Any marketer knows that data has revolutionized the way we work.Once, we built campaigns and hoped for the best; today, we can seeexactly how each campaign tactic performs. But all of that data meansnothing if we’re not using it to keep improving — which is whereoptimization comes in.
Last month, Alice Avery, our Content Marketing Analyst here atSalesforce, attended a conference hosted by San Francisco-based A/Btesting company Optimizely.
Marketers, listen up!
1. Set goals before you start
“It’s pretty important to decide what success is before you start your experiment,” Avery writes. “‘Make the page better’ or ‘help people find what they’re searching for’ arenot clear, actionable goals. A good hypothesis has a variation (the B to your A) and clearly defined metrics.”
2. Think big, not small
Advises Avery: “Take a step back, and think aboutthe big picture for your site. One of the best use cases for A/B testing is site redesign — test the alternative design against the originaland, based off results, hone in on details as you progress.”
2. Keep it simple
“There’s a statistical reason to keep itsimple: error rates are affected by the number of variations running at a time, and the more tests you have, the longer it can take to determine a winner/loser,” Avery shares.
4. You’re probably wrong
Put aside your own preconceptions (and otherpeople’s, too). The point of a test is to uncover solid facts, notconfirm what you already think you know.
5. Failure is OK
“Just as you’re getting excited aboutall the cool stuff you can test, we have bad news: most tests end in astatistical tie,” Avery writes. But aspects of the test might spur newideas: “Maybe one segment like mobile or existing customers couldhave determined a winner/loser, and you can dig into that a littlefurther to develop new hypotheses.”
6. Start with qualitative testing
Not sure what you want to optimize? Start with a simple survey to see what your readers are thinking about your website or blog.