AI and Language Testing: Everything You Need to Know About Testing Language to Increase Marketing Performance
Cutting through the noisy world of content marketing and standing out in today’s crowded inbox is crucial to capturing audience engagement, but is also a common and universal challenge for brands. The challenge is perhaps even greater for retailers operating in a cluttered environment where the noise is louder than ever. Effective marketing copy, optimized for the tastes and preferences of a brand’s unique audience, is the most effective tool to help cut through the noise.
But how do you maximize the effectiveness of copywriting?
This post offers some guidance on optimizing marketing language with a specific focus on one important element of this—language diversity—and invites you to try out a new tool developed by Phrasee for retailers to test the linguistic diversity of copy and find out how you measure up against industry competitors.
Increasing Copy Efficacy Through Better Use of Language
There are many factors that separate “good” marketing copy, the kind that engages customers and generates revenue, from “bad” copy, the kind that does little more than annoy customers and damage your brand. Understanding these factors can often mean the difference between marketing success and marketing failure.
To understand exactly what makes marketing language work, Phrasee has analyzed the performance of millions of email subject lines across dozens of industries over the years. This exhaustive process taught us a lot about what makes an effective email subject line—and what doesn’t.
The story that all the performance data told us was one of rapidly evolving subscriber preferences, shifting audience tastes, and an urgent need for ongoing, rigorous subject line split testing to keep brands ahead of the curve.
But there’s another part of the story all those email sends had to tell: when it comes to email subject line performance and effective split testing, language diversity matters.
Language Diversity and Email Marketing Performance
Phrasee’s data science team analyzed over 420 million subscriber interactions with email subject lines and identified a clear correlation between language diversity and email subject line performance. Our team found that split testing using a diverse set of language properties will, on average, lead to an open rate uptick of 5% to 10%.
Recycling the same old words, phrases, and themes again and again simply doesn’t cut it anymore. It takes fresh, engaging language to capture and maintain subscriber interest. If you keep plugging the same language that worked a month ago into your subject line split tests, all you’ll get is a poorly performing subject line that tested better than a few other poorly performing subject lines. And what good is that?
Incorporating more linguistic variance into the copy you test on your audience is the only effective way to find out what’s going to maximize your subscriber engagement today. And that’s important, because maximized subscriber engagement means more opens, more click-throughs, and more revenue for brands.
This fact is just as true regardless of which brand is sending the campaign, regardless of which industry that brand operates in, and regardless of the demographic makeup of its audience. Hence, upgrading the linguistic diversity of brand’s subject lines is an ideal way to differentiate a brand in the inbox and gain a subscriber engagement advantage over the competition.
Measuring Language Diversity
Measuring subject line language diversity is hard. It took Phrasee’s team of data scientists quite some time to figure out how to do it effectively and consistently. With the most effective AI technology, we’ve built an easy-to-use tool for retailers to gauge the language diversity of their email subject lines and to see how they measure up against industry competitors. It’s free, calculates your language diversity score, and provides an analysis of linguistic optimization opportunities in a matter of seconds, allowing you to maximize email marketing success.