Retail

Are Buyable Pins Working For Pinterest?

Social media has a basic business model problem. It is good at drawing in eyeballs, but turning eyeballs into dollars isn’t always so easy — unless one has a truly unfathomable number of eyeballs to call a base (like Google or Facebook) so as to make advertising an extremely lucrative enterprise.

Pinterest since its inception has found itself square in those cross-hairs — a popular place to hang out on the Web, and certainly the inspiration for many random acts of commerce — but one standard deviation removed from the clear path to purchase.

Buyable pins, which let consumers one-stop shop it within the site itself, are one push in the monetization direction, but it is only available on iOS and Android. That, however, seems due to change, as buyable pins are soon coming to Pinterest’s website as well.

“We have over 100 million users on our platform. Almost no retailer has 100 million customers. Just looking at the math, most people on Pinterest haven’t shopped from any particular retailer. If Pinterest can help consumers find new products and brands, he says, it will have a very powerful eCommerce platform,” noted Michael Yamartino, Pinterest’s head of commerce.

Yamartino further noted that while it is still early days for the service, there are 60 million buyable pins from over 10,000 brands.

“Last year we were focused on building out the platform,” he says. “This year we want to make sure the shopping experience is terrific. That means finding more ways to connect users to relevant products.”

The move to the Web allows Pinerest to capitalize on desktop computing superior conversion rate. On average, desktop users and tablet users buy about equally often at 2.9 and 2.8 percent, respectively, whereas smartphone users’ conversion rates hover around 1.7 percent. Pinterest is also working on being a better matchmaker for its buyable pins – and putting the right pin in front of the right consumer while also offering enough product differentiation.

“These are complicated problems to solve,” Yamartino says. “It requires us to understand a lot of different signals. But when we figure them out, we’ll have an extremely powerful discovery engine.”

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