I’ve wanted to tackle this series for a while—an ongo­ing look at per­son­al­iza­tion, div­ing into the nitty-gritty in a big way. Bring in the experts from around Adobe who can speak to their unique arm of the business—and the rel­e­vance story in general—and demys­tify an over­whelm­ingly essen­tial piece of the dig­i­tal expe­ri­ence that has been murky for too long. So here goes: part one.

When it comes to per­son­al­iza­tion in gen­eral, we can all agree that as con­sumers, we desire per­son­al­ized expe­ri­ences. They make us feel good. We react emo­tion­ally when things line up the way we want them. And that kind of vis­ceral response to a prod­uct, ser­vice, or con­tent sends effi­ciency through the roof.

What still eludes mar­keters: what “per­son­al­iza­tion” really boils down to. It’s an overused term, so unnec­es­sar­ily com­pli­cated and so provoca­tive at times that it can get lost in trans­la­tion. And if you aren’t speak­ing that rel­e­vant language—remember, per­son­al­iza­tion is all about relevance—then it’s no sur­prise you aren’t see­ing the per­son­al­iza­tion pay­off, and no won­der the con­cept con­tin­ues to con­found you and your organization.

So let’s kick off the series, start­ing with the guts of per­son­al­iza­tion and what it means for your busi­ness and its customers.

Think back to the pre-Internet days. Grow­ing up, the neigh­bor­hood butcher knew every­one in the neigh­bor­hood, and exactly what cuts of meat to hold for them—even bones for their dogs. The butcher and other com­mu­nity stores were bustling hubs of per­son­al­ized expe­ri­ences, and what helped local busi­nesses thrive up until the late 1970s/early 1980s.

Now, the cor­ner store has gone dig­i­tal and, with it, is that much larger with even greater oppor­tu­ni­ties for align­ment and con­nec­tiv­ity. But, at the end of the day, it’s that highly rel­e­vant, one-to-one mar­ket­ing we all crave … and respond to.

So if the notion of per­son­al­iza­tion is so sim­ple, why is it so elu­sive? For many, it’s often that next step—you know you need to be spot-on rel­e­vant to your cus­tomers, but now what? Being rel­e­vant means align­ing with your indi­vid­ual con­sumers to the point that the engage­ment expe­ri­ence becomes so in tune with their needs, move­ments, searches, prod­uct inter­ac­tions, and responses that they’re com­pelled to action. I always wanted what the cor­ner store clerk was hold­ing spe­cial for me.

Although the notion of being rel­e­vant hasn’t changed over the last few decades, today’s per­son­al­iza­tion oper­ates at a scale that the cor­ner store could never have imag­ined. This type of high-level con­nec­tiv­ity is done through a host of opti­miza­tion best prac­tices and a solid com­mit­ment to test­ing and stick­ing to the data-driven deci­sion­ing that results. You know your cus­tomers, you greet them when they arrive, and you lead them on rel­e­vant jour­neys filled with spot-on rec­om­men­da­tions, offers, announce­ments, and pro­mo­tions, increas­ing their sat­is­fac­tion with your brand and dri­ving engage­ment, pur­chase, and, ulti­mately, a pow­er­ful loyalty—which requires fur­ther rel­e­vance to sus­tain and grow. This boils down to always being “on.”

Bridg­ing the gap between the deter­mi­na­tion that per­son­al­ized expe­ri­ences mat­ter and get­ting to “go”—and beyond—can still be the  stum­bling block. Start with the basics: you know some­thing about every cus­tomer. New or return­ing, known or anony­mous, some dig­i­tal fin­ger­print exists. For the anony­mous cus­tomer it could be geolocating—offering a pair of rain boots to some­one in Florida dur­ing a par­tic­u­larly damp month. And for the known user there are infi­nite appli­ca­tions and pos­si­bil­i­ties. The most obvi­ous exam­ple, of course, is Ama­zon and its “Ama­zoni­fi­ca­tion” of the online shop­ping expe­ri­ence. From the minute I get to the site every offer, every push, every rec­om­men­da­tion seems like it was crafted just for me.

