Recently, I traveled to New York City to attend Strata + Hadoop World. In the tech industry, it seems like there are more and more major conferences and events that spring up every year. Strata really stands out as the marquee annual event for the Big Data and analytics community, though, and it’s always extremely rewarding to listen and learn from peers, customers and influencers from across the globe.
This year, I presented a session on “Talking to your Digital Customers.” I focused on helping conference attendees that came to my session better understand their customers by harnessing the power of behavioral analytics on event data. Event data is not like any other data out there. It may be defined as any occurrence that has time, entity and attributes, but its meaning for companies is much more than that. Any swipe, scan or click your customer makes can be found in your event data. You can think of the famous artist Georges Seurat, known for his pioneering Pointillism technique, when you try to comprehend event data: each event, by itself, seems insignificant and almost invisible, like a dot on a canvas. But when properly put together, they paint a vivid picture.
Most businesses think they understand their customers, but if you’re not carefully analyzing data, a lot of potential insight gets lost in a blur. Rudimentary analysis can tell you what a customer did and why they did, while more advanced analytics can tell you what a customer will do in the future and how you can even change their actions.
You’ve probably heard of the social app Tinder. Recently, Interana announced how we are helping Tinder better understand their users by analyzing their massive quantities of event data.
Download the case study on how Tinder is utilizing behavioral analytics.
Web companies always deal with a lot of data. But even by that standard, Tinder gathers enormous quantities. The app is used by several millions of people across the globe, who collectively account for 1.8 billion swipes and 26 million matches each day. The company recently surpassed one trillion rows of data, the largest so far of any of our customers!
Before Tinder deployed Interana, they were mostly relying on Hadoop. Only a small group of highly skilled IT experts could access Hadoop, and even for them, it was daunting. Overall, the process of analytics was slow and cumbersome. As a result, Tinder didn’t have full visibility into user behavior, which limited opportunities to improve the app and attract new users.
Tinder now has Interana to rapidly analyze its surging quantity of event data, offering insights and answers in real time. With Interana, it never takes longer than seconds.
Tinder’s VP of technology, Dan Gould, agrees with us that data shouldn’t be kept in some “magic temple” where it’s only available to a privileged few, as was the case when they were just using Hadoop. Interana’s interactive dashboards and the Retention View provides every Tinder employee a self-service experience, while allowing different teams to easily share insights they’ve uncovered and collaborate with one another.
One of Interana’s core appeals is that it makes data accessible to both data scientists and general business users. One of the company’s marketing managers told us he never considered himself a “data person,” but now is comfortable enough to complete nearly all his data tasks independently. That autonomy is critical: It’s everyone’s job to listen to the customer, so it’s everyone’s job to look at data.
To understand your users, you need an analytics solution that’s FAST: flexible, accessible, scalable and transparent.
Are you using a FAST tool for analytics? If so, your event data might paint you a picture of customer behavior as nuanced and colorful as Seurat’s above. If not, you may be left with a picture that looks more like this: