How to get more value from your Data Management Platform


We all know per­son­al­i­sa­tion is the key to engag­ing dig­i­tal cus­tomers. We also know that achiev­ing per­son­al­i­sa­tion at scale is no small feat. Even for Coca-Cola, one of the world’s most recog­nis­able brands, the move to dig­i­tal required a change in tac­tics. The com­pa­ny has no issues with aware­ness – its bev­er­ages are con­sumed by 18% of the world’s pop­u­la­tion each week! – but aware­ness and reach alone are no longer enough to dri­ve sales.

That is why Coca-Cola is “enter­ing a new chap­ter”. In the words of chief dig­i­tal offi­cer David Gods­man, “it’s a chap­ter of dig­i­tal trans­for­ma­tion. It requires us to deep­en our rela­tion­ships with our con­sumers, to per­fect the idea of mass per­son­al­i­sa­tion, which is not easy to do.”

To achieve per­son­al­i­sa­tion at scale, brands need to devel­op a bet­ter under­stand­ing of each cus­tomer they inter­act with, and that’s all about com­bin­ing all the data they col­lect from every avail­able source into a sin­gle cohe­sive cus­tomer view. There is no way they can han­dle this task or man­age all this data man­u­al­ly, which is why Data Man­age­ment Plat­forms (DMPs) rose to prominence.

Today, com­pa­nies are look­ing to build on this sin­gle cus­tomer view with a real-time under­stand­ing of their audi­ence across every dig­i­tal chan­nel, mark­ing the next phase on the matu­ri­ty ramp for DMPs.

Data Man­age­ment Plat­forms are maturing

Accord­ing to Gart­ner, 50% of brands already use a DMP in some capac­i­ty, either buy­ing their own or rely­ing on an exter­nal agency. The issue is that most of these busi­ness­es haven’t looked beyond the mar­ket­ing use case for their plat­form, which great­ly lim­its its potential.

The real val­ue of a DMP comes when you can apply the same lev­el of audi­ence insight to every inter­ac­tion with every cus­tomer across every touch point. With that, brands can bridge their dig­i­tal expe­ri­ence between chan­nels and engage cus­tomers in a way that feels con­sis­tent, rel­e­vant and tai­lored to their unique persona.

Thomas Vaarten, dig­i­tal direc­tor, A.S.Adventure agrees. In a recent Adobe report, he argues that, at this moment, the DMP is just viewed as a tool. In his eyes, it needs to evolve to be the cen­tre­piece and start­ing point for all cus­tomer com­mu­ni­ca­tions across all depart­ments – from per­for­mance mar­ket­ing to CRM to cus­tomer service.

His com­ments come fol­low­ing A.S.Adventure’s own trans­for­ma­tion. The com­pa­ny was pre­vi­ous­ly using a con­tent man­age­ment sys­tem, an email plat­form, a sys­tem for per­son­al­i­sa­tion and an ana­lyt­ics pack­age, but realised it need­ed a DMP to devel­op a sin­gle cus­tomer view. Addi­tion­al­ly, A.S.Adventure can now seg­ment its audi­ence more pre­cise­ly and use these seg­ments as the foun­da­tion for all of its dig­i­tal marketing.

Use data to engage new prospects

Anoth­er major appeal of DMPs is that they help brands entice peo­ple who are not already cus­tomers (as opposed to Cus­tomer Data Plat­forms, which are lim­it­ed to man­ag­ing exist­ing cus­tomer data). The dig­i­tal ecosys­tem is not just more com­pet­i­tive, it’s also much hard­er to get cut through with so much infor­ma­tion at your audience’s fin­ger­tips. The abil­i­ty to iden­ti­fy and con­vert unknown prospects is a valu­able dif­fer­en­tia­tor in this envi­ron­ment, which is why chal­lenger brands tak­ing a data-dri­ven approach have done so well.

Some­times even the sim­plest wins can have a big impact. Sandy Ghu­man, cam­paign plan­ning and deliv­ery coor­di­na­tor at Sky Insight and Deci­sion Sci­ence explains how the company’s DMP helped it opti­mise media spend: “The biggest user case was the media effi­cien­cy gain. We’re not wast­ing paid impres­sions to sell Sky to cus­tomers who already have Sky. Just the abil­i­ty to… iden­ti­fy those peo­ple and exclude them from any prospect activ­i­ty was a mas­sive efficiency.”

