Tech­nol­o­gy is mov­ing at the speed of light. We can know more about our cus­tomers and prospects now than ever before. But how do we know when we’ve crossed the line from car­ing to creepy?

By 2020 we will have cre­at­ed a total of 35 zettabytes of data, accord­ing to the Com­put­er Sci­ences Cor­po­ra­tion. In Stephen Hawking’s phrase­ol­o­gy, that’s 35 fol­lowed by 21 zeroes. Let’s face it: Our pri­va­cy isn’t what it used to be. Mort­gage infor­ma­tion is pub­lic record. Google Earth is watch­ing. Cam­eras loom in park­ing lots, at stop­lights and even in our own home secu­ri­ty sys­tems. In our data-on-demand world, more is always bet­ter, right? That’s true only if you have a strat­e­gy for what comes next after data col­lec­tion. Cre­at­ing great con­tent is only the begin­ning, accord­ing to Forbes con­trib­u­tor Greg Petro. Con­text mar­ket­ing must pro­vide the right con­tent to the right prospect at just the right moment. Mar­keters have more access to data than ever before, but the key is to under­stand what comes next. Our cus­tomers must receive val­ue in return for giv­ing up some­thing per­son­al. Oth­er­wise, the rela­tion­ship fal­ters and sus­pi­cion aris­es around the use of data. As mar­keters and as stew­ards of con­sumer data, we need to ask four key ques­tions if we want to be rel­e­vant and build trust in our mar­ket­ing out­reach.

1. Did I Ask Permission?

We’ve all seen those hard-to-read finan­cial ser­vice and insur­ance dis­clo­sures that are mailed annu­al­ly in legalese and ultra-fine print dis­clos­ing how our data is or isn’t used. These state­ments are telling us what hap­pens with our data. What about ask­ing? Have you asked your cus­tomers whether they would like to hear from you, how often they would like to hear from you, what chan­nel they pre­fer (email, phone or direct mail) and what con­tent inter­ests them the most? We all feel oblig­at­ed to sign up in our retail brick-and mor­tar expe­ri­ence for that loy­al­ty card, but we are told to pro­vide our email address rather than asked how we would like to be con­tact­ed.

2. Why Do I Need More Customer Data? What Do I Look For?

Accu­mu­lat­ing infor­ma­tion is appeal­ing. After all, min­ing data is like look­ing for the gold amongst the rocks. But there’s just too much to sift. So let’s think about data in tiers. This will help pri­or­i­tize the effort, time, and cost to col­lect and ana­lyze.

Tier 1 Data

Let’s say you have a base of cus­tomers who have been dili­gent­ly tracked in your mar­ket­ing and finan­cial sys­tem. You know what they bought, how long ago they bought it, and what their cus­tomer jour­ney looks like. This is the most valu­able infor­ma­tion. This is Tier 1, what they have done with you. No com­peti­tor has this infor­ma­tion – only you have it. The data is pro­pri­etary and shows your cus­tomers’ “votes” (what they like and don’t like through their pur­chase pat­terns) and how prof­itable they are to you.

Tier 2 Data

How­ev­er, you want to enrich the what from Tier 1 with why. This involves look­ing out­side of your orga­ni­za­tion to Tier 2 data. This data rep­re­sents behav­ior out­side of your com­pa­ny. For exam­ple, which web­sites are my cus­tomers vis­it­ing? Where do my cus­tomers live, work and play? Tier 2 data is dynam­ic, or ever-chang­ing. It helps us infer why cus­tomers do what they do. Cus­tomers have fam­i­lies, trav­el, browse online, and vis­it loca­tions for food, cloth­ing and enter­tain­ment. Col­lect­ing this data is a bit more chal­leng­ing, but it’s worth min­ing for the under­stand­ing of indi­vid­ual moti­va­tions. It helps reveal why our cus­tomers seek a prod­uct or ser­vice and whether that need is rel­e­vant to our offer­ing.

