Working for Lijit, I spend a lot of time thinking about the collection and aggregation of data. The presentation of that data, the ability to sift through all that data, and the utility of that data.

Funny thing is that I am not a programmer or developer. Mostly, I spend my day thinking about how Lijit the product, can interact with other products to mutually improve both products.

Here is an example:

Tumblr. Awesome product. I have a tumblog at micahbaldwin.com, and a follow 30 or so other tumblogs. The minimalist design, short form post style and ease of use makes its a viable communication platform and will open up “blogging” to folks that dont want to build and maintain a full blog.

Because of the user experience, the content on people’s tumblogs grows quickly, sometimes I may post 4-5 times a day, I see others post at a much more rapid pace. Unless I stay on top of the data, there are often many good posts that I miss.

What’s missing? Some sort of search functionality. Not just the ability to search through posts, but to help me discover content from other tumblogs that would interest me, and I could grow my follow list. Reblogging (the ability to re-post someone else’s post) certainly allows the best of the best to rise to the top, but its very superficial and manual.

Enter Lijit. We offer much of that functionality, and the ability to better integrate in the Tumblr platform would certainly improve the results we provide.

Beyond interconnected search, the added benefit is that Lijit can use following and reblogging to help “rank” posts and people based on trust, which could aid in content discovery and relationship recommendations.

It is pretty clear that a relationship between Lijit and Tumblr would be mutual beneficial and provide additional functionality that would not take away from the core value of either product, but would be embraced and useful to users of either product.

Which takes us to Twitter.

After all, if Tumblr and Lijit would make a good match, wouldnt Twitter as well? It shares much of the simple user interface and ease of use of Tumblr. People use it…a…lot.

And while there are services that exist search through tweets and users, there is nothing like the interconnected search capability of Lijit, where I can search through my tweets and the tweets of my network simultaneously, as well as all the content in my and my networks combined social graph.

But tweets are different than Tumblr and blog posts. They are ephemeral, usually in context, and more and more part of a longer public conversation. Rarely, does a tweet stand on its own.

While there is intersections that Lijit and Twitter can have around the collecting, indexing and presentation of data, its certainly not as robust as other relationships.

Would I do a deal with Twitter? Absolutely. There is often ways to determine benefit to both parties without needing to implement a complete solution.

Which leads to social aggregation products. I have spoken to many of them about the value to Lijit to collect more of the user’s social graph, and the need for an interconnected search functionality to exist within their application. The biggest difficulty facing social aggregation products is the sheer amount of collected data and the rate at which that data changes.

At the end of the day, the best business development deals are the ones where both products are improved by the relationship, and therefore both companies are motivated to see the relationship grow and flourish.

SIDE THOUGHT:

After becoming quite the consumer of Tumblr, Twitter and several social aggregation products, I have also come to another belief: Tweets should stay in TwitterLand.

Because context is so important to understanding the follow of Twitter, it works best as SMS, IM in a Twitter client, or in a browser window. When mixed with Tumblr or a social aggregation product, Twitter becomes noise.

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