Ad-driven media organizations are under extreme pressure to increase revenues and maximize the value of their airtime inventory to enable new business opportunities. Now more than ever, it’s important to provide measurable methods that allow our customers to be more intelligent with their multiple types of inventory. This white paper provides some inside-industry information on the evolution of ad management, the history of linear vs. nonlinear delivery methods, and why inventory optimization is the next logical step towards increasing ad revenue. Put your ad caps on. We guarantee you’ll learn at least one new thing in here.
The Bridge Between Linear & Nonlinear
First, a linear/nonlinear primer: In traditional linear viewing, content and advertising is delivered real-time to a region with no option for the viewer to skip ads, receive targeted ads, or choose to not watch them (without leaving the linear channel). With nonlinear viewing, content and advertising can be delivered in either real-time or time-shifted methods (OTT, DVR, etc.) and can allow the viewer to skip the ad, click through to view it, and receive highly targeted ads specific to the viewer’s preferences and habits.
Traditionally, linear TV sells ad space using a forecasting system called, “Gross Rating Point” (GRP), which is a ratings-based formula that projects what kind of an audience a particular piece of content (such as a TV show or sporting event) will draw. Many of the new nonlinear advertising business models use a different system, “Cost Per 1,000 Impressions” (CPM), which is an impressions-based method that measures how many users were actually exposed to the ad. As traditional media companies expand their services to nonlinear viewing, a new “currency” problem emerges: how can a media seller offer an omniplatform campaign with radically different currency models like GRP and CPM? This lack of a standard currency makes it incredibly challenging to sell and manage inventory across all media platforms. Advertisers, like media sellers, want to unify their campaigns and objectives, but without significant reconciliation for these currencies, it is near impossible to make full use of all available seller inventory. In effect, millions of dollars—and billions of impressions—get flushed away every year as a result of not optimizing inventory.
Before the ad industry embraced automated methods of buying and selling, the idea of automation (using software to buy, sell, manage, and optimize ad placements and opportunities) was just as foreign to advertising managers as personal computers were to the average household in the ‘80s. And just like personal computers, automation is something no one can imagine living without these days.
The next step in the industry’s evolution is optimization: the ability to leverage sophisticated algorithms and machine learning to determine the optimal placement of an ad based on campaign objectives. By using optimization automation, a media seller can more accurately deliver the right audience for the right ad at the right time. Optimization tools leverage an efficiency model in which the algorithm looks at past performance of programming, placements, and consumer trends to determine where the most productive yield will result from a placement. In essence, optimization uses a computer to compare and contrast business rules that the media seller sets up to ensure an ad runs in the avail that is best positioned to deliver against campaign objectives.
Consider a scenario where ad space is traded against a low-cost, general demographic of adults 25-64 years old versus the higher cost, targeted demographic of left-handed golfers. Without an optimization engine, the media seller may consider the general adults’ category as more financially advantageous, and choose to run an ad appropriate to the wider demographic. But a good optimization engine might determine that this particular ad avail would be better served by running a targeted ad to the left-handed golfers, while saving the more general demographic for another time.
Accordingly, a good optimization engine should:
- Review all inventory and manage against campaign objectives automatically—not just against availability and/or price;
- Accurately analyze real-time and historical data to ensure the right inventory opportunity is used against the campaign objectives;
- Remove the guess-work of an ad’s audience, reach/ frequency capabilities through data-driven forecasting;
- Provide accurate metrics on demographics using highly advanced CPM statistics;
- Find every second of underutilized inventory in order to squeeze every ounce of revenue from it;
- Further automate the process of scheduling commercial and promotional content without adding additional resources or back-office infrastructure.
Most importantly, a good optimization engine should process both currencies by converting GRP / spot objectives to audience / CPM metrics. This enables traditional linear programming to behave like nonlinear— and vice versa; one that is cross-platform functional and capable of optimizing ad inventory for multiple methods of media delivery.
OldTown………………………………Traditional broadcaster sellers
NewTown…………………………….Multiplatform video service providers
Utopia…………………………………..Successful audience delivery of an ad campaign
The Ship……………………………….Video content (TV show, sports event, etc.)
Passengers…………………………..Target market consumers
The Water/Currents……………Traditional linear broadcast delivery method
Wizards……………………………… Ad sales representatives
By air, by space, over the water……..New nonlinear delivery (Packaging, multi-device, OTT, VoD)
OldTown’s method of valuation……..GRP (Gross Rating Point)
NewTown’s method valuation………..CPM (Cost per 1,000 ad impressions)
Test Group………………………………………….A traditional ratings mechanism, like Nielson
OldTown’s extra space algorithm…..Ad inventory optimization
The Ad Management Tower of Babel... Can’t We All Just Get an Ecosystem?
Video delivery people say tomato; ad management people say orange. Why is there such a disconnect in terminology? Shouldn’t we all just standardize on the same language?
Not necessarily. Language is contextual. The language of delivery focuses on how content is delivered; the language of ad management focuses on how content is monetized. Telling an ad person that her linear TV includes digital delivery might start a fight; telling a delivery person that his front end is really the back end and, well, maybe something more than a fight.
Now that delivery and ad management systems are joining together to create next-generation, cross-platform media ecosystems, knowing some Ad Speak might help.
We Challenge You to an xG GamePlan™
If you’re looking for the only cloud-based application on the market today that uses unparalleled, battletested inventory optimization tools, look no further. xG GamePlan™ allows the highest level of inventory optimization for the least amount of back-office traffic and sales solution replacement. The only downside of it is… wait, there is no downside. You have literally nothing to lose and millions to gain.
Interested in learning more?
Read Lessons Learned From The Frontlines of Global Content Monetization to learn why audience-based buying is gaining traction in key global markets and why North America may be making the shift as well.