NEVER COLD CALL AGAIN An ex­tract from our 2016 re­port Big Data and the Fu­ture of Prospect­ing

WE LIVE in an age of ‘con­sumerism’ where po­ten­tial clients have more in­for­ma­tion on us than ever. But it is also true that we can ac­cess a whole lot more in­for­ma­tion that en­ables us to be smarter at mar­ket­ing to them. To­gether with CoreLogic Aus­tralia, El

Elite Agent - - CONTENTS -

Never cold call again. Par­don the pun, but it does have a great ring to it, right? With tools now avail­able, it is pos­si­ble to pre­dict a vast ar­ray of hu­man life changes, well be­yond the four ‘tra­di­tional Ds’ of real es­tate: death, di­vorce, debt and de­par­ture. Th­ese life events might in­clude hav­ing a baby, teenagers leav­ing the nest, a change in jobs, trends in spend­ing pat­terns and much more. In turn, this knowl­edge can lead to bet­ter com­mu­ni­ca­tion with your cur­rent and prospec­tive cus­tomers. Rather than call­ing peo­ple you don’t know out of the blue, it is pos­si­ble to get close to pre­dict­ing which house, in a street, in an area, is most likely to list next – and then use smart meth­ods of con­tent mar­ket­ing to at­tract them to to you. It’s not science fic­tion; it’s here to stay, thanks to some clever data and an­a­lyt­ics.

Our panel started the dis­cus­sion by agree­ing that the term ‘big data’ is largely un­known and/or mis­un­der­stood. “Agents are not data­base ad­min­is­tra­tors, so there is a learn­ing gap on how to get the data main­tained,” says Brook.

Says Priv­ett, “Typ­i­cally [we have been] given the big data def­i­ni­tion which is all about the ‘fun stuff’ we can do with it. [My] def­i­ni­tion is that it is data that’s too big to be han­dled in the tra­di­tional ways. You can’t use it on one server, one of­fice, you can’t an­a­lyse it in the stan­dard way that we’re used to. That usu­ally means that it’s broad; it’s got mul­ti­ple sources, mul­ti­ple agents, and is dis­parate un­til you do the work to clean it and make it use­ful.”


An area where Brook be­lieves there is a wide gap in knowl­edge is to do with the ad­van­tages that could be gained if data was to flow seam­lessly be­tween fran­chise of­fices and head of­fice, some­thing that is be­ing over­looked by many real es­tate brands. While some are suc­cess­fully shar­ing data, he says, most busi­nesses would be amazed at how much crossover there is right now be­tween buy­ers, sell­ers, ten­ants and land­lords. Three or four dif­fer­ent fran­chisees might be speak­ing with the same per­son, which re­ally no longer needs to hap­pen. “We’ve just gone through the process of sell­ing and buy­ing, and I’m be­ing con­tacted through three dif­fer­ent of­fices from the same fran­chise,” says Brook. Greater Data is work­ing with some of the larger fran­chises to bring their data to­gether with more in­tel­li­gence and co­he­sion.


De­spite the per­ceived fran­chisor/ fran­chisee gap, there is now a ca­pa­bil­ity in over­lay­ing con­sumer be­hav­iour in­sights onto prop­erty data to al­low smart tar­get­ing to con­sumers. Pre­vi­ously the in­dus­try has had ac­cess to prop­erty data via CoreLogic but lit­tle in­for­ma­tion about the per­son/ peo­ple in the prop­erty. Big data and an­a­lyt­ics mar­ries the two.

Around this ta­ble alone, there are three dif­fer­ent ‘propen­sity to list’ mod­els. “Th­ese guys,” says Brook, re­fer­ring to Quan­tium and Data Repub­lic, “have a huge amount of be­havioural in­for­ma­tion, and we’ve got the de­mo­graphic and life stage in­for­ma­tion to be able to pre­dict when some­one is able to do some­thing.

“Specif­i­cally our in­ter­est is in bridg­ing that gap with an­swer­ing the ques­tion of what your ex­ist­ing cus­tomers are do­ing. How can you main­tain that [as­so­ci­a­tion] and con­tinue to seg­ment your mes­sag­ing to get the right mes­sage across to the right per­son at that time?” says Brook.

