“Big data” is hot.
If you look at how the phrase “big data” is trending on Google Trends, you can see that the term took a huge leap between 2012 and 2013, and has been rising ever since. It’s huge (no pun intended). It’s everywhere (even on our blog). In fact, as I was writing that last sentence, I received an email that began: “Big data is a top concern of marketers around the world – it has the potential to change nearly everything about the way they do business.” Yup.
But before marketers get overly concerned with BIG data, I’d like to see more companies do something interesting with, well, data.
A few weeks ago, we talked about how Pinkberry uses data to make their emails more targeted and relevant (and to motivate people like me to binge on froyo). Today, I’d like to share a story about how another company, Fandango, is taking data – and personalization – to an entirely new, multi-channel level.
Fandango Uses Data For More Personalized Experiences
My wife and I went to the movies last week. While I realize this isn’t a big event for most people, anyone with young children understands how rarely we get out of the house. We decided to see The Grand Budapest Hotel, the new movie from director Wes Anderson (Bottle Rocket, Rushmore, Royal Tenenbaums, etc). I fired up the Fandango app on my iPhone, searched for our date-night movie, and – boom – 45 seconds later, our tickets were reserved!
Nothing earth-shattering. Yet.
But what happened next was pretty cool. On our way to the movie, I opened up the Fandango app again. The screen now displayed a big “countdown” to the start of the movie. Fandango was using the data – our movie’s start time in this case – to serve up relevant content. Again, this was not mind-blowing, but it was useful. They knew what movie we’d bought tickets for, factored in the time the movie started, and used it to help us arrive in time.
What Fandango could have done better: I had to go back to the app to see the countdown. What if they sent me a text message alerting me that the movie was starting in 10 minutes? Sure, I’d have to opt-in to this first, but there is a much better chance I’d see it!
We snagged a large, extra-butter popcorn and dashed into the movie. A few hours later, as we were walking out of the movie, my iPhone buzzed. No, it was not our babysitter asking a question about the kids. Instead, it was from Fandango! See screenshot below:
Fandango used the data to know exactly when the movie ended … and then sent me this app alert shortly after. Fandango also used the data to know what movie we watched, and then included the name of the movie in the message. This is a great example of how data can inform real-time personalization.
Personally (no pun intended), I love this approach. My wife and I had just walked out of the movie, so it was very top of mind. Talk about the right message at the right time!
However, I can also see how some people would think this messaging was “too soon.” Again, we had just walked out of the theater. We were having a post-movie debrief and BUZZ! BUZZ! And to be honest, even though I liked the timing of the message, I got distracted and forgot to rate the movie that night.
What Fandango could have done better: Instead of a “now or never” option to rate the movie, some sort of “snooze until tomorrow” or “send me an email” option would have been a nice touch.
Speaking of email, Fandango sent me one the morning after we saw the movie, asking the same question: “How did you like The Grand Budapest Hotel?” Was this because I didn’t rate the movie when I first had the chance? If so, kudos to Fandango. If they were going to send me the same email regardless of whether or not I’d already rated it, they lose points in my book. But either way, they used the data to personalize the subject line with the movie name. Easy and effective.
But the personalization didn’t end there. What other examples of “using the data” can you spot in the email below? (Scroll down below the screenshot to see all the ones I found. But don’t cheat!)
Note: When we purchased these tickets, I did not log in. This is why the salutation read, “Dear Fandango Customer” and not “Dear DJ.”
Here are all of the ways of using data in this email that I spotted – let me know if I missed any:
1. Custom Image: Fandango grabbed the movie image and plopped it into the left side of the email. Instead of some generic stock image, they actually used the movie art. Nice!
2. Custom Links: Not only did Fandango personalize the email with the actual name of the movie we just watched (as opposed to simply “the movie”), the link pointed me directly to the page where I could review the movie. While this sounds obvious, too often links take clickers back to a generic page where they have to search. If you want me to take some action, make it easy!
3. Suggestions: “We thought you may also like…” was a nice upsell opportunity. I’m not sure what intelligence is behind that suggestion (as it happens, I’m not really the Captain America type), but my hunch is that the more data they have on me, the more customized and personalized this suggestion becomes.
What Fandango could have done better: Their “Be the first to know when the Grand Budapest Hotel comes out on DVD” link took me to a landing page, where I had to check a box (AKA do more work). Instead, they could have captured my intent immediately after the click and directed me to a thank you page.
Big data is all the rage. The potential to do something interesting with that data to create more personalized user experiences is ginormous. However, if you don’t have the resources – human capital, financial capital, etc. – to leverage big data, start small. As described above, Fandango is using some pretty basic data they have about me to personalize my experience across channels (app, mobile/SMS, web, and email). It’s simple, yet incredibly effective.
What are you doing with data to create a more personal, cross-channel experience for your audience?