When big data gets personal
Until recently, it seemed big data was, well…big. But that may have changed.
At this year’s Data Marketing 2015 Conference (#DM2015) one of the opening keynotes was pointedly titled “Big Data—From Hype to Here.” As a topic, big data was relegated to pre-conference workshops. Last year, big data technologies like Hadoop — the groundbreaking open-source framework for processing large data sets — dominated main-stage conference tracks.
We’re not the only ones who noticed. This summer, Datanami reported that Gartner dropped big data from its coveted Hype Cycle for Emerging Technologies.
What’s changed, according to Gartner, is that big data now exists behind other technologies on the Hype Cycle (Internet of Things, machine learning, wearables and the like). In this respect, it’s moved from the front page to the back office.
Although there were some impressive examples of marketers using current Hype Cycle technologies in their campaigns, customer personalization was the most dominant theme at Data Marketing 2015.
Here are three key takeaways from the conference that challenge the way we use big data now.
1. Don’t make the last customer transaction your first point of reference
Focusing solely on the last transaction can lead marketers to generate negative personalized experiences. Think of a time when a product you bought appeared in product recommendations, or when ads for your purchase continued to chase you around the web or—in the case of emails—repeatedly prompted you to buy the same product long before you needed to replace it.
Instead we should analyze customer transactions along with other sources of available data to create the rich profiles needed for highly relevant personalization.
We should analyze customer transactions along with other sources of data to create the rich profiles needed for highly relevant personalization
Take The North Face, for example. The company considered where and how its products are used and combined that knowledge with richer, data-driven profiles of its customers. Since 80% of customers who buy hiking boots are also runners, the company also promotes running gear. It even offers adventure travel rewards. By doing so, The North Face went beyond basic transactional data to create a much deeper connection with its customers.
2. Strive for a zero-click user experience
As we design user flows aimed at increasing page visit durations and decreasing bounce rates, we can use our vast collections of data to create web experiences so personalized that a single visitor sees everything she needs in a one-page representation of the site. While it may not make sense in all cases, the goal of creating one-page websites for individual customers will challenge the way we think about and design user experiences.
3. Tell your customers what you’re doing with their data
Candor can build trust. So don’t be afraid to talk about what you’ll do with that information you’re gathering. Embrace privacy legislation and don’t bury your intended data use in your privacy notice with your other legal disclaimers. According to a joint presentation from the Canadian Office of the Privacy Commissioner and Osler, privacy isn’t just a legal issue; it’s about customer trust. From their deck: Trust = Value x Privacy x Security. They believe marketers could see higher conversion rates if they put the intended use of form data on the form itself, in plain sight.
Marketers could see higher conversion rates if they put the intended use of form data on the form itself, in plain sight
Lasting Impressions
Today, big data serves a bigger purpose: creating complete customer personalization. Misusing it can create an experience akin to leering, lurking, even creeping.
To deliver truly innovative, personalized customer experiences, it requires some effort to combine and analyze behavioral and contextual data with transactional data to create a truly thoughtful—and effective—customer experiences.
Stay tuned! We’ll be sharing more insights about personalization in future posts.