I’ve had the good for­tune to travel almost lit­er­ally around the world over the past six months meet­ing with Adobe Mar­ket­ing Cloud cus­tomers on sev­eral con­ti­nents. Each mar­ket and each cus­tomer is dif­fer­ent, fac­ing its own unique chal­lenges and apply­ing dig­i­tal mar­ket­ing best prac­tices in its own way.

One thing has been the same every­where I’ve been: Forward-thinking dig­i­tal mar­keters are ask­ing more of their data than ever before. That part prob­a­bly isn’t shock­ing. What has been some­thing of an epiphany to me, how­ever, is that these mar­keters are simul­ta­ne­ously real­iz­ing that visitor-based data will never be as pow­er­ful in opti­miz­ing cus­tomer expe­ri­ence and mar­ket­ing cam­paigns than customer-based data will be.

What is cus­tomer ana­lyt­ics and how is it dif­fer­ent than dig­i­tal analytics?

Almost invari­ably, your cus­tomers do not see your brand as a col­lec­tion of chan­nels: web, mobile, call cen­ter, point of sale, etc. You are one brand, and cus­tomers expect to be known how­ever they inter­act with you. Cus­tomer ana­lyt­ics seeks to allow mar­keters to have that same per­spec­tive on cus­tomers. Ben Gaines is Ben Gaines, whether I am mar­ket­ing to him via direct mail, send­ing him a weekly e-mail newslet­ter, tar­get­ing him with a per­son­al­ized expe­ri­ence on the web, or answer­ing his sup­port ques­tion. Your ana­lyt­ics can and should reflect this truth. If they do not yet, they def­i­nitely will in the not-too-distant-future.

Here’s a recent, basic exam­ple of what I mean: I a while ago took my daugh­ter on a short trip to Boston, where her grand­mother lives. I had booked my ticket online, using a credit card. But I added my daugh­ter to my itin­er­ary by call­ing one of the airline’s phone agents. If an ana­lyst is look­ing at what I’ve done as a web vis­i­tor alone, he’s miss­ing a huge oppor­tu­nity. I’m not just a busi­ness trav­eler, like my web vis­i­tor pro­file might sug­gest; I’m also a dad who is always inter­ested in mes­sages about cheap fares to fam­ily des­ti­na­tions. But you only get to know that by look­ing at me at a higher level than the web visitor. A good ana­lyst would see that I have a higher propen­sity to travel to Boston with a com­pan­ion; when going to other cities, it’s just me and the web is my pre­ferred chan­nel for inter­ac­tion. But the air­line knows much more about me—and has a much greater oppor­tu­nity to mar­ket to me intelligently—when they take my whole set of inter­ac­tions into account.

On the web, I’m a vis­i­tor. But every­where, across all chan­nels, I’m a cus­tomer. A web visit is just one way I hap­pen to inter­act with your brand. That’s the key prin­ci­ple; that’s the right par­ent count­able for marketers.

Let me also be clear in stat­ing that I’m not down­play­ing the impor­tance of the web and web data. I’ve been a dig­i­tal ana­lyst and a prod­uct man­ager devel­op­ing dig­i­tal ana­lyt­ics tools. Great dig­i­tal analy­sis gen­er­ates tremen­dous ROI and grows busi­nesses. But I also see orga­ni­za­tions look­ing to make their data power con­tent opti­miza­tion, or remar­ket­ing, or mer­chan­dis­ing, etc. What will be more effec­tive in reach­ing your cus­tomers: con­clu­sions based on one chan­nel of inter­ac­tion, or con­clu­sions grounded in the com­plete cus­tomer inter­ac­tion map? You can still do your con­tent analy­sis, your nav­i­ga­tion analy­sis, your cam­paign analy­sis, etc.—everything you, as a dig­i­tal ana­lyst, know and love. But you can do it from the top of Ever­est, with the whole vista laid out before you in addition.

How is this dif­fer­ent than BI and/or Hadoop?

Tra­di­tional BI tech­nolo­gies, and more recently Hadoop, are great at a lot of dif­fer­ent things. Hadoop and map/reduce store large amounts of data really, really well. I am a huge believer in big data.

Where they fall down for marketers—and espe­cially dig­i­tal marketers—is the require­ment for exploratory analy­sis. Big data for mar­keters, as some have termed it, demands the abil­ity to iter­ate through an ana­lyt­i­cal thought process very quickly.

One of the ways that advanced ana­lysts achieve this today is by focus­ing on data sets and spe­cific data ele­ments that are rel­e­vant to under­stand­ing the cus­tomer. A com­mon approach with big data is to shove every­thing under the sun into Hadoop. But a good data archi­tect can help you focus such you have the right data that you need in order to under­stand the cus­tomer journey.

Hadoop and sim­i­lar big data tech­nolo­gies will con­tinue to play a major role in the growth of orga­ni­za­tions. But there is the need for another layer of ana­lyt­ics that pro­vides both the speed and flex­i­bil­ity that mar­ket­ing, and the ana­lysts serv­ing mar­ket­ing, will need in order to achieve the kind of rela­tion­ships with their cus­tomers that they’re clam­or­ing for today.

How will cus­tomer ana­lyt­ics change in the future?

As a dig­i­tal ana­lyst, it’s easy to sort of “tune out” the con­ver­sa­tion around big data. And if you don’t under­stand the role of cus­tomer ana­lyt­ics in mar­ket­ing, it’s easy to believe that it’s this other thing that “isn’t you.” You’re the owner of dig­i­tal ana­lyt­ics. Six months ago, I would have agreed with you. But hav­ing sat with advanced ana­lysts and heard them talk about where they’re headed, I’ve come to believe in the vision whole­heart­edly. And the best part is that we’re quickly approach­ing some major tech­nol­ogy and industry/skill shifts that will make cus­tomer ana­lyt­ics more pos­si­ble and more acces­si­ble to you than ever before.

You’ve prob­a­bly read about the pro­lif­er­a­tion of data. That is cer­tainly one of the key dri­vers of the shift I’m expect­ing. But per­haps even more sig­nif­i­cant are hard­ware improve­ments that will make it eas­ier for you to explore large amounts of cus­tomer data quickly. In-memory ana­lyt­ics is great today, but as mem­ris­tors move from the­ory to real­ity, the amount of data you’ll be able to store in mem­ory for fast retrieval will blow the doors off of every­thing we do in ana­lyt­ics today.

Now imag­ine what the emerg­ing field of data sci­ence can do with the kind of fast-input/fast-output cus­tomer ana­lyt­ics sys­tems I’m envi­sion­ing. Think about some­thing like k-means clus­ter­ing (and other terms I only sort of under­stand), sit­ting on top of your cus­tomer data, fol­lowed by send­ing those clus­ters to a tool like Adobe Tar­get or Adobe Neolane for per­son­al­ized, tar­geted inter­ac­tions online and offline. But it isn’t just for data sci­en­tists; the visual query concept—where your selec­tions and clicks and explo­ration of data changes your queries on the fly with­out you need­ing to know how to program—makes these kinds of insights acces­si­ble to those of us who do not have Ph.Ds. Until a few months ago, I had never seen data inter­acted with like this. It’s a phe­nom­e­nally excit­ing time for marketers.

The Adobe Ana­lyt­ics team believes firmly in a future where you see, mar­ket to, and inter­act with your cus­tomers the way they see, buy from, and inter­act with your brand: as a sin­gle entity. Our Adobe Ana­lyt­ics Pre­mium solu­tion offers true best-in-class cus­tomer ana­lyt­ics today, in an envi­ron­ment where you an inter­act with data in ways that I’ve never seen any­where else. It’s worth not­ing that even cus­tomers who only put web data into our data work­bench are amazed by the pre­dic­tive and sta­tis­ti­cal mod­el­ing that we’ve added, as well as sim­ply the flex­i­bil­ity to delve into their data that cus­tomer ana­lyt­ics tools pro­vide. I know that sounds like that con­tra­dicts every­thing I’ve been say­ing in this post about cus­tomer data, but for the cau­tious dig­i­tal ana­lyst (like I was), it’s a start!

If you’re like me, and you were once scared of Adobe Insight (now Adobe Ana­lyt­ics Data Work­bench), it’s time to get over the fear. I’ve sat with ana­lysts and watched how they can iter­ate through a thought process across mul­ti­ple chan­nels and have derived insights (no pun intended) more quickly and pow­er­fully than any­where else I’ve seen. But I’m not writ­ing this in order to sell you Adobe Ana­lyt­ics; I’m writ­ing this in order to share with you what I’ve seen as I’ve met with advanced ana­lyt­ics prac­tices all over the world, and what I believe is the future of most dig­i­tal analysts.

The thing is that once you’ve seen what a sharp ana­lyst can do for his or her mar­ket­ing team with cus­tomer ana­lyt­ics, it’s hard to be sat­is­fied with “just” the web any­more. I guess you could say that I’ve become con­verted to cus­tomer ana­lyt­ics. It’s the future of mar­ket­ing ana­lyt­ics, and, for me at least, there’s no look­ing back.

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