Fol­low the Money

An in­sight is only as good as the money it makes.

Point of Purchase - - CONTENTS -

Here is a look at how com­pa­nies plan their ap­proach and strate­gies based on the in­sights they gain into their tar­get con­sumers and how shop­pers be­have in dif­fer­ent re­tail en­vi­ron­ments.

Henry Ford said: “If I’d asked cus­tomers what they wanted, they would have said, ‘a faster horse’.” Steve Jobs fa­mously echoed that sen­ti­ment when he said: “It isn’t the con­sumers’ job to know what they want.” Sam Wal­ton took a re­lated view with his 10th Rule: “Swim up­stream. Ig­nore the con­ven­tional. Think dif­fer­ently. If ev­ery­body’s do­ing it one way, there is a good chance you can find your niche by go­ing in ex­actly the op­po­site di­rec­tion.”

Oth­ers, mean­while, of­fer a more “quan­ti­ta­tive” per­spec­tive. Dr. Oz says, “The ma­jor part of good heart health is in the met­rics,” and W. Ed­wards Dem­ing ad­vised: “In God We Trust; all oth­ers must bring data.” Peter Brand, of Money­ball fame, said: “It’s about get­ting things down to one num­ber. Us­ing the stats the way we read them, we’ll find value in play­ers that no one else can see.”

It seems good in­stincts and hard data are the yin and yang of busi­ness in­sights.

JC Pen­ney chief ex­ec­u­tive Ron John­son told Har­vard Busi­ness Re­view, “you’ve got to trust your in­tu­ition much more than you trust the data.” In his book, Blink, Mal­colm Glad­well also came down on the side of run­ning with our first im­pres­sions.

On the other hand, Michael Mauboussin, au­thor of Think Twice, of­fered a re­but­tal to Glad­well’s the­sis, ar­gu­ing that bet­ter de­ci­sions de­pended on the “wis­dom of the crowds,” along with data and math­e­mat­ics. And IBM chief mar­ket­ing of­fi­cer Jon Iwata ad­vised his fel­low CMOs to em­brace “ad­vanced an­a­lyt­ics and com­pelling met­rics” in their de­ci­sion mak­ing.

This de­bate may be as old as the busi­ness of mar­ket­ing it­self, but it prob­a­bly will never die — and cer­tainly not at a time when brand loy­alty is erod­ing, pri­vate la­bels are grow­ing, and more than 90 per­cent of new prod­ucts are fail­ing. Growth re­quires in­no­va­tion, and in­no­va­tion will not hap­pen with­out in­sights.

So, is get­ting at those in­sights an art or a sci­ence? The an­swer, clearly, is “yes.” It is both. But the more im­por­tant thing is to eval­u­ate the qual­ity of the in­sights based on the re­sults that they ul­ti­mately de­liver in terms of in­no­va­tion and growth. That’s the rea­son we in­vest in in­sights, whether gut or quan­ti­ta­tive.

Look at the top-level com­pa­nies in the Hub Top 20 over the last five years. We know how they got there. They un­der­stand that a brand is a prom­ise made and kept, and that mak­ing and de­liv­er­ing the brand’s prom­ise drives eq­uity that drives en­dur­ing, prof­itable growth. They know that it’s in­no­va­tion in the prod­uct, prom­ise and chan­nel that drive eq­uity.

We need to rec­og­nize that shop­pers are mo­ti­vated first by emo­tion; shop­ping is an ex­pe­ri­ence and that ex­pe­ri­ence is an emo­tional one. One of the most im­por­tant things to un­der­stand about trans­lat­ing in­sights into in­no­va­tion is where the de­ci­sion is made.

Most com­pa­nies use a sim­i­lar process for de­vel­op­ing the in­sights. Ev­ery com­pany has some level of in­sights that trans­late to some level of in­no­va­tion that trans­lates to some level of strate­gic plan­ning and ac­ti­va­tion. Maybe it’s be­cause they all use a sim­i­lar process that most are ex­pe­ri­enc­ing less growth than they could?