Says Driscoll, “There is now an abil­ity to be able to ‘sec­ond guess’ peo­ple – just based on con­sumer be­hav­iours, their ev­ery­day lives. The re­al­ity of the sit­u­a­tion is that we [the real es­tate in­dus­try] are all fight­ing at the ‘bot­tom of the fun­nel’ at the mo­ment, and as a re­sult it be­comes a bloodbath. We un­der­cut each other on fees… but if you can get fur­ther to­wards the top of the fun­nel you are far

more likely to have sen­si­ble con­ver­sa­tions that should demon­strate value long be­fore that per­son looks to list a prop­erty.”


While Brook has al­ready men­tioned the work that Greater Data is do­ing with some of the fran­chises, Quan­tium has been work­ing with CoreLogic on a prod­uct called SmartList, a prod­uct that some com­pa­nies, like Starr Part­ners, are al­ready us­ing.

Says Liao, “[SmartList] es­sen­tially is tak­ing all the in­for­ma­tion we have about house­hold­ers plus the 9.8 mil­lion or so prop­er­ties here in Aus­tralia (through CoreLogic’s data), ty­ing that to­gether with all of the mar­ket trend data anal­y­sis in­for­ma­tion and con­sumer in­sights data. Then we try to pre­dict who is more likely ready to sell through con­sumer be­hav­iour and also whether the area has been good with re­cent sales.” The out­put of this is peo­ple who are more likely to sell, a warm list of prospects.

“With all pre­dic­tive mod­el­ling there is no 100 per­cent cer­tainty. It’s about high­light­ing and iden­ti­fy­ing the peo­ple who are more likely based on their be­hav­iour.”


Driscoll has been us­ing the SmartList prod­uct for a cou­ple of months and is one of the first in the in­dus­try to do so. He notes that the data is im­pres­sive but there are a cou­ple of chal­lenges that they need to come to terms with as a busi­ness to get the most out of the sys­tem.

“The num­bers we are talk­ing about is that one in 10 peo­ple will list their house in six months, and one in five within 12 months. They are pretty im­pres­sive num­bers.

“But it’s all about the ap­proach. You’ve got a list of names and num­bers, so you’ve got to fig­ure out the ap­proach for con­tact­ing th­ese peo­ple. Is it a mail­box drop, is it an intelligent let­ter, is it an email, is it a phone call? So that is where we are still try­ing to come to grips with it. But so far so good.”

Liao agrees; it is still go­ing to come down to the con­ver­sa­tions a real es­tate agent sub­se­quently has with those prospects. “You have to un­der­stand the be­hav­iour be­hind the al­go­rithms that iden­ti­fied them in the first place to in­crease your chances of con­vert­ing the list­ing.”

Davis also ac­knowl­edges this. “You can’t have peo­ple ring­ing prospects and say­ing, ‘our data says you are about to sell’. So now we need to have a con­ver­sa­tion about how to man­age the slightly creepy side of big data and how do you ‘de-creep’ it.

“Un­der no cir­cum­stances can you have a con­ver­sa­tion that says, ‘I know all th­ese things about you’. It’s more about pro­vid­ing the right in­for­ma­tion that ‘mag­i­cally’ turns up at the right time or when you’re in the right headspace for it.”


One of the main el­e­ments of feed­back from clients, says Liao, is not be­ing able to ac­ti­vate di­rectly the in­sights that big data pro­vides. As a re­sult, Quan­tium has part­nered with Face­book, as a me­dia ac­ti­va­tion chan­nel, and cre­ated more than 150 seg­ments (QSeg­ments) across con­sumer-type be­hav­iour, so­ciode­mo­graph­ics, prop­erty at­tributes and more. Says Liao, “This al­lows our cus­tomers to tar­get spe­cific types of peo­ple that they want to talk to on Face­book.” Like any mar­ket­ing, whether it’s ad­ver­tis­ing or con­tent mar­ket­ing – it then comes down to the cre­ative and how ap­peal­ing that hap­pens to be. But you can be smarter at creat­ing a mes­sage if you know where you want the mes­sage to land.

