa­tion. This in­di­vid­u­alised data is gen­er­ated and cap­tured by a range of con­nected de­vices. For ex­am­ple, us­ing GPS track­ing data, my phone told me that I’d walked 29km last month and at a more gran­u­lar level it also cap­tured that I had been to four dif­fer­ent shop­ping cen­tres. As mar­keters start ex­plor­ing how this lo­ca­tion and be­havioural data can be put to use in highly rel­e­vant and per­son­alised com­mu­ni­ca­tions, the op­por­tu­ni­ties rack up quickly.

Wal­mart and Tar­get are two huge US retailers that have em­braced big data. They both have a strong vi­sion for us­ing that data. They have built strong data­bases that pro­vide a solid stream of con­sumer be­hav­iour in­sights, en­abling them to tai­lor of­fers. They’ve more re­cently added the abil­ity to over­lay ex­ter­nal data, such as cus­tomers’ mo­bile phone lo­ca­tions and the weather con­di­tions. The re­sult is even more rel­e­vant and timely com­mu­ni­ca­tions. The end game will be rel­e­vant of­fers de­liv­ered to cus­tomers as they shop in those stores, based on real-time data and in­sights.

Busi­ness such as th­ese, as well as Ama­zon andT-Mo­bile, are lead­ing the charge in the US, part of the 68 per cent of US busi­nesses that un­der­took big-data ini­tia­tives in 2012. Yet only 32 per cent of Aus­tralian busi­ness lead­ers said they had done so last year.

Aus­tralian brands such as Qan­tas, Vir­gin, Myer, Coles and Wool­worths have the ad­van­tage of large in­ter­nal data­bases built off loy­alty pro­grams. Those pro­grams pro­vide ter­rific op­por­tu­ni­ties for de­vel­op­ing deep pur­chase-be­hav­iour knowl­edge and, in turn, per­son­alised and rel­e­vant of­fers and ser­vice. So they are well ad­vanced in em­brac­ing big data, and will be even fur­ther down that path when they over­lay ex­ter­nal data.

For busi­ness peo­ple who feel they’re still at the start­ing point, it’s im­por­tant to over­come the daunt­ing con­fu­sion about where to start. Take sim­ple first steps. De­velop a great plan for data based on how it will help de­liver the goals of the busi­ness. Or be­gin col­lect­ing data and stor­ing it in a way that can be eas­ily ac­cessed by the right tal­ent down the track. Or use small pock­ets of that data to test and learn. Then it’s one step at a time, rather than try­ing to fig­ure out how to leap straight to big data nir­vana. Ama­zon’s big data play didn’t hap­pen overnight. But by tack­ling it one chunk at a time, the pos­si­bil­i­ties are now ex­tremely ex­cit­ing.

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