But what makes some com­pa­nies more in­no­va­tive than oth­ers? What is their strat­egy? Some of­fer a value break­through like Wal­mart. Some are first-movers, like Mi­crosoft. Some have a new vi­sion, like JC Pen­ney (re­sults are yet to be de­ter­mined, of course). There’s also a whole lot of talk to­day about the re­la­tion­ship be­tween com­pany cul­ture and in­no­va­tion, with Zap­pos of­ten men­tioned. Each of these com­pa­nies has dif­fer­ent strate­gies, but they all use in­sights as the cur­rency, and trans­late those ben­e­fits to some form of con­sumer end-ben­e­fit.

A Whole-Brain Ap­proach

Given that con­sumers take a “whole brain” ap­proach to mak­ing de­ci­sions, mar­keters need to take a “whole brain” ap­proach to in­sights, with full con­sid­er­a­tion to both the “left brain” (log­i­cal, se­quen­tial, ra­tio­nal, an­a­lyt­i­cal, ob­jec­tive) and “right brain” (ran­dom, in­tu­itive, holis­tic, sub­jec­tive).

We need to rec­og­nize that shop­pers are mo­ti­vated first by emo­tion; shop­ping is an ex­pe­ri­ence and that ex­pe­ri­ence is an emo­tional one. One of the most im­por­tant things to un­der­stand about trans­lat­ing in­sights into in­no­va­tion is where the de­ci­sion is made. That means we have to un­der­stand the con­sumer, the shop­per, and whether their de­ci­sions are made be­fore they get to the store or while they are in the store.

There’s no way that we could do all of that purely through in­tu­ition — or purely through data. What’s re­quired is a “think, feel, do” ap­proach.

To un­der­stand the shop­per mind­set, we need to have a deep, fact-based un­der­stand­ing of their be­hav­ior and the mo­ti­va­tions that drive it, which can be acted upon to fur­ther brand innovations. These mo­ti­va­tions can in­clude at­ti­tudes, be­liefs, val­ues and feel­ings. Tap­ping into those mo­ti­va­tions to inf lu­ence shop­per be­hav­ior re­quires un­der­stand­ing that be­hav­ior in the re­tail en­vi­ron­ment.

So, we need an un­der­stand­ing of that, as well: How does the con­sumer de­cide where to shop, and then how do their sur­round­ings inf lu­ence whether they stick to their shop­ping lists or make their pur­chase de­ci­sions on the f ly? The re­la­tion­ship be­tween in­sights and in­no­va­tion is built on the con­nec­tions be­tween the con­sumer, the brand and the re­tailer. It’s these con­nec­tions that take us to a more strate­gic ap­proach to de­vel­op­ing in­sights, and it mixes quan­ti­ta­tive and qual­i­ta­tive in­tel­li­gence. They can help push the idea fur­ther be­cause we are tak­ing a more com­plete view of the con­sumer into ac­count. Af­ter all, it’s the idea that changes the world, not the in­sight, so let’s put the fo­cus there.

Cray­ola, the num­ber-one brand in chil­dren’s art sup­plies, has done a great job in this re­gard. More than half of Cray­ola’s cat­e­gory vol­ume is sold dur­ing the back-to-school pe­riod and the brand has lim­ited rel­e­vance the rest of the year. Their chal­lenge is to in­no­vate within their cat­e­gory and ex­pand their rel­e­vance from “chil­dren’s art sup­plies” to some­thing more.

Their strat­egy is to broaden the def­i­ni­tion of their cat­e­gory by cre­at­ing new op­por­tu­ni­ties for self-ex­pres­sion. This is based on the in­sight that par­ents want a broader range of prod­ucts to sat­isfy the as­pi­ra­tions they have for their kids. Cray­ola de­vel­oped a range of “con­cept lanes” at re­tail, in­clud­ing kids’ art gal­leries in stores and Cray­ola Tow­ers, a strik­ing dis­play of Cray­ola prod­ucts that high­light the prod­uct’s many cre­ative pos­si­bil­i­ties.

