Pinterest is the newest social network that I cover in this book. Research done by other organizations, as well as my own experience, shows that it is very closely tied to purchasing behavior. Users have collections of products they want to buy or they want given to them as gifts. They have images of food they’d like to cook (and ingredients they’ll need to buy). And they keep inspirational collections of clothing styles and accessories they want to wear. Clearly it’s an important platform to investigate for use in your business.
The Pinterest API, however, is not public, and the ability to do qualitative research on the site is very limited. I was able to use search engine APIs and their cached copies of pages to collect a database of more than 11,000 pinned images and the number of times each was repinned, liked, or commented on.
This chapter is quite short, but Pinterest commerce-friendly usage and it’s unique position as a visual content–based social network means that I still felt it was worth including these data.
The first characteristic about pinned content I analyzed was the length of the textual description attached to the image, in characters. An anecdotal glance over random pins tells me that short descriptions are best, but I’m not one to rely on gut feelings and small sample sets like that.
In my data, I found that repins were highest for images that had descriptions between 100 and 200 characters (Figure 6.1). This is similar to the length of ...