Over the past few years, we’ve spent a lot of time advising Brands and Agencies on the challenges and risks associated with Programmatic buying (which for this post will encompass exchange traded media, RTB, etc.). While the idea of machine-based buying is exciting, it’s not without significant challenges and risks. Having analyzed dozens of programmatic campaigns, we’ve found that a blind leap into Programmatic is almost always a costly endeavor. The thesis for taking a smart approach to programmatic buying is summarized below:
- While the promise of self-optimizing buying is intriguing, it doesn’t replace the need for objective, rational analysis.
- Programmatic optimization is typically based on a broken model. The continued reliance on clicks, post-click and post-view metrics may do more harm than good.
- Algorithmic attribution is critical for measuring and optimizing media. Fractional, statistical analysis is needed for accurate and impactful cross-channel, full-funnel insights.
- As brands shift more of their budgets to programmatic, the need for objective, attribution-based insights will become even more critical
I recently put documented some of the key lessons learned to produce the embedded Presentation: “Investing Confidently in Programmatic“. I thought about calling it “How to Avoid Wasting Half of Your Media Budget” but opted for the more positive spin. Either would be sufficiently accurate.
In it, I address some of the risks and challenges of Programmatic buying, along with recommendations for ensuring a successful investment in this rapidly changing arena. Also included is a SWOT analysis to frame the strengths, weaknesses, opportunities and threats that advertisers must deal with to be successful in this new area of machine-based buying.