Social shopping services are a strange grab-bag of sites all trying to crack the nut of how to monetise social networking around shopping, which is most social when it is real-world, not virtual. In April Wishpot took $1 million Series A for a service that lets you collect and and share information about items you find online and in stores, via texting the site. Users can later view saved items, research prices, view ratings and reviews, ask friends for opinions or share recommendations. It competes in the same space as Kaboodle, Stylehive, Yahoo Shoposphere, Zlio and MyPickList. Kaboodle – which has has $5m in funding to date – lets you collect information from the web about things you may be interested in buying. The usual ‘social shopping’ site of reference is ThisNext, where people recommend their favorite products so others can discover what’s best to buy online.
However, most of these sites are very defined and process driven. They just let users say “this is nice, this is nice, collect and store” and then not much else happens. The sites tend to be too much novelty and not enough utility.
Skimbit is a UK-based site is this vein, but which is re-launching as a social booking site for actually making decisions about the stuff you want to buy. In the process it has created a new and subtle way to generate affiliate revenues without bothering the user, selling to them, or using up screen real-estate with terrible ads.
Skimbit has recently been signing deals with US social sharing distributors like Add to Any. It has also gone live with an affiliate engine, which means the site now earns money from sales leads from its site to any merchant it is connected with, turning it into a kind of user-generated product comparison site.
Here’s a scenario:
You are trying to find a coffee table. You go to a big furntiture store online, and while there, as you click through the products you like you use the Skimbit browser plugin to add the product to your skimbit product page, collecting products as you go. What other social bookmarking sites do is put this into a flat list, usually with tags. Skimbit, however, puts the products into a project page which is pre-configured by you based on the criteria you think is most important, so price, dimensions, style etc. All the options you bookmark you then save with the image description. Once you have your project page with all the results you can compare like for like or order them ranked by dimensions etc. You then invite others, like your partner, to comment and rank the findings or they can add further to the project page.
An interesting side-note is that men don’t often “get” Skimbit because they tend to create lists and email them off to others. Women appear to respond better to the Skimbit project page because because they like the range of options to order the list for others, perhaps their girlfirneds, to contribute feedback, like “thumbs up, thumbs”, star ratings etc. The results are presented graphically.
The third and final step is a project whiteboard, a checklist, map and a meebo IM window. That’s the simple process. Skimbit also has a white-label version of this system for publishers/retailers, but Skimbit gets to retain all of the data produced by a white label partner.
This is where it gets interesting. Because although project pages by users can be private, Skimbit encourages users to make them public, so other people can leverage the long tail research, say for baby prams or shoes, mobiles you name it. So Skimbit is getting higher on these long-tail searches on Google, because the content is user-generated editorial, not spammy product comparison pages.
Skimbit’s revenue model is the same as a price comparison sites, based on affiliate commissions. If someone skims content from a site which is a merchant of Skimbit’s, that link is turned into a commission earning affiliate link. The key thing here is that this doesn’t disrupt the user experience, as it’s invisible. So the potential from earning a lot of revenue is higher because Skimbit is not pushing products at Users, the users are bringing their own crowd-sourcing around the products.
Users are encouraged to use Skimbit for things that don’t earn Skimbit revenues, which adds to the data and increases its status as an engine driven by users, not price comparison deals. It’s a sort of user generated comparison tool in the cloud which retains all user’s research. Think Mahalo for product comparison.