Shortening the Cycle Time for Data Driven Insights


 

In a recent Q & A in AdAge, Scott Burke, a VP of Engineering at Yahoo, shared some great observations about the use and valuation of data by marketers today. Two points, in particular, resonated with me, as they reinforce key aspects of our mission here at DataXu:

1. Shortening the cycle time for data-driven insights will benefit everyone involved in online advertising.

2. “It’s not about how much data you have, it’s what you do with it.”

In the article, Scott mentions how Yahoo strives to accelerate their decisionmaking internally, and do so in an “iterative loop” of hypothesize, test, learn, repeat—a paradigm that describes our platform’s learning system quite well. Scott also echoes our philosophy that the ability to derive insights from data more quickly will make all parties involved in advertising more effective. We built our platform to analyze enormous amounts of data with unprecedented speed, in order to make highly informed decisions about the barrage of ad impression opportunities available at any given second on the Internet. We also recognized the value of learning from each of those decisions, to continually improve the system’s decision making data models and algorithms going forward. This dynamic, closed loop learning model – especially when combined with real-time bidding – gives our clients a distinct advantage over more static approaches to buying media online. We extend the continual learning outward from our system, too. Our clients gain timely, granular insights from their campaigns that they can apply to better inform a range of marketing efforts.

The ability to leverage data in this dynamic way can also extract more value from the data itself, as the quote from Scott in my second point above illustrates. It can be challenging for marketers to anticipate what type of data will have the most impact on a campaign’s success, but when applied within an intelligent system, you can pick out the signals that matter for the specific campaign. More data isn’t always better. But more advanced decisioning can make limited data do big things or elicit the select, valuable gems among larger sets of data – both tasks that are nearly impossible for an individual to do without the benefit of some powerful technology. (For more on my thoughts about the role of data in display campaigns, please see a recent column I wrote for ClickZ.)

It’s great to hear validation in the marketplace that what we offer our clients is relevant and meaningful. The amount of data marketers have at their disposal is growing by leaps and bounds, so our goal is to continue to develop the best system for using that data to improve media efficiency and lower customer acquisition costs.