There's nothing like a good old-fashioned romance between a man and his phone. Actually, Theodore Twombly fell in love with his phone's operating system after they started dating. Theodore is the main character in "Her," a provocative movie about how people personify technology to the point where we can "fall in love" with our devices. Of course, it doesn't hurt that the beguiling, sultry voice of the operating system is Scarlett Johansson.
As companies move to engage mobile users, they would be wise to approach acquisition and mobile database building from a customer-centric perspective. Mobile phones aren't just the receptors at the end of a powerful new marketing channel. They are an extension of people, carrying their friendships, photo and video memories, self-expression, and social connection to the world. Keen marketers would be wise to develop relationships with customers and their best friends, and not just use that friend to get to the person you want to talk to.
You had me at LOL
Starting mobile relationships with customers and building a mobile database requires connecting with people genuinely, and making them feel special.
The best way to increase mobile opt-ins is with people you know, your customers, and social media followers via email, on-site or in-product messages, newsletters, and social media accounts. Asking customers to text a keyword to a short code is quick and easy, though success mostly depends on the offer. For the general public, the offer is even more important because they are less familiar with you and what you have to offer.
To attract high-value users, tie the offer to your product. For example, opting in to monthly text coupon codes attracts people interested in your product, rather than offering a "chance to win an iPad" where users won't even remember your name.
Be creative as well. Redbox is renowned for its campaign where users send a text and get a coupon for anywhere between 10 cents and $1.50 -- a sort of discount slot machine. Others include memorable words: "text STEAL for a 50% discount," "text BFF for 10% off or LUV for 25%."
We just "get" each other
Google has a message for you: Optimize mobile delivery or suffer the consequences.
Google now punishes non-optimized mobile delivery for misconfigured sites for smartphones (and many other criteria), so if you don't do it yourself, you may drop in search result rankings. The same goes for mobile load speeds -- more than one second and down you go again.
Consumer response is clear. Approximately half of mobile users won't return to a company's mobile properties if they're not mobile-optimized, even if they like the brand. And the majority of users move quickly to another site if they don't find what they're looking for in a rapid fashion.
As always, tracking is imperative. There is a proliferation of mobile analytics platforms for a variety of mobile activities. Appsee, Google Mobile Analytics, and Mixpanel are powerful tools among many others. Deciding which to use depends on exactly what you're measuring.
Do you tell your friends about me?
I recently received a brilliant referral message from a friend. He had filled in a short "mad lib" about me and why I would love an offer for a particular designer clothing brand: "Joseph, I know you attempt to look great for happy hour so you'll get 20 percent off any of the new fall collection, just because of your epic friend Forrest." If he had posted "Get 20 percent off the new fall collection" on his Facebook timeline, I wouldn't have noticed and perhaps not cared.
Dropbox is famous for its successful referral campaign, rewarding customers with extra storage space for themselves and any friends they refer to the cloud storage service. The Give-Get construct -- give $10, get $10 -- has been used thousands of times for decades. The reason Dropbox succeeded here was because its offer was so attractive: extra storage space for free.
With a mediocre offer, customers won't share with friends unless you improve the presentation of the offer, so make friend referrals a one-to-one proposition. Don't ask users to simply post an offer on their social accounts, impersonally blasting their friends. I opened the referral email mentioned above because it was from a friend. The message was funny, customized for me, and sent to me because he knew I'd be interested in the product.
I really think this is going somewhere
Perhaps my strongest piece of advice for sustaining and building relationships is to deliver personally relevant, interactive content.
Blasting non-personalized posts, emails, texts, web visits, and other touchpoints is a thing of the past, especially as big data changes the game. Predictive analytics is a transformative way to deliver personally relevant content to customers. Consider that while 19 percent of brands personalized customers' web experiences last year, a full 59 percent expect to do so in 2014.
On the interactive side, one of my favorite companies constantly asks for ideas, feedback, and customer interaction in a gamified forum with brief, fun activities. I now see mobile communication from this company as an invitation to engage, rather than a request to read a generic update.
Also, be brief, and let your customers know they're valued and appreciated.
I recently had a company text me: "We'd like to give you one big, fat..." Five seconds later, a second text: "...THANK YOU." It said they appreciated my support for the company. There was no reward, no coupon, just one big thank you. And I loved it. Everything they did seemed to value customers first and marketing messages second, which of course was the ultimate marketing performance.
You're the only one for me
"I heartily endorse this product or service." These are the comically impersonal words of Krusty the Clown from "The Simpsons." We relate to it because we're constantly inundated with communication that's not personalized for us whatsoever. As noted above, machine learning and predictive analytics will change all this.
Machine learning doesn't just look at rudimentary user data and behavior. It interprets them continually. It scans billions of lines of data, looking for statistically significant patterns and interplay between variables. It can predict what customers will purchase, which customers will promote you on social networks (and on which social network for each customer), who's likely to cancel a subscription or not return to your site, and which customers will become most valuable after they sign up.
Imagine discovering that 65 percent of single women from New York will likely cancel their accounts based on language they use in customer support emails, time between logins, and sentiment interpreted in social media posts (especially during cold weather spells). Knowing these warning signs lets you respond at the right time and with the right message, per customer. What's more, your machine learning system can predict the likelihood that your fix-it strategy will work, per customer. And that's just the beginning. Predictive analytics removes much of the guesswork, providing for extremely successful marketing campaigns via any medium.
Happily ever after
A person's mobile phone is now an extension of who they are. Think of mobile as a relationship with the end user and his or her phone, rather than a communication medium. Fail to do this and your mobile users are going to "cheat" on you (they have other suitors), ignore you, or dump you ("it's not you, it's me"). Succeed, and the world is all dotted "i's" with hearts, walks on the beach at sunset, and finally finding "the one." Well, "the millions," if all goes well, so vive l'amour.