Says Brook, “If a real es­tate agent is ad­ver­tis­ing on Face­book with a mes­sage that just says, ‘List your house now’, it doesn’t re­ally ap­peal to any­one. If you’ve got a pic­ture of a lovely house in the ’burbs with a young fam­ily hold­ing up two kids [and that hap­pens to be your au­di­ence] the mind tells you, ‘That’s me, they’re talk­ing to me. This res­onates bet­ter with me [as a cus­tomer]. This is more rel­e­vant’.”

Over the last few years, notes Cobb, it has been harder to reach peo­ple on Face­book, no mat­ter what in­dus­try you are in, un­less you now pay Face­book to pro­mote your post. In fact Cobb has been work­ing di­rectly with his real es­tate clients with the CoreLogic and Quan­tium QSeg­ments and says the re­sults have been out­stand­ing in both cost re­duc­tions and con­ver­sions.

“On the prop­erty-re­lated ads that we’ve been run­ning for a se­lect group of clients [us­ing QSeg­ments] on Face­book, specif­i­cally pro­mot­ing a prop­erty or de­vel­op­ment of some kind... we’ve been able to re­duce that cost for the same re­sult by up to sixty per cent,” says Cobb.

“When it comes to con­tent, we spend a lot of time talk­ing about the top of the fun­nel: at­tract­ing peo­ple to our busi­ness through help­ful con­tent, whether that be life­style or re­lated ar­ti­cles, how-tos or es­tab­lish­ing some­one as the lead­ing au­thor­ity in their lo­cal mar­ket. We’ve seen up to a 70 per cent de­crease in the cost per con­ver­sion be­cause what we’re do­ing is es­sen­tially be­ing more rel­e­vant to the peo­ple that mat­ter only to our busi­ness.”

Says Cobb, “It has al­lowed our clients to de­ter­mine, ‘Well, I’m spend­ing four thou­sand dol­lars on DL cards or off­line mar­ket­ing, tra­di­tional things that real es­tate agents do… [or] I’m spend­ing a thou­sand dol­lars over here on Face­book.’ The dif­fer­ence be­tween the two is when it’s dig­i­tal it’s far more mea­sur­able and you can de­ter­mine, ‘Is my money bet­ter spent over here?’ We would never sug­gest ‘can­cel this one for this one’. But you can make a much more ed­u­cated de­ci­sion on where you’re go­ing to spend your money.”


Many of our pan­elists ex­pressed con­cerns dur­ing the con­ver­sa­tion about the cur­rent state of the in­dus­try in both train­ing on big data and also stor­age of ex­ist­ing data. “If data­bases are still held in Ex­cel at fran­chisee level, if we don’t have the abil­ity to un­der­stand ex­ist­ing data, we can’t, with con­fi­dence, step into big data,” says Brook. “To un­der­stand ac­qui­si­tion prop­erly you re­ally need to un­der­stand what ex­ist­ing cus­tomers look like.”

Driscoll be­lieves this to be the re­sult of a lack of the right type of train­ing to equip the in­dus­try with the skills it needs to un­der­stand the op­por­tu­ni­ties and the po­ten­tial. “One of the ma­jor is­sues is to do with up­skilling. We’re still rolling out the same kind of train­ing as an in­dus­try that we were 20 years ago. This isn’t fu­tur­is­tic stuff; this is stuff peo­ple in other in­dus­tries are do­ing now.”

The big data loop also does not stop with sim­ply get­ting your data in or­der. It’s about hav­ing a con­tin­ual feed­back loop and learn­ing more from your ex­pe­ri­ences to ben­e­fit the in­dus­try as a whole.

Says Owed, “If you’re us­ing SmartList, which is de­rived from big data… when you cap­ture a re­sponse, it en­ables a whole new set of data to be col­lected. So what is the mes­sage that you de­liv­ered? What re­sponse did you get back? Then feed that back into the al­go­rithm. The amaz­ing thing about big data is you are not just lim­ited to one point in time; the data you col­lect has a net­work ef­fect that you can keep build­ing. It’s a con­tin­u­ous cy­cle and it’s re­ally phe­nom­e­nal.”

Words: Sa­man­tha McLean. Our full re­port, in­clud­ing video, will be avail­able at­data in late Oc­to­ber. For more in­for­ma­tion about Quan­tium QSeg­ments or SmartList, email us: sup­

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