As your com­pany builds and matures its opti­miza­tion pro­gram, it’s worth con­sid­er­ing how you can ben­e­fit from the trail already blazed by other suc­cess­ful opti­miza­tion pro­grams. Win­ning in the opti­miza­tion game requires effec­tive plays, and I’d like to share some of the com­mon­al­i­ties among the suc­cess­ful, more mature opti­miza­tion teams that I’ve come across.

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Let’s look at five plays that can help you win in the big leagues:

1. Accel­er­ate your test­ing velocity

Many com­pa­nies engage in lim­ited A/B test­ing, but this does not amount to a true opti­miza­tion pro­gram. Test­ing offers lit­tle value when not used reg­u­larly and in a dis­ci­plined fash­ion. Effec­tive opti­miza­tion requires ongo­ing test­ing built around a well-developed test strat­egy and well-defined methodologies.

Suc­cess­ful orga­ni­za­tions make opti­miza­tion an iter­a­tive process in which suc­cesses inform what and where they test next. This enables them to test more effec­tively and demon­strate value to man­age­ment. In turn, that helps them gain the bud­get, resources, and head count to expand the pro­gram, run more tests, and see even greater returns.

2. Use a vari­ety of strategies

As a gen­eral rule, I’ve noticed that com­pa­nies with the most suc­cess­ful opti­miza­tion pro­grams use a com­bi­na­tion of strate­gies. Many of these pro­grams start with sim­ple approaches that deliver quick wins—for exam­ple, geo­tar­get­ing, in which con­tent is tar­geted based on a visitor’s loca­tion. They might also tar­get based on con­tent affin­ity, another proven and pop­u­lar approach for increas­ing rel­e­vance and rev­enue. As these pro­grams get quick wins under their belt, they gain expe­ri­ence and build the con­fi­dence to start using more strate­gies. 

3. Lever­age more data

Great mar­keters have great instincts, but if they don’t com­bine data-driven insights with instincts, they limit their effec­tive­ness. Data informs mar­ket­ing deci­sions and often reveals anom­alies and trends that might not be read­ily appar­ent to even the most sea­soned marketers.

Suc­cess­ful opti­miza­tion pro­grams lever­age as much data about vis­i­tors as they can to iden­tify high-value cus­tomers. With the right data, mar­keters can iden­tify the audi­ence seg­ments that con­vert more and gen­er­ate more rev­enue, enabling them to best allo­cate lim­ited mar­ket­ing dol­lars. The more data they use to under­stand their vis­i­tors, the bet­ter equipped they are to serve them.

4. Extend your opti­miza­tion reach

Many com­pa­nies start by opti­miz­ing only their land­ing pages, test­ing to see what con­tent dri­ves higher con­ver­sions from paid and organic search traf­fic. I’ve noticed that the more mature opti­miza­tion orga­ni­za­tions have expanded those efforts, iden­ti­fy­ing addi­tional high-impact, high-potential loca­tions on a web­site, and test­ing and tar­get­ing on those loca­tions to improve their offers and con­tent and increase conversion.

Those same orga­ni­za­tions also extend their test­ing and tar­get­ing to other dig­i­tal channels—for exam­ple, to email, social sites such as Face­book, and mobile sites and apps. To do this, they must often work across orga­ni­za­tional teams, for exam­ple social mar­ket­ing, to build opti­miza­tion strate­gies into their mar­ket­ing efforts.

5. “Democ­ra­tize” optimization

By democ­ra­ti­za­tion, I’m talk­ing about enabling mar­keters out­side of the core opti­miza­tion team to try out their ideas by test­ing and tar­get­ing con­tent and expe­ri­ences to their impor­tant audi­ences. These mar­keters include prod­uct and brand man­agers, edi­to­r­ial teams, con­tent strate­gists, and merchants—people who have a big stake in the suc­cess of their com­pa­nies’ dig­i­tal strat­egy and want to have more con­trol over the expe­ri­ences that impact KPIs. Typ­i­cally, line-of-business mar­keters are not expe­ri­enced testers, so the tools they use must build in best prac­tices and intu­itively walk them through each step required to build an effec­tive test.

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