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In my last post, I intro­duced the two great fea­tures of Big Data that great mar­keters strive for: sim­plic­ity and per­son­al­iza­tion. Increas­ingly, the work of con­ver­sion rate opti­miz­ers (CROs) and dig­i­tal mar­keters can be boiled down to these two opti­miza­tion tac­tics. Why? Because they do so much more than convert.

Per­son­al­iza­tion is about cre­at­ing rel­e­vant and valu­able con­tent, and sim­plic­ity is about deliv­er­ing that con­tent quickly and seam­lessly. Imag­ine wak­ing up on your birth­day, and a friend has already left the per­fect gift—that rare gad­get you’ve been pin­ing after—right there on the kitchen table beside a steaming-hot pot of cof­fee, cream no sugar. That’s per­son­al­iza­tion. Now imag­ine the present is unwrapped, no plas­tic pack­ag­ing to hack through. That’s simplicity.

Yes, in life most of us find unwrap­ping presents excit­ing, but in dig­i­tal we don’t want any­thing between us and the prod­uct or infor­ma­tion we’re search­ing for. In the test­ing we’ve done at Adobe most recently, we’ve found that the sim­plest ver­sion wins every time. You know how some sites give you the spin­ning “site load­ing” icon and then make you sit through 30 sec­onds of mean­ing­less graph­ics before you even get to a nav­i­ga­tion page? Throw out the wrap­ping and give your vis­i­tors instant gratification.

2-for-1 Big Data Strategies

Big Data should help us view and respond to vis­i­tors as indi­vid­u­als, cre­at­ing unprece­dented oppor­tu­nity to tar­get and con­vert. The four strate­gies below will help you har­ness Big Data to achieve both sim­plic­ity and per­son­al­iza­tion in one fell swoop.

1. Embrace the Process

Don’t make the mis­take of mea­sur­ing all your mar­ket­ing efforts in dec­i­mals and dol­lar signs. Big Data can allow us to break free of this lim­it­ing yard­stick and start mea­sur­ing in three dimen­sions. Many vis­i­tor inter­ac­tions are valu­able and suc­cess­ful for other rea­sons. Vis­i­tors might read the great blog post you shared, down­load a free report, chat with a cus­tomer ser­vice rep, sub­scribe to an e-newsletter, or com­pare prod­ucts with­out giv­ing you a dime. But all these touch points have likely made them more famil­iar, trust­ing, and loyal to your brand. And they’ve allowed you to gather more behav­ioral data, which you can now use to enhance per­son­al­iza­tion over time.

On the path to con­ver­sion, every step is impor­tant. Iden­tify each step, deter­mine what makes it valu­able, and opti­mize accord­ingly. You can then mea­sure suc­cess by whether or not one touch point led to the next.

2. Cul­ti­vate Exist­ing Customers

It may seem coun­ter­in­tu­itive to use Big Data to hone in on smaller tar­gets, but this strat­egy has proven results. For one, cus­tomer acqui­si­tion can be costly and time inten­sive. Stud­ies show “it’s more cost-effective to cul­ti­vate exist­ing cus­tomers than to find new ones.” Big Data can yield tremen­dous insight into the loyal folks who’ve already clicked through, sub­scribed, and made repeat orders. Inte­grate these indi­vid­u­als’ demo­graphic, behav­ioral, and purchase-history data and con­tinue pop­u­lat­ing emails and web­pages with per­son­al­ized mes­sag­ing that antic­i­pates their ques­tions and needs. You’ll make it easy (i.e., sim­ple) for them to stay loyal.

3. Gen­er­ate Insights, Not Reports

A report tells you the per­cent­age of vis­i­tors who clicked through, or the num­ber of would-be cus­tomers who aban­doned their cart. Insights tell you why. With Big Data, it’s pos­si­ble to answer ques­tions that we used to only guess at, such as “Who are the 15% who signed up and why?”

4. Pay Atten­tion to Deviations

Big Data can lib­er­ate mar­keters from lim­it­ing cat­e­go­riza­tions of cus­tomers. When an indi­vid­ual does some­thing unex­pected or devi­ates from the trend, we can take note and respond. What may have been per­ceived as a fail­ure of ana­lyt­ics, can now be an oppor­tu­nity for engage­ment. If a cus­tomer buys some­thing out of the ordi­nary, or fails to renew a stand­ing order, a com­pany can imme­di­ately reach out with dis­counts on a new line of prod­ucts, a sim­ple sur­vey, or a free­bie. This reminds peo­ple that you value them and can be flex­i­ble enough to grow with them.

Even neg­a­tive vis­i­tor expe­ri­ences can be turned into pos­i­tive oppor­tu­ni­ties. If you’re tap­ping into Big Data, you can lis­ten to cus­tomers across mul­ti­ple chan­nels, reg­is­ter­ing their com­plaint on Twit­ter, and send­ing them a per­son­al­ized mes­sage to rem­edy the situation.

Con­sumers Wel­come Relevance

Although we’ve all heard the buzz about Big Data and tar­geted mar­ket­ing being “creepy,” the truth is your vis­i­tors are ask­ing for a more respon­sive user expe­ri­ence. Accord­ing to Mon­e­tate, 75 per­cent of con­sumers don’t mind retail­ers using per­sonal infor­ma­tion when it makes their life eas­ier, and 85 per­cent under­stand that mea­sur­ing enables com­pa­nies to make more rel­e­vant offers. When it comes to Big Data, most con­sumers are opting-in and enjoy­ing the ben­e­fits. As long as mar­keters treat peo­ple as the unique indi­vid­u­als they are, and focus on per­son­al­iza­tion and sim­plic­ity, we can all enjoy a long, fruit­ful rela­tion­ship with Big Data.

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