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Pin to purchase: How retailers can leverage Pinterest data like never before

Pinterest may just be the epitome of line-of-sight marketing for the digital age. Brides-to-be "pin" their favorite wedding dress designs and new homeowners follow DIY window treatment boards on the image-sharing social network. Pinterest is the ultimate wish list, radiating millions upon millions of consumers' intent to purchase. Pinterest now accounts for 44 percent of e-commerce related shares, and its sharing stats are growing.

Until recently, retailers faced one big problem: their ability to tie individual pins to actual products for sale was limited. But with the release of its automatic programming interface (API) late last year, Pinterest granted brands valuable insight into the vast digital trove of users’ aspirational consumerism.

It’s information that retailers - several months into using the API - are leveraging to improve online shopping experiences, from product displays to recommendation features. Keep in mind that we're still in the early stages of gaining marketing insights and identifying opportunities born out of this new API. But as more brands gain access to Pinterest data, they’ll integrate findings into channels beyond the Web and create more personalized experiences for wishful customers via email and mobile.

What does the Pinterest API do?

In the past, some retailers tried to scrape Pinterest and their own websites, compile the data and draw conclusions. The Pinterest API basically is a widget that grants retailers direct access to previously hard-to-gather data. Specifically, retailers can now track:

  • Top pins: The most popular images that consumers have pinned or re-pinned from others
  • Most recent pins: A timely stream of the latest and greatest pins
  • Related pins: Correlations between different items that people are pinning
  • Pins from search terms: Lets retailers display trending results for key terms like “rain boots” or “grilling recipes”

When Pinterest first released its API, only select brands, including ModCloth, Disney, Whole Foods, Zappos and Target, were invited to test it. The service still is in beta mode, but developers who would like to participate now can request access.

How are retailers using the API?

Most brands that use the API concentrate on the Web. They’re building pages of “top-pinned products” and including stats next to items that indicate how many times they've been pinned.

Take online vintage retailer ModCloth. One of the API’s early users, ModCloth has a section on its website called, “Most Popular Pins on Pinterest,” where people can view and purchase items that have garnered attention. In December, Target launched a microsite called "Target Awesome Shop," which features the most popular pinned items in a given day and their reviews from Target.com.

The real potential lies ahead

Following ModCloth and Target’s lead, retailers are beginning to add similar curated Pinterest pages to their websites. In the future, we’ll see further development of site sort algorithms. Right now users sort products based on top sellers, price and relevancy. Eventually brands will offer the option to sort by top-pinned products.

The real excitement with the Pinterest API will occur when retailers move beyond the Web and incorporate their findings into other channels like email and push notifications. Brands will find ways to incorporate personalized recommendations based on customers’ pin preferences into email.

Say a person pinned an area rug, for instance. Eventually marketers will be able to send an email that says, “Thanks for pinning that designer area rug. Here are other products that you may be interested in. Check out this table, sofa and lamp that go really well with the rug.”

It becomes a cross-sell and upsell merchandising opportunity based on having that user-level data available and leveraging the Pinterest API to fill in that data gap for cross sell and upsell recommendations.

Retailers who are able to take advantage of this rich data from Pinterest’s API will be able to deliver a more personalized customer experience as they listen in to these key signals of future purchase intent. This will allow them to realize better engagement metrics, higher average order value and greater conversion rates coming from this pivotal social shopping site.

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