June 4, 2013 Leave a comment
At Digiday we have this thing we call Buzzword Bingo at events. The idea is that people get a prize by plotting out various buzzwords. I like to have a side bet nowadays of what will get checked off first: “native advertising” or “Big Data.” I don’t have the numbers totally crunched but I’m pretty sure Big Data is in the lead.
This is normal. Big changes – think the cloud – frequently become marketing terms that quickly lose all semblance of meaning. It’s easy to poke fun at them, or even dismiss their importance entirely. That would be a mistake with Big Data. It means something – but that something has been lost by all the marketing that’s overwhelmed it.
I say this because I feel that our ability to collect so much data, crunch it, etc. has sometimes caused us to lose sight of the ultimate goal. Take publishing. In my role as editor, data is incredibly important. I look at data from Google Analytics, Chartbeat and sharing services in order to determine answers to a few simple questions: 1) Is what we’re doing working? 2) What should we do? Now this data is an input. It’s just that. Our audience development manager, who is very young, mentioned to me that Upworthy uses about 200 versions of a headline to see which one will work. That’s OK to me, but it’s also a bit of a shortcut. In the end, I can’t make editorial decisions based purely on the numbers. All our stories would be Top 15 Worst Brand Screwups in Social Media. Our goals of building a strong brand and a loyal audience that respects us for honest coverage of important issues would be compromised. There’s not an algorithm for that. It’s a sensibility.
Data is an input that will help. When it comes to digital media, data is about two things from my point of view.
Data allows companies to better serve their customers. This isn’t new – companies have always relied on data. It’s just that now, there’s a lot more of it. The really interesting part about data is when companies improve their services for customers. This is the promise of Big Data to me. I go back to Amazon’s collaborative filtering technology. At the risk of sounding like the old guy my millennial colleagues like to paint me to be, this was a game changer. Suddenly I was able to find related products of interest to me. I knew full well Amazon was tracking my purchases and browsing to do this. And I loved it! Same with Netflix – I love it tracking me. I want it to track me. I need it to track me. I want it to figure out for me what to watch.
Data allows digital media to be more efficient and useful. In this world of data, we should see fewer, better ads. That’s the promise. We operate online leaving a digital bread crumb trail. Nothing is free in life. The implicit tradeoff is that we’ll allow publishers and advertisers to responsibly use this data in order to improve the ads we see to pay for the content and services we use. This is noble, and important – and I’m not saying that because eXelate bought me a lovely lunch. You can feel the “but” coming here, right?
The simple truth is the promise of Big Data in advertising is confusing. There’s an idea on the data side of this business that marketers must speak the language of technologists and not vice versa. We see this all the time in how the many technology companies try to explain what they do. Khurrum (Malik, CMO eXelate) and I were talking the other day, and he brought up the concept of the tyranny of knowledge. It fits perfectly for one of the biggest challenges of this industry: how to simply explain what it does. Too often there’s an assumption on the part of the data-crunching techies that everyone understands this – or should. It leads to people on the marketing side not asking simple questions for fear of looking foolish. But these are the questions that need to be asked: How does what you do help me serve my customers better? How can it help make advertising better and more efficient?
That brings me to where I see this idea of Big Data going. And it’s away. It’s like how social media is fading into the ether. “Social” is part of everything. I’d coopt something Charlene Li said years ago about social: It’s like air. So too is data. It’s everywhere. It’s not a feature, it’s the environment. Once we get over this idea that data is something new and exotic, to be mined maniacally, collected and protected zealously, we can get back to what I mentioned at the outset: How can we use these raw data inputs to help people? How can data be used to tell better stories? How can data improve services and even create entirely new ones?
To answer these questions, it is necessary to move a step further from Big Data – it’s time for quality over quantity.