I was not in­volved in the de­vel­op­ment of these con­cepts, but clearly they took into ac­count the mind­set, be­hav­ior and sur­round­ings that were in­flu­enc­ing the shop­per’s de­ci­sion-mak­ing.

Con­nect­ing the Dots

In to­day’s frag­ile econ­omy, com­pa­nies are un­der such pres­sure on the earn­ings side of the equa­tion that a lot of de­ci­sions are made to re­duce risk. At many com­pa­nies, it’s be­lieved that quan­ti­ta­tive re­search re­duces risk.

Not ev­ery­one buys into this, how­ever. In fact, Chris­tine Day, chief ex­ec­u­tive of Lu­l­ule­mon Ath­let­ica, the rapidly- grow­ing fit­ness-ap­parel re­tailer, says it’s just the op­po­site. “Big data gives you a false sense of se­cu­rity,” she told the Wall Street Jour­nal. Lu­l­ule­mon uses no cus­tomer-re­la­tion­ship man­age­ment soft­ware at all, and in­stead re­lies on lis­ten­ing to what shop­pers say when they are in the store (see page six). Lu­l­ule­mon’s re­sults speak for them­selves: “Over the past three years, the com­pany has posted nine quar­ters in which sales rose 30 per­cent or more from the year be­fore,” ac­cord­ing to the Jour­nal.

Re­gard­less of whether the ap­proach tilts to the quan­ti­ta­tive or qual­i­ta­tive side, Lu­l­ule­mon and other in­no­va­tive en­ter­prises are con­nect­ing the dots be­tween the in­sights and the re­sults achieved. And in a world where in­sights are judged only by the re­sults they help de­liver, the most sen­si­ble ap­proach is to com­bine the hu­man el­e­ments of judg­ment and cre­ativ­ity with the pre­dic­tion and anal­y­sis of sta­tis­tics or agent-based mod­el­ing. In this way, smart data col­lec­tion pro­vides the facts; mod­els sup­ply the rigor; and we sup­ply the judg­ment and cre­ativ­ity for in­sight-in­spired ideas that get bet­ter re­sults.

In to­day’s frag­ile econ­omy, com­pa­nies are un­der such pres­sure on the earn­ings side of the equa­tion that a lot of de­ci­sions are made to re­duce risk. At many com­pa­nies, it’s be­lieved that quan­ti­ta­tive re­search re­duces risk.

We can do sce­nario plan­ning and un­der­stand how the con­sumer de­ci­sion is made and which levers to pull. There­fore, we can iden­tify the re­la­tion­ship be­tween the con­sumer’s de­ci­sion process, brand eq­uity and the re­turn-on-in­vest­ment. We can do that by chan­nel, by re­tailer and by con­sumer (see chart). It’s not about an­a­lyz­ing each of these ar­eas in­de­pen­dently, but

rather look­ing at their in­ter­de­pen­dence.

As a re­sult, we can now un­der­stand the suc­cess driv­ers in terms of aware­ness and de­mand cre­ation. We know what to do at re­tail, and how much money to spend. We are build­ing in­sights based on sce­nario plan­ning with pre­dic­tive re­sults. It is the best of all worlds, where not only are we us­ing in­sights to cre­ate great ideas, but we are also test­ing them in dif­fer­ent sce­nar­ios, at dif­fer­ent lev­els of spend­ing.

The three ques­tions about ac­count­abil­ity are al­ways: How can we im­prove over the re­sults we’re get­ting now; how can we say that with a straight face; and how can we be sure we’ll get the re­sults we’re pre­dict­ing? Us­ing the data, the model, our judg­ment, and test­ing the dif­fer­ent sce­nar­ios al­lows us to go back to the data, push the ideas, make those ideas big­ger and op­ti­mize the busi­ness.

This is art and sci­ence, gut and anal­y­sis, and it pro­vides a frame­work for in­sights, in­no­va­tion and growth

Newspapers in English

Newspapers from India

© PressReader. All rights reserved.