Comments on: Gaining Clarity in the Spot Buy

By: RC

RC — Fri, 21 May 2010 01:34:58 +0000

Zach, your sentiment is understood but this article was purposely not intended to showcase MediaMath or any other DSP. It is intended for anyone trying to buy ads on remnant and do so without getting inundated with all the variables. Like financial trading, there are professionals and the everyday home trader. The everyday home trader uses e-trade to execute (with a ton of information to keep them busy for decades). They would be crushed by a pro due to execution times, better information, faster feeds, etc. We, as DSP's, have all this. We (at MediaMath) process terabytes of information across double digit exchanges to buy as effectively as possible. We've proven this for over 3 years, but I have an arsenal of machines and an amazing team of industry vets who know how to pull this off. Reality is, if you really want to buy effectively, use a DSP across every exchange possible a let the machines do the work, then get some aggregrate reports that show a nice picture. That would not have been a very interesting article though. Furthermore (although I did find your tweet funny), a shotgun approach to buying should really be thought of as a "control group". That means understanding the market, understanding the basics of the campaign, what the client wants, and what you know historically has been successful. Just don't be too stringent because tomorrow's another day. RMX calls it "learn", we call it "watermarking". I, of all people, highly recommend using DPS's as your primary execution arm and data collector when running campaigns, but not everyone is in that boat ... thus a simple article on what data is out there and a request to think a little before you start bidding.

By: Tim

Tim — Thu, 20 May 2010 23:57:04 +0000

Zach,

That's Roland's point. Part of the value DSPs such as MediaMath and Invite bring to the table are solving for media buying logistics which have been historically nightmarish. I thought that was obvious.

Good article. I see the analogy of shotgun -> rifle. It's about tightening the aperture as you learn more. Right?

By: Zach Coelius

Zach Coelius — Thu, 20 May 2010 22:12:28 +0000

Roland, that is exactly the antiquated inefficiency that we are trying to address. What would the point be of our companies if we bought media like the agencies with a spreadsheet and a prayer?

By: RC

RC — Thu, 20 May 2010 20:41:00 +0000

Ken, I agree that all data has value. However, most (not all) companies who actually manage campaigns cannot do this. If you are an agency that does not have the luxury of big data machines, quant guys and your own platform to trade on, you are most likely looking at excel spread sheets when making price changes. If this is the case (and I would bet it is for more than 90% of our industry), limiting the data to manageable pieces is a feasible solution.

By: Ken Rona

Ken Rona — Thu, 20 May 2010 16:13:41 +0000

Nice article Roland. Agree that we can learn a lot about audiences in the process.

But I respectfully disagree about the size and scope of data. Big? yes. Hard to do? yes. Even harder to well? oh yeah. But we eat hard for breakfast.

All data has value and we spent a lot of effort on learning how to use it for targeting and bidding. Data is the new currency and we don't leave a single penny on the floor.

By: Albert Azout

Albert Azout — Thu, 20 May 2010 15:14:38 +0000

Great post Roland. What do you think data providers will look like in the future?

By: Daniel Haran

Daniel Haran — Wed, 19 May 2010 21:03:47 +0000

"Don’t expect to take all of this data and make any sense of it, its just too big"

While most stats packages will make your machine cry when faced with too much data, we can distribute data and computation over many machines to make sense of it. Standard stats won't work very well; only machine learning (AI) approaches are likely to yield useful and actionable insight.

The harder challenge for us is dealing with data vendors and ad buyers that still want to buy inventory with old fashioned demographic categories or arbitrarily delineated intender segments.