There is an impor­tant point to make about the qual­i­ty of data being fed into your Data Man­age­ment Plat­form. As the old IT indus­try phrase goes, ‘Garbage in, garbage out’. A DMP is a pow­er­ful tool for turn­ing raw infor­ma­tion into insight the busi­ness can use, but the qual­i­ty of that insight will only be as good as the qual­i­ty of infor­ma­tion on which it’s based. You can’t just dump any and all data into a DMP and expect it to spit out gold­en nuggets of intel­li­gence. It’s impor­tant to care­ful­ly select the infor­ma­tion that goes in DMP based on what you want to achieve.

A word on GDPR and data privacy

No dis­cus­sion about data man­age­ment is com­plete with­out explor­ing what this means for pri­va­cy, espe­cial­ly in the age of GDPR. One of the key require­ments of GDPR is that com­pa­nies must be able to show their cus­tomers which data they hold about them on request. This is extreme­ly dif­fi­cult to do if all a company’s data is held in dis­parate sys­tems, not to men­tion time-con­sum­ing. The fun­da­men­tal func­tion of a DMP is to con­sol­i­date a company’s data in one place, which dra­mat­i­cal­ly sim­pli­fies and speeds up this process.

DMPs also help com­pa­nies man­age how their data is shared, as well as the rules and per­mis­sions around how that data is used both inter­nal­ly and by exter­nal part­ners. For mar­keters who need to make deci­sions each day about which cus­tomer seg­ments to tar­get with spe­cif­ic cam­paigns or offers, DMPs can tell them not just who to con­tact but also whether they have per­mis­sion to do so.

Adding AI into the mix

Tra­di­tion­al­ly, the prac­tice of data man­age­ment and cus­tomer ana­lyt­ics has large­ly been descrip­tive, help­ing brands to explain an out­come based on the results of an action, like a cam­paign. More recent­ly, brands have been using data in a more pre­dic­tive way, draw­ing con­clu­sions about their cus­tomers’ future behav­iour based on his­tor­i­cal data so they can deliv­er a more per­son­alised user journey.

The ulti­mate aim is pre­scrip­tive ana­lyt­ics. Today, Arti­fi­cial Intel­li­gence (AI) is being baked direct­ly into data man­age­ment process­es so that brands can deter­mine the next best action for each cus­tomer at each point of their jour­ney, con­tin­u­ous­ly push­ing them one step clos­er to a purchase.

To make this hap­pen across mul­ti­ple chan­nels, in real time, and at scale, mar­keters need the help of intel­li­gent machines. That’s why the inte­gra­tion of AI direct­ly into DMPs promis­es to have a sig­nif­i­cant impact, help­ing users to dis­cov­er pat­terns of behav­iour in their data to inform bet­ter seg­men­ta­tion and smarter looka­like mod­el­ling. Cru­cial­ly, AI sys­tems are con­stant­ly learn­ing and adapt­ing, so that audi­ence seg­ments evolve in line with chang­ing cus­tomer behaviour.

Of course, the use of AI in data man­age­ment is still the domain of a select few com­pa­nies and risk-tak­ers, but change will come quick­ly as the approach begins to demon­strate how valu­able it is to engage cus­tomers in a more proac­tive way.

The dig­i­tal cus­tomer expe­ri­ence has become the new bat­tle­ground for mar­keters. And the keys to deliv­er­ing incred­i­ble per­son­alised expe­ri­ences at scale – cre­ativ­i­ty, con­ve­nience, rel­e­vance and time­li­ness – all hinge on a deep­er lev­el of cus­tomer under­stand­ing. A DMP may just be a piece of soft­ware, but it is also an invalu­able tool in help­ing brands get clos­er to their exist­ing audi­ence while also reach­ing new cus­tomers. In this way, a DMP done right is a dri­ver of organ­i­sa­tion­al change.

Read our full report on how the DMP is evolv­ing here. And vis­it our web­site to learn more about how Adobe Audi­ence Man­ag­er is help­ing brands mod­ernise their approach to cus­tomer data.

Jan Borgwardt

Posted on 10-24-2018

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