Data nerds and stats enthusiasts can rejoice – Pinterest is more than just fashion, home décor, crafts and cute animal images. It’s also a massive treasure trove of information about the tastes, interests and habits of millions of people all over the world.
In a recent interview with Mashable, Pinterest’s data scientist John Rauser says, “At its core, Pinterest is a data company. When people make a pinboard, they’re telling us important information about how they view the relationships between those concepts — every new pin gives us new information.”
Rauser isn’t the only person that understands the value of this information. Brands are taking notice of pinning patterns and responding enthusiastically, and several companies are getting into the Pinterest Big Data analytics game.
So, what can we hope to learn from this wealth of information? Analysts are actively exploring these three data avenues on a large scale.
Effective Pins & Boards
The artsy, subjective nature of pinning has very quickly spawned the science of pin optimization. Bloggers, e-commerce brands and other content creators are digging into the kind of images that result in the highest engagement measured by likes, re-pins and comments.
For example, statistics indicate that product pins with a price will generate about 25% more likes than pins without. Likewise, bloggers and online magazine publishers have responded to the high click-through rate of “Twenty Things to do with XYZ” types of posts by creating similar content that drives traffic to their own site.
Increasingly, analytics firms are turning to deeper image analysis to tease out the specific attributes of the most successful pins, such as size, color scheme, texture, and object placement, in order to establish the elements of a perfect pin.
Actions on Pinterest
Pinterest’s latest announcements indicate that the company is shifting some focus from pure growth to creating a more engaging experience for its users. In that vein, they’ve recently made some platform changes, which are not only in response to user behavior but are geared toward influencing user behavior as well. Specifically, the new “People who pinned this also pinned” feature is designed to keep users engaged with the site for a longer period of time, which, of course, means more pins, re-pins and site traffic.
When Pinners Leave The Site
This is where the e-commerce community collectively jumps for joy. Retailers pay very close attention to where their customers are coming from, and it turns out that Pinterest has morphed into one of the most effective brand engagement tools since the free sample table at Costco.
Not only does Pinterest drive more conversions than most other sources (at a higher average revenue per transaction to boot), it’s also entirely user driven (read: low-cost) and inherently viral. A single pin from one brand by an influential pinner can reach 1,000+ first-generation re-pins. That means each one of those 1,000 pinners are sharing the pin with all of their followers, and so on down the line. Influential pinners also tend to share each other’s content, which translates to exponential pin virality potential. What this means for retailers is that investing resources into creating content that appeals to an influential pinner can effectively expose that content to millions of Pinterest users in a single click.
Influence Matters
Pinterest has changed, and continues to change, the landscape of e-commerce, self-publishing, brand recognition and grassroots marketing. A lot of what makes a pinner influential, or a brand popular, centers on intuition and just plain good taste. However, when it comes to driving traffic and revenue, brands should continue to keep an eye on the numbers.
Looking for more information about good pinning practices? Check out our series about how to optimize pins for creating effective, meaningful content that performs well on Pinterest.
