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Working at Yieldbot

We’re adding more developers to our team and pushing things to the next level. If you like seriously interesting and challenging work in the areas we’re looking for help in, you should be talking to us. You’ll have a single-digit employee number, so you’ll be getting in early and powering us on our way to fulfilling the huge potential we’re sitting on.

What can you expect if you decide to jump in and join us on our mission to make the web experience more relevant? For one thing, no shortage of interesting hard problems to solve, and the latest tools to do it with.

A Great Environment

For our devleopment environment we each have an AWS sandbox that deploys the same code as production, so everyday work is production devops training too, with a Mac for your local dev environment. You’ll have Campfire group chat up all day, and be in the middle of all the important conversations around what we need to do and how we need to do it, from the CEO on down.

The language and tools you use most during the day will depend on what part of the platform you’re focusing on.

A Distributed Realtime Platform

A large part of the core platform is in Python. All of the code around scheduling of tasks and managment of the platform are found here, as well as the key ad serving logic and realtime event processing. You’ll be making use of MongoDB, redis, and ElephantDB. You’ll be solving problems on running the platform distributed across several data centers worldwide. You’ll likely be doing some devops stuff here too, and loving the ease with which Chef lets you get that done.

Bleeding Edge Analytics

If you’re working on our analytics then you are loving the use of Cascalog (a Clojure DSL that runs over the Cascading API on Hadoop). The power-to-lines-of-code ratio here is ridiculous. More than that, you’ll be writing realtime analytics in Storm. That’s not cutting edge, it’s definitely bleeding edge.

Focus on UX

To work on the UI you’re pushing the limits on the latest Javascript UI tools like D3.js and Spine.js. Have you thought about how clean client-side MVC should be done? Spine is it. We’re serious about quality of UX here. If you’re serious about it too, this is where you should be.

An Awesome Team

The team you’ll be joining has been there before. We’ve founded and built successful products, platforms, and companies. We know our industry and what it takes to be successful. And we’re doing it.

The most important thing that keeps us developers here at Yieldbot energized is that we’re building something people want, that’s been clear from the beginning. Our mission to make the web experience more relevant resonates with users, publishers, and advertisers.

If you’re up for the challenge contact us at Check out We have some seriously challenging work you can get started on right away.



How Yieldbot Defines and Harvests Publisher Intent

The first two questions we usually get asked by publishers are:

1) What do you mean by “intent”?

2) How do you capture it?

So I thought it was time to blog in a little more detail about what we do on the publisher side. 

The following is what we include in our Yieldbot for Publishers User Guide.

Yieldbot for Publishers uses the word “intent” quite a bit in our User Interface. Webster’s dictionary describes intent as a “purpose” and a “state of mind with which an act is done.” Behavioral researchers have also said intent is the answer to “why.” Much like the user queries Search Engines use to understand intent before serving a page, Yieldbot extracts words and phrases to represent the visitor intent of every page view served on your site.

Since Yieldbot’s proxies for visit intent are keywords and phrases the next logical question is how we derive them. 

Is Yieldbot a contextual technology? No. Is Yieldbot a semantic technology? No. Does Yieldbot use third-party intender cookies? Absolutely not!

Yieldbot is built on the collection, analytics, mining and organization of massively parallel referrer data and massively serialized session clickstream data. Our technology parses out the keywords from referring URLs – and after a decade of SEO almost every URL is keyword rich - and then diagnoses intent by crunching the data around the three dimensions of every page-view on the site. 1) What page a visitor came from 2) what page a visitor is about to view and 3) what happens when it is viewed. 

Those first two dimensions are great pieces of data but it is coupling them with the third dimension that truly makes Yieldbot special. 

We give our keyword data values derived from on-page visitor actions and provide the data to Publishers as an entirely new set of analytics that allow them to see their audience and pages in a new way – the keyword level. Additionally, our Yieldbot for Advertisers platform (launching this quarter) makes these intent analytics actionable by using these values for realtime ad match decisioning and optimization.

For example: Does the same intent bounce from one page and not another? Does the intent drive two pages deeper? Does the intent change when it hits a certain page or session depth? How does it change? These are things Yieldbot works to understand because if relevance were only about words, contextual and semantic technology would be enough. Words are not enough. Actions always speak louder.

All of this is automated and all of this is all done on a publisher-by-publisher level because each publisher has unique content and a unique audience. The result is what we call an Intent Graph™ for the site with visitor intent segmented across multiple dimensions of data like bounce rate, pages per visit, return visit rate, geo or temporal.

Here’s an example of analytics on two different intent segments from two different publishers:



For every (and we mean every) visitor intent and URL we provide data and analytics on the words we see co-occurring with primary intent as well as the pages that intent is arriving at (and the analytics of what happens once it gets there). We also provide performance data on those words and pages.

Yieldbot’s analytics for intent are predictive. This means that the longer Yieldbot is the site the smarter it becomes - both about the intent definitions and how those definitions will manifest into media consumption. And soon all the predictive analytics for the intent definitions will be updated in realtime. This is important because web sites are dynamic “living” entities - always publishing new content, getting new visitors and receiving traffic from new sources. Not to mention people’s interests and intent are always changing. 

I hope this post has served a good primer on Yieldbot for Publishers and maybe even gotten you interested in seeing it in action on your site. One of the best parts of what we do is seeing people’s faces when they first see the product. If you are a publisher and would like a demonstration please email info <at>