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Thinking Big About Revenue Management and Optimizing All Sources of Income
- 1. Thinking Big About Revenue Management September 15, 2011
- 2. The Problem: Two Systems for Selling Online Ads Ad Server Sold direct Sales Ad Network #1 Sold indirectly Ad Network #2 Ad Network #3 Etc.
- 3. The Problem: Two Systems for Selling Online Ads Yield optimizers or Ad exchanges Ad Server Sold direct Sales Sold indirectly
- 4. Focus on All Your Revenue Publisher Ad Revenue Example Spot Market Sales Advertisers buy inventory on spot market Sold Indirectly
- 5. Focus on All Your Revenue Publisher Ad Revenue Example Exclusive Campaigns Home Page Sponsorship Guaranteed Campaigns Sold Directly Non-Guaranteed Campaigns Spot Market Sales Advertisers buy inventory on spot market Sold Indirectly
- 6. Focus on All Your Revenue Publisher Ad Revenue Example Exclusive Campaigns Home Page Sponsorship Guaranteed Campaigns Ad campaign with fixed dates Sold Directly Non-Guaranteed Campaigns Spot Market Sales Advertisers buy inventory on spot market Sold Indirectly
- 7. Focus on All Your Revenue Publisher Ad Revenue Example Exclusive Campaigns Home Page Sponsorship Guaranteed Campaigns Ad campaign with fixed dates Sold Directly Optimize this! Non-Guaranteed Campaigns Performance based campaigns run on ‘space available’ basis Spot Market Sales Advertisers buy inventory on spot market Sold Indirectly
- 9. Revenue Serving One holistic platform to optimize all sources of revenue in real time
- 11. Access new demand (i.e. DSPs)
- 12. More Control
- 13. Unified reporting & no discrepancies
- 14. More revenue!Ad Server Inventory Ad Exchange Revenue
- 15. Two Ways to Play: Ad Server + Exchange Buyers Ad Server Guaranteed Private Trading Select Inventory Open Ad Exchange All other Inventory
- 16. Two Ways to Play: Exchange Only Buyers Open Ad Exchange Private Trading Select Inventory All other Inventory
- 18. Growing at 300%
Editor's Notes
- Despite growing demand for online advertising, publishers are struggling more than ever to grow their ad revenue efficiently. As buyers get smarter, publishers often find themselves at a disadvantage in the ‘arms race’ developing over data, targeting, and inventory optimization.
- It used to be a lot simpler. In the ‘old days’ (like 1999) publishers would sell as much as they could with their sales force, then sell the rest through intermediaries. They had direct (“I sell it”) and indirect (“I sell through other firms”) sales strategies, often managed by different people in their organization. For indirect sales, originally rep firms, and later ad networks, would sell that publisher’s inventory. Soon a thing called the ‘daisy chain’ developed. Publishers would stack a series of ad networks into a hierarchy. The ad network yielding the highest effective CPM got the first set of impressions; then the publisher would pass the next set of impressions to the next network, and so on. It was a big operational headache—a completely manual process where yields were reviewed weekly by a dedicated team to adjust allocations.To solve this problem, a bunch of yield optimizers, often called supply side platforms,said that they could manage the daisy chain for publishers. These supply side platforms said they could do two things: Take the pain awayOptimize the daisy chain and make more moneyWhich kind of happened. But it only focused on one part of a publishers total revenue portfolio.
- It used to be a lot simpler. In the ‘old days’ (like 1999) publishers would sell as much as they could with their sales force, then sell the rest through intermediaries. They had direct (“I sell it”) and indirect (“I sell through other firms”) sales strategies, often managed by different people in their organization. For indirect sales, originally rep firms, and later ad networks, would sell that publisher’s inventory. Soon a thing called the ‘daisy chain’ developed. Publishers would stack a series of ad networks into a hierarchy. The ad network yielding the highest effective CPM got the first set of impressions; then the publisher would pass the next set of impressions to the next network, and so on. It was a big operational headache—a completely manual process where yields were reviewed weekly by a dedicated team to adjust allocations.To solve this problem, a bunch of yield optimizers, often called supply side platforms,said that they could manage the daisy chain for publishers. These supply side platforms said they could do two things: Take the pain awayOptimize the daisy chain and make more moneyWhich kind of happened. But it only focused on one part of a publishers total revenue portfolio.
