Experience Personalisation: Getting the Data Right

Expe­ri­ence Per­son­al­i­sa­tion Series, Part 1 : Data

Every dig­i­tal mar­keter recog­nis­es per­son­alised con­tent as a cru­cial ele­ment in each customer’s jour­ney toward con­ver­sion. In the most basic sense, per­son­al­i­sa­tion is sim­ply the use of cus­tomer infor­ma­tion to deliv­er the right con­tent for each vis­i­tor, every time—in order to get the busi­ness results you want.

At Adobe, we express this equa­tion with a sim­ple for­mu­la: “Data + Con­tent = Per­son­al­i­sa­tion.” In oth­er words, the bet­ter you know your audi­ence, and the bet­ter you know which offers you want to deliv­er when and where, the more rel­e­vant your con­tent will be, and the more pow­er­ful­ly it’ll dri­ve cus­tomer engage­ment and conversions.

Per­son­al­i­sa­tion runs along a spec­trum, from tra­di­tion­al large-seg­ment marketing—which isn’t very per­son­alised at all—through pre­scrip­tive pro­fil­ing, auto­mat­ed mes­sage deliv­ery, and tar­get­ed rec­om­men­da­tions. At the “very high” end of the per­son­al­i­sa­tion spec­trum we find the lat­est inno­va­tions: sophis­ti­cat­ed algo­rithms and machine learn­ing gen­er­at­ing entire web­sites and in-app expe­ri­ences on the fly for each indi­vid­ual user.

In this series of three arti­cles, I’ll explore the ways in which you can bring data and con­tent togeth­er to cre­ate all these types of per­son­alised pro­files and user experiences.

Let’s start by div­ing into data.

Pro­gres­sive profiling

Sales­peo­ple have been build­ing pro­files of their cus­tomers since the very ear­li­est days of trade, when your local shop­keep­er knew you by sight, and would rec­om­mend prod­ucts you’d find use­ful. In today’s world of large-scale mar­ket­ing, though, many com­pa­nies rely on broad cus­tomer seg­ments and out­dat­ed pro­files to tell them which ads to serve—a waste­ful approach in which thou­sands of irrel­e­vant mes­sages are ignored by cus­tomers every day.

To avoid this waste­ful spend­ing, your per­son­al­i­sa­tion plat­form needs to pro­vide tools that enable your under­stand­ing of your cus­tomer seg­ments to adapt in real time—molded by new cus­tomer behav­iours, loca­tion vari­ables, refer­rer data, and oth­er rel­e­vant information.

The first time you inter­act with dig­i­tal users, you might know very lit­tle about them—nothing more than the time and touch­point where you met them, per­haps, and which link they clicked. This tiny clus­ter of data acts as the ini­tial seed of an ever-grow­ing profile—a pic­ture of each user that you build up over time as you inter­act with that cus­tomer on your web­site, on mobile, in store, and at every oth­er touchpoint.

The more you learn about your cus­tomers, the more you can per­son­alise the con­tent you serve them—and the more able you are to adapt the pro­files you have for them, the more quick­ly you can re-per­son­alise as their needs change. That means reduc­tion in wast­ed ad spend, no more fric­tion with cus­tomers, no more ignored mes­sages, and a much clos­er, more mutu­al­ly trust­ing rela­tion­ship with the cus­tomer; just like how it used to be at your local shop.

Cus­tomer attributes

The data from your pro­gres­sive pro­files will pro­vide a sol­id back­bone for your con­tent personalisation—but if that’s the only tool you use, you still won’t be tak­ing advan­tage of a wealth of oth­er use­ful cus­tomer data you already have. I’m talk­ing about all the data that’s locked up in your cus­tomer rela­tion­ship man­age­ment (CRM) sys­tem, your inter­nal systems—such as enter­prise resource plan­ning (ERP) and data ware­house (DWH)—and all your oth­er cus­tomer infor­ma­tion resources that aren’t linked direct­ly with your mar­ket­ing plat­form. You own all this data, so why not make the most of it?

Well, not so fast. Not all data is action­able, and data doesn’t auto­mat­i­cal­ly equal use­ful knowl­edge about a cus­tomer. That’s why your per­son­al­i­sa­tion plat­form should allow you to upload this data, then com­bine it with oth­er cus­tomer inter­ac­tions to deter­mine which of it will be rel­e­vant to your ever-grow­ing cus­tomer profiles—and thus, which of it you should use to enrich your per­son­alised marketing.

A toolk­it with this abil­i­ty will enable you to build tru­ly uni­fied cus­tomer pro­files, not only around inter­ac­tions at mar­ket­ing touch­points, but—potentially—around every inter­ac­tion a cus­tomer has ever had with your busi­ness, in any con­text. More to the point, these tools free you from try­ing to pre­scrip­tive­ly define your audi­ences based on cor­re­la­tions between data points. Instead, they lever­age actu­al inter­ac­tions with these cus­tomers to show you how to mar­ket to them in the future.

Think­ing even big­ger, you’ll be able to use this new­ly import­ed data in many oth­er mar­ket­ing con­texts, beyond just personalisation—think ana­lyt­ics for report­ing, con­tent man­age­ment for con­tent indi­vid­u­al­i­sa­tion, data man­age­ment to enhance your on and off­site expe­ri­ences, and cam­paign man­age­ment for cross-chan­nel cam­paign exe­cu­tion. This means you’ll want to be able to share this data with oth­er groups through­out your organ­i­sa­tion, as seam­less­ly as possible.

At Adobe we’ve been work­ing hard to pro­vide exact­ly these kinds of inte­grat­ed capa­bil­i­ties. We’ve built the abil­i­ty to define uni­fied audi­ences into solu­tions like Adobe Ana­lyt­ics and Adobe Tar­get, and pro­vid­ed core ser­vice capa­bil­i­ties like Cus­tomer Attributes—all of which elim­i­nate the need for Frankenstein’s mon­ster-like plat­forms built of mul­ti­ple appli­ca­tions, data­s­tores, APIs, and user inter­faces; and make seam­less shar­ing of cus­tomer pro­files a point-and-click reality.

With a pow­er­ful solu­tion for gath­er­ing and inte­grat­ing data into robust, adap­tive cus­tomer pro­files, you’ll have one major piece of the per­son­al­i­sa­tion puz­zle. But two big ques­tions remain: How can you make sure the right con­tent gets served to the right pro­files? And how can you bring data and con­tent togeth­er to cre­ate inno­v­a­tive cus­tomer experiences?

Those are the ques­tions I’ll be tack­ling in arti­cles two and three of this series. See you there!