In early 2015, we were approached by a luxury apparel retailer about designing an advertising campaign that would help the company convert more of their engagement into sales. The client had built a large and loyal audience by cultivating a luxury lifestyle image that appeals to Tumblr’s young, aspirational, and affluent audience. One thing they noticed was that their most engaged followers were existing shoppers, so a key criteria of their campaign was that it would target those users and their followers.
Tumblr and Curalate (curalate) designed a unique ad targeting solution using their advanced image recognition software, which made it possible for the client to target users based on images as well as text. First they scanned the client’s online store and built a library of product images—these could be standalone photos of a handbag or blouse, or of a model wearing the client’s merchandise.
They then scanned the Tumblr firehose, a massive stream data containing all the public interactions on the network (posts, likes, reblogs, etc.) looking for anything pulled from the client’s online store. Since the software was scanning the image, not the source, it could even identify images that came from another social network.
The whole process looked something like this:
By targeting users who were already actively posting and sharing the client’s content, image retargeting drove a 59% increase in overall engagement compared to the month before. That engagement translated directly into additional site traffic and sales:
- 2.4x increase in unique visitors to their online store.
- 20x increase in sales attributable to a Tumblr post compared to untargeted Sponsored Posts.
- 31% reduction in the campaign’s effective cost from earned media.
- Reach known shoppers with image retargeting to increase sales and reduce cost. Tumblr and Curalate’s image retargeting solution allowed the client to focus on users who share content from from their online store. These users were naturally more receptive to the client’s advertising and were much more likely to be converted into shoppers and buyers.
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