Tier 3 Data

Tier 3 data is about the who. These are the demo­graph­ics and psy­cho­graph­ics around cus­tomers, their fam­i­lies, and friends. This infor­ma­tion helps us with rel­e­van­cy. In oth­er words, if I know my cus­tomer is a mom with teens, I’ll be bet­ter able to per­son­al­ize my mes­sage. In sum­ma­ry: Tier 1 tells me hard facts about pur­chase infor­ma­tion – the what. Tier 2 is the why. Before we craft mes­sag­ing for Tier 3, we have to con­sid­er behav­ior from Tier 1 and why that behav­ior occurred from Tier 2. Now we are ready to per­son­al­ize.

3. Is There A Value Add To My Customer & My Business?

In addi­tion to “big data,” “machine learn­ing” and “mar­ket­ing automa­tion,” you have prob­a­bly also heard the “bea­con mar­ket­ing” buzz­word. This has cre­at­ed sig­nif­i­cant atten­tion among mar­keters, and would fit into Tier 2 data. While bea­con mar­ket­ing may be the lat­est shiny object, Forrester’s Thomas Hus­son points out that bea­con mar­ket­ing (a.k.a. loca­tion-based mar­ket­ing) has a great deal of dis­rup­tive poten­tial to bridge the dig­i­tal and phys­i­cal worlds. But mar­ket­ing lead­ers must resist the hype and think strate­gi­cal­ly and respon­si­bly about how – and whether – to imple­ment pro­grams around this data. Regard­less of the type of data col­lect­ed, cus­tomer and com­pa­ny alike must ben­e­fit. Apply­ing this to bea­con mar­ket­ing, we must con­sid­er:

• Cost of installing the tech­nol­o­gy.
• What ben­e­fit is pro­vid­ed to the cus­tomer? What’s your quid pro quo?
• Do you have a strat­e­gy? Who will receive an offer based on prox­im­i­ty and at what point in time?
• What are the legal terms and con­di­tions for cus­tomers to opt in and pro­vide their loca­tion data?

While these are imme­di­ate con­sid­er­a­tions, it remains to be seen whether the strat­e­gy can pay for itself. A long-term view based on ROI must con­sid­er loy­al­ty and advo­ca­cy over an extend­ed peri­od of time across exist­ing and future cus­tomers.

4. How Will I Store & Use Data?

Last, but cer­tain­ly very impor­tant, is the top­ic of data stor­age. Expo­nen­tial growth of col­lectible detail has result­ed in expand­ing needs for data stor­age. Rapid access to high vol­umes of data must also be con­sid­ered. Ama­zon Web Ser­vices, Google Cloud and Microsoft Azure allow rapid deploy­ment of inex­pen­sive stor­age. The abil­i­ty to inte­grate, store and con­sume data at any point in time is key. Why? Get­ting the right com­mu­ni­ca­tion in front of con­sumers with the right con­text will sup­port their next deci­sion. Mar­keters must deter­mine which real-time data is worth stor­ing, how to make effi­cient use of it, and how to main­tain cus­tomer val­ue and pri­va­cy along the way.

What’s Next?

Use a crawl/walk/run approach to data col­lec­tion, usage, and stor­age. Get start­ed by tak­ing inven­to­ry of cus­tomer data with­in your orga­ni­za­tion. Ana­lyze and iso­late the infor­ma­tion that brings the most val­ue to your cus­tomer and orga­ni­za­tion. Store this data. Next, review out­side data sources, pay­ing atten­tion to depth of detail and ROI. After the review, esti­mate the cost to ramp up to the next lev­el of data man­age­ment, stor­age and strate­gic val­ue. Crit­i­cal­ly assess how much exter­nal data is nec­es­sary, what infra­struc­ture is required to house it, and how your orga­ni­za­tion and cus­tomers will derive val­ue. This approach takes time, but the result will be increased cus­tomer and com­pa­ny sat­is­fac­tion from a care­ful­ly planned approach to the lat­est infor­ma­tion.