Most likely your orga­ni­za­tion is in those ear­lier stages, some­where between ad hoc per­son­al­iza­tion and Ama­zon pro­por­tions. So what, then, con­sti­tutes per­son­al­iza­tion? Plenty of tac­tics and strategies.

  • Per­son­al­ized greetings—say hello to me when I arrive!
  • Rel­e­vant ads or con­tent pieces that align with past searches or con­ver­sion points.
  • Com­ple­men­tary prod­uct or ser­vice rec­om­men­da­tions. If I bought a pasta pot last month I likely don’t need another, but I might like some gourmet olive oil or a top-of-the-line colander.
  • Fol­low them on their jour­ney, through your site and beyond. Think retar­get­ing (a topic we’ll explore down the road) or email mar­ket­ing that dri­ves back to your site based on recent pur­chases, expressed pref­er­ences, and more.

Step two is build­ing that pro­file. We’ll dive into the anony­mous vis­i­tor but, likely, after they’ve vis­ited your site that crit­i­cal first time they won’t be a stranger any­more. Craft a view of your customers—and keep it simple:

  • Behav­ioral variables—how did they get to you, what did they do once they got to you, and where did they engage?
  • Pur­chase or con­ver­sion patterns—what did they want and what might they want in the future.
  • Tem­po­ral con­sid­er­a­tions, includ­ing when they vis­ited and how long they lingered.
  • Geolo­ca­tion data.
  • Where they’re com­ing from—the device, the plat­form, and the browser.
  • Where they came from—search? ads? direct? That makes a difference.
  • Expressed preferences—who doesn’t like to talk about them­selves? When they opt-in ask them what they like and what they don’t, when their birth­day falls and, even more blunt, exactly what they want to see and hear from you. You’d be sur­prised what you get by being direct.

Then keep col­lect­ing and refin­ing, refin­ing and col­lect­ing, test­ing, opti­miz­ing, and striv­ing to gather more rel­e­vant data to make every cus­tomers’ jour­ney more per­son­al­ized from start to finish.

Step three is lever­ag­ing this poten­tially vast amount of data. Hav­ing and rec­og­niz­ing the power of data and ana­lyt­ics doesn’t mat­ter if you can’t use it effec­tively. This is where audi­ence seg­ment­ing, data-driven deci­sion­ing, and automa­tion come into play. The big­ger and more diverse your orga­ni­za­tion becomes in terms of vis­i­tors, the less likely you as a human mar­keter will be able to suc­cess­fully steer the per­son­al­iza­tion ship. That doesn’t mean you’re out of the equa­tion, it just means you need to fun­nel your tacit knowl­edge into inform­ing an auto­mated pow­er­house that can deliver the right action, rec­om­men­da­tion, or con­tent to the right cus­tomer at the right moment.

More on automat­ing per­son­al­iza­tion in the com­ing weeks.

Hav­ing this com­plex, mean­ing­ful, action­able rela­tion­ship with your customers—and actu­ally act­ing on it—is what per­son­al­iza­tion is all about. Being that cor­ner store or local butcher and remem­ber­ing my preferences—then deliv­er­ing what I want when I want it—is what being rel­e­vant is all about. Spot-on rel­e­vance never gets tire­some or redundant—it only improves and refines with age and depth.

Per­son­al­iza­tion is sim­ple and nec­es­sary. Don’t let your orga­ni­za­tional waters get mud­died with unnec­es­sary chat­ter and ill informed tac­tics. At the end of the day, per­son­al­iza­tion is about deliv­er­ing 24/7 rel­e­vance to every cus­tomer. It started with the local cor­ner store and has mor­phed into its (mas­sive, global-reaching, omnichan­nel) dig­i­tal cousin. But the rules haven’t changed. 

This is just the jump­ing off point to what I hope will be an ongo­ing con­ver­sa­tion cov­er­ing all things personalization.

Let the per­son­al­iza­tion begin.

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