Real-Time Data: Introducing the RTM Wave

Real-time marketing: it’s a weird thing, isn’t it? We’re not used to seeing brands jump in on trending conversations, and it can be strange to see at first. When an airline talks about the royal baby, it’s...different. It’s hard to connect the dots between the brand, the trend, and the conversation. But still, RTM has taken off and every day I'm seeing more and more social marketing teams adopt the strategy.

But Where’s the Data?

To date, the conversation about RTM has been based on opinion. Some people think it’s interesting, others think it’s a flash-in-the-pan. But I’m an analytics guy, and I never listen to an argument without good data behind it. So observations and opinions aside, what I'm really itching to know is: Does RTM work?

That’s why I wrote Trendology—the first data-driven analysis of real-time marketing that determines what works and what doesn't. Data shouldn’t drive every decision we make as marketers, but we need data in our back pocket when we make decisions. So, for the sake of this blog post, let’s go find ourselves some data.

Let’s Pick a Trend and Give it a Try

In mid-September, as many of you remember, Apple had a PR problem on it’s hands. It’s new, gigantic iPhone 6 Plus, was reportedly starting to bend in people’s pockets. “Bendgate” was born, along with the trending #Bendgate hashtag on Twitter. This quirky news story began to build as the social conversation grew. After the trend really took off, brands hopped aboard as well.

So what did the people think of brands joining the daily trend conversation? Were they welcomed with open arms or were they asked to leave? Let's take a look...

I saw 14 brands partake in the #Bendgate conversation. How do we start to measure performance of their RTM efforts? Let’s get started by looking at how a brand has historically performed with engagement (Favorites) and sharing (Retweets) metrics on Twitter, and compare their RTM Tweets to those historical averages.

For each of the 14 brands, I pulled their last 3,200 Tweets from the Twitter public API and then stripped out all their retweets and replies, to avoid skewing our performance numbers. I then compared their #Bendgate Tweets to their historical averages (which, in most cases, only went back a few months.)

The results were kind of crazy.

On average, brands saw almost a 12,000% bump in Retweet performance, and a 6,000% bump in Favorites performance vs. their own historical averages. No, that wasn’t a typo—it’s ridiculously good. But these are just averages, and a few outliers can skew our understanding of the data. We want to look at the distribution of success.

Here’s is that view, and it’s a shape that I’ve seen again and again. I call it “The RTM Wave”:

Each bar on this chart is an individual brand, and the length of the bar shows it’s performance vs. it’s historical numbers. Usually I see a few brands that do worse than their past averages, but not this time. In fact, Bendgate is one of the best-performing trends that I’ve ever seen for RTM performance.

All 14 brands saw bumps in their sharing and engagement metrics by leveraging a trending topic and joining a conversation that was already top-of-mind for their audience. Pretty cool, right?

Data Can Cut Through the Hype

There’s been plenty of hype about real-time marketing, but data can lead the way by informing us about which strategies we should be using to connect with our audience. Bendgate is only one example, but the data shows that RTM is an effective marketing strategy, and it works time after time (when it’s done right). If you’re interested in the insights from over 100 brands doing real-time marketing, check out the Trendology book and let me know what you think.

Next week we’ll dive more into the different types of real-time marketing that brands can do. How much of this can be planned? How much has to be done in the moment? We’ll take a look.

Trendology: Download Introduction

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Chris Kerns

@chriskerns
Chris Kerns has spent more than a decade defining digital strategy and is at the forefront of finding insights from digital data. He currently leads Analytics and Research at Spredfast. His research has appeared in The New York Times, Forbes, USA Today and AdWeek, among other publications.