The Power of Language in Mobile Messaging

Digital messaging has evolved since the early days of email marketing into a powerful, succinct and timely medium. The proliferation of smartphones is connecting consumers to each other and to their favorite brands like never before. What was previously in the wheelhouse of executives and jet-setters, the mobile web has made it possible for each and every person to browse the web and communicate via SMS, MMS, social networks, email and even that most tried-and-true of channels, voice, in one small, pocket-born package.

Mobile devices bring together multiple communication channels onto one screen: email, web and the more native push (SMS, rich inbox and MMS). Of these channels, push notifications allow companies to target and communicate with customers based on the abundant criteria that can be gleaned from their devices. The 256-byte brevity of push demands that marketers carefully plan and test the content of each message to gauge its effectiveness in driving customer engagement, retention and conversions. In today’s data-rich society, not testing the language in push notifications is essentially a missed opportunity, tantamount to leaving money on the table.

Savvy marketers can leverage the tried-and-true A/B split test methodology to gauge the tone and impetus of a message before delivering a campaign. Case in point: The Astrologer, a horoscope and lifestyle mobile app seeking to boost engagement, sent out variations of relevant astrological sign-specific push notifications that increased open rates from 2.8 percent to between 4 percent and 10.5 percent.

Here’s an example: “Hey Libra, got a problem?” vs. “Hey Libra, got a question?”

The second message saw a modest lift in open rate, from 3.8 percent to 4.1 percent. This implies that users respond better to more positively worded messages posed in the form of a question. The lift makes it clear that testing messages is critical to the success of push notification campaigns. Push isn’t just a broadcast medium with a one-size-fits-all message; it needs to be grounded in relevant data that personalizes the call to action for each customer. Any uncertainty about what should be the most relevant call to action can be tested and retested to ensure that messages are engaging rather than a nuisance to recipients.

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