- In the hierarchy of ad inventory, first there’s exclusive. Nobody else gets it. It’s a commitment a publisher makes to show only one advertiser during a set time period. Second, there are campaigns sold directly by the publisher’s sales force on a guaranteed basis. The guarantees are based either on volume (set # of impressions per month), or by share-of-voice (% of total inventory for the month). Third there are non-guarenteed deals sold directly by a publisher’s sales force. Often these are performance deals (ie. that may yield a $1.20 ‘effective’ CPM for a publisher), but are served only on a ‘space available’ basis.But what about the bigger picture? I call it the ‘uber’ daisy chain: all four types of ad inventory including exclusive, guaranteed, non-guaranteed that’s sold directly, and non-guaranteed that is sold indirectly. How do you optimize all of that? Where should a publisher send the next impression they serve to generate the most revenue possible while keeping their best customers happy? Publishers need a system that looks holistically at all their ad inventory to make sure they make the right decision—and then captures all the information in one dashboard. Otherwise they have to look at different sets of data and sew it all together to understand the whole picture.
- In the hierarchy of ad inventory, first there’s exclusive. Nobody else gets it. It’s a commitment a publisher makes to show only one advertiser during a set time period. Second, there are campaigns sold directly by the publisher’s sales force on a guaranteed basis. The guarantees are based either on volume (set # of impressions per month), or by share-of-voice (% of total inventory for the month). Third there are non-guarenteed deals sold directly by a publisher’s sales force. Often these are performance deals (ie. that may yield a $1.20 ‘effective’ CPM for a publisher), but are served only on a ‘space available’ basis.But what about the bigger picture? I call it the ‘uber’ daisy chain: all four types of ad inventory including exclusive, guaranteed, non-guaranteed that’s sold directly, and non-guaranteed that is sold indirectly. How do you optimize all of that? Where should a publisher send the next impression they serve to generate the most revenue possible while keeping their best customers happy? Publishers need a system that looks holistically at all their ad inventory to make sure they make the right decision—and then captures all the information in one dashboard. Otherwise they have to look at different sets of data and sew it all together to understand the whole picture.
- In the hierarchy of ad inventory, first there’s exclusive. Nobody else gets it. It’s a commitment a publisher makes to show only one advertiser during a set time period. Second, there are campaigns sold directly by the publisher’s sales force on a guaranteed basis. The guarantees are based either on volume (set # of impressions per month), or by share-of-voice (% of total inventory for the month). Third there are non-guarenteed deals sold directly by a publisher’s sales force. Often these are performance deals (ie. that may yield a $1.20 ‘effective’ CPM for a publisher), but are served only on a ‘space available’ basis.But what about the bigger picture? I call it the ‘uber’ daisy chain: all four types of ad inventory including exclusive, guaranteed, non-guaranteed that’s sold directly, and non-guaranteed that is sold indirectly. How do you optimize all of that? Where should a publisher send the next impression they serve to generate the most revenue possible while keeping their best customers happy? Publishers need a system that looks holistically at all their ad inventory to make sure they make the right decision—and then captures all the information in one dashboard. Otherwise they have to look at different sets of data and sew it all together to understand the whole picture.
- In the hierarchy of ad inventory, first there’s exclusive. Nobody else gets it. It’s a commitment a publisher makes to show only one advertiser during a set time period. Second, there are campaigns sold directly by the publisher’s sales force on a guaranteed basis. The guarantees are based either on volume (set # of impressions per month), or by share-of-voice (% of total inventory for the month). Third there are non-guarenteed deals sold directly by a publisher’s sales force. Often these are performance deals (ie. that may yield a $1.20 ‘effective’ CPM for a publisher), but are served only on a ‘space available’ basis.But what about the bigger picture? I call it the ‘uber’ daisy chain: all four types of ad inventory including exclusive, guaranteed, non-guaranteed that’s sold directly, and non-guaranteed that is sold indirectly. How do you optimize all of that? Where should a publisher send the next impression they serve to generate the most revenue possible while keeping their best customers happy? Publishers need a system that looks holistically at all their ad inventory to make sure they make the right decision—and then captures all the information in one dashboard. Otherwise they have to look at different sets of data and sew it all together to understand the whole picture.
- That’s why at OpenX we’ve worked hard to transform ad serving into Revenue Serving.Publishers need a system that looks holistically at all their ad inventory to make sure they make the right decision—and then captures all the information in one dashboard. Otherwise they have to look at different sets of data and sew it all together to understand the whole picture.
- With OpenX, publishers can reserve their select inventory and establish tight controls over how it’s sold…that’s why we call it ‘private trading.” Only a short list of buyers—like certain RTB agency trading desks—can access this inventory. And the terms (like pricing, data access, and inventory type) are strictly controlled. This way the publisher avoids channel conflict when selling their most valuable inventory indirectly. Yet they get the benefits of the real-time auction model that drives CPMs up. Plus it automates the sales process.The rest of their ad inventory can be sold through the ‘open’ ad exchange, which has a wider list of buyersOne complete solution for monetizing all classes of ad inventory.
- Of course, some publishers already have an ad server, and aren’t ready to switch. Good news is that they can still take advantage of our real-time exchange platform for their indirect revenue
- We spent the last two years building the most advanced ad server that embodies these ideas. Take a look.