Optimising FSI Customer Experiences, Part 2: Content Velocity

Dig­i­tal mar­ket­ing has nev­er been eas­i­er in some ways, or more dif­fi­cult in oth­ers. Even as data gives us more pow­er to iden­ti­fy each cus­tomer and deter­mine what they want, con­sumers expect per­son­alised, rel­e­vant expe­ri­ences, and they expect those expe­ri­ences to work seam­less­ly across every device they use.

In this series of arti­cles, we’re analysing the five key com­po­nents of opti­mis­ing your FSI cus­tomers’ jour­ney: bring­ing data togeth­er, cre­at­ing indi­vid­u­alised con­tent, lever­ag­ing deci­sion­ing and algo­rithms, deliv­er­ing flu­id expe­ri­ences across chan­nels, and con­tin­u­ing to test, learn, and opti­mise over time.

We’ve already spo­ken about data—how to iden­ti­fy who the cus­tomer is and what con­tent we should show—and explored key con­cerns around uni­fy­ing data and hav­ing a KPI frame­work. But once we’ve got that data, the next piece of the puz­zle is to cre­ate the per­son­alised con­tent our cus­tomers expect.

Google’s 2014 Zero Moment of Truth sur­vey found that cus­tomers engaged with 10.4 pieces of con­tent before mak­ing a pur­chase, and that num­ber has only increased since then. What’s more, a recent Nielsen sur­vey found that cus­tomers are five times more depen­dent on con­tent than they were five years ago.

Forrester’s study Prov­ing the Val­ue of Dig­i­tal Asset Man­age­ment reports that most brands are cre­at­ing more than 10 times the assets they used to, in order to sup­port today’s pro­lif­er­a­tion of new chan­nels. A full 76 per­cent of those brands agree that con­sumers’ expec­ta­tion for per­son­al­i­sa­tion increas­es the need for assets.

In short, con­sumer expec­ta­tions, new chan­nels, and the per­son­al­i­sa­tion expec­ta­tion all cre­ate demand for great con­tent. But how do we actu­al­ly go about deliv­er­ing that con­tent?

Free­dom with­in con­sis­ten­cy

We want to give our design­ers and cre­ative teams the free­dom to cre­ate, with­in the lim­its of brand con­sis­ten­cy and guide­lines. That means we need tem­plates. It also means we need to give our cre­ative teams access to the right tools, and put the right work­flows in place to enable them to collaborate—both with each oth­er and with out­side cre­ative agencies—as well as to lever­age user-gen­er­at­ed con­tent from cus­tomers. The goal is to speed up the entire cre­ative work­flow, at scale. This is where I have seen organ­i­sa­tions adopt tra­di­tion­al agency mod­els, or pub­lish­er mod­els, to suc­cess­ful­ly deliv­er con­tent quick­ly and effi­cient­ly.

Once you’ve opti­mised the process of cre­at­ing new con­tent, you need to man­age it from a cen­tral repository—a dig­i­tal asset man­age­ment (DAM) sys­tem, which gives you the abil­i­ty to search for con­tent. To achieve that search­a­bil­i­ty at scale, you’ll need machine learn­ing to analyse and extract the seman­tic con­tent of an image, and to auto­mat­i­cal­ly tag images with help­ful key­words. You’ll also want your DAM to inte­grate with oth­er sys­tems, whether that’s enter­prise resource plan­ning (ERP) or a con­tent man­age­ment sys­tem.

Anoth­er key ben­e­fit of a DAM sys­tem is the abil­i­ty to auto­mat­i­cal­ly gen­er­ate hun­dreds of dif­fer­ent vari­a­tions of the same asset, each tai­lored for a par­tic­u­lar screen res­o­lu­tion, band­width, or cus­tomer seg­ment. Each of these assets may start with the same back­ground image—or with a range of images you’ve specified—then dynam­i­cal­ly over­lay many ver­sions of mes­sages and calls to action (CTAs), each to be deliv­ered to a par­tic­u­lar cus­tomer at a spe­cif­ic time, on a cer­tain chan­nel.

Assem­bling all those assets by hand would take years of labour, but a cut­ting-edge con­tent man­age­ment sys­tem can assem­ble mil­lions of them on the fly, and deliv­er them as need­ed.

Opti­mi­sa­tion and ben­e­fits

Now that you’re deliv­ered mil­lions of per­son­alised assets at scale, it’s time to start opti­mis­ing your cam­paigns. A dig­i­tal con­tent man­age­ment sys­tem makes this much eas­i­er, because it records ana­lyt­ics on every asset it deliv­ers. This means you’ll be able to run A/B and mul­ti­vari­ate tests on each ver­sion of every asset, analysing its per­for­mance in ways that will help you opti­mise its con­tri­bu­tion to the user expe­ri­ence as a whole.

One obvi­ous ques­tion is, “How does each asset con­tribute to rev­enue?” As your ana­lyt­ics come rolling in, you’ll be able to start per­son­al­is­ing assets even fur­ther, by bring­ing that real-time per­for­mance data back to your design­ers, explain­ing which audi­ence seg­ments espe­cial­ly like which types of con­tent, and assign­ing them to focus on cre­at­ing more con­tent that’s like­ly to res­onate.

This data-dri­ven process not only mit­i­gates risk, it also dri­ves engage­ment by mak­ing con­tent more inter­ac­tive, and break­ing down com­mu­ni­ca­tion bar­ri­ers as you learn more about what your audi­ence seg­ments want and expect. Mean­while, it also helps you stream­line pro­duc­tion by cut­ting down on repet­i­tive tasks, and elim­i­nates the costs of cre­at­ing redun­dant or use­less assets. Most of all, the right cre­ative process­es help you go to mar­ket faster, and reach each of your cus­tomers with pre­cise­ly the right mes­sage before your com­peti­tors do.

On-demand data man­age­ment

Finan­cial ser­vices firm UBS had a world­wide port­fo­lio of mar­ket­ing assets, includ­ing a flag­ship glob­al web­site offer­ing more than 50,000 pages in mul­ti­ple lan­guages, high­light­ing finan­cial plan­ning ser­vices, cred­it cards, and a wide range of oth­er prod­ucts. How­ev­er, with­out a cen­tralised repos­i­to­ry for the vast amount of assets required to sup­port mar­ket­ing, media, and e-com­merce, UBS was slow to launch new cam­paigns, updates, and events.

By switch­ing to an on-demand DAM plat­form, UBS improved col­lab­o­ra­tion with its video pro­duc­tion teams, and with agen­cies han­dling oth­er types of asset cre­ation. They strength­ened brand man­age­ment and con­sis­ten­cy and improved their abil­i­ty to share large files, as well as to col­lab­o­rate with inter­na­tion­al offices and exter­nal ven­dors, achiev­ing a quick time-to-val­ue on their invest­ment.

The results have been strik­ing. UBS has achieved three times faster and more effi­cient pub­lish­ing, with increased per­son­al­i­sa­tion; up to 40 per­cent faster updates through reusable assets; increased secu­ri­ty in man­ag­ing author­ing rights; and new insights into user activ­i­ty.

As data and con­tent con­tin­ue to pro­lif­er­ate, it becomes impos­si­ble to man­u­al­ly deliv­er per­son­alised expe­ri­ences at scale. To meet your cus­tomers’ expec­ta­tions, you need to auto­mate by lever­ag­ing data sci­ence. That’s what we’ll be talk­ing about in the next blog of this series: how you can use machine learn­ing in dig­i­tal mar­ket­ing to deliv­er stand­out cus­tomer expe­ri­ences. See you there!

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