Funded Widgets: Minekey

As reported by Mashable and StartupSquad, content discovery service Minekey has raised a $3M round of funding from NEA IndoUS Ventures, a $189M fund targeting India based businesses (Minekey has offices in both India and Sunnyvale).

The heart of Minekey’s service is its JavaScript content discovery widget.  The pitch goes something like this: adding a Minekey widget to your blog can deliver relevant, customized content recommendations for each of your blog readers, in the process, increasing your blogs pageviews, usefulness, and profitability.

Analytics is a crucial part of this service, as it drives the recommendation output.  Every time somebody hits a page with the Minekey widget installed, their browsing habits are captured, alerting Minekey to the sort of content that interests that particular user.  Obviously, the quality and breadth of Minekey’s recommendations will depend in large part on how many pages contain their widget.  Hence the funding.

The universe of recommended sites is determined by the blogger.   During the widget configuration process, each blogger can define the feeds of the blogs that are included in the widget’s output.

I’ve added a Minekey widget to my left sidebar.  I’ve included some of my favorite widget sites to the output. Until those sites add the Minekey widget however, I'm not exactly sure how those recommendations will be generated.

The world of content discovery is a crowded and exciting space right now.  As the amount of content on the Web explodes – fueled by self publishing platforms of all flavors – finding content that interests you becomes increasingly challenging.  The prolonged and astronomical success of Google AdSense also provides a nice example of the upside of solving the content discovery riddle.

Two Silicon Valley sites that are making noise in this space – and that also rely on analytics as the input - are Loomia and the fabulously funded Aggregate Knowledge. 

French company Criteo has a similar offering with their Autoroll widget (review), but unlike Minekey, Criteo doesn’t let the blogger define the universe of output sites.  Spotplex (review) is focused on providing recommendations within the same domain.

Another interesting company in this space is Media River and their Click Surge product line – a company that grew out of a Northwestern research project.

And analytics is not the only way to drive cross site recommendations.  Israeli start-up Spotback collects content ratings from the user, and uses those ratings to deliver other content that the user might enjoy.

I’m also aware of at least one stealth start-up attacking this space.

In the coming days and weeks, I’m going to try and take a more detailed look at some of the other players taking on the dual challenges of content parsing and discovery.

Comments

[Rajiv Doshi]

I work for Minekey so thank you for posting about Minekey and for also using our widget. The way our recommendation works, we don't need those other web sites to place our widget to analyze their content. Once those site's feeds are entered into your widget we can provide recommendations to your readers immediately.

[lawrence]

Thanks Rajiv. Can you provide us with any more information about how your engine can rank / correlate specific posts within a feed based solely on that feed being added to a user's widget? For example, if I add some obsure blog's feed to my widget, how will your engine know which posts to recommend to readers?

[Rajiv Doshi]

Hi Lawerence, the Minekey engine crawls each RSS feed as they are added to your widget.

The engine then analyzes the content that the visitor is currently viewing against all that content from the RSS feeds to match recommendations to your visitors based on each specific visitor's behavior and the collective wisdom of the crowds.

Does that help clarify? If you are looking for a deeper explanation of the technology, you can also find it here:
http://www.minekey.com/about/tech

[lawrence]

That's cool Rajiv. So this isn't just analytics. It's analytics plus content parsing / analysis.

[John]

Thank you very much for sharing your thoughts. It is always great pleasure to read your posts.

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