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The data is in: time spent with video each day is flattening—which means overall consumption is flattening as well. Tighter numbers mean now is the time to pay special attention to yield, making the most of revenue per spot. Since every media company is unique—with its own programming, ad inventory, and data—the business logic that predicts and determines the right pricing must be unique as well.
Luckily, new technology—like AI and advanced data science—allows media companies to maximize yield intelligently for their unique circumstances. AI is becoming an essential tool for navigating the complexity in a rapidly-evolving video advertising market. As more viewing occurs on demand and across an increasing number of devices, a growing amount of data must be processed for media companies to stay ahead. AI makes this not only possible but actionable—helping media companies forecast, allocate and optimize inventory within campaigns and across their portfolios at large, increasing yield and improving the bottom line.
Our recent Furious whitepaper explores the science behind this, and more, in detail. For now, here are 7 key rules that forward-looking media companies should follow to harness the power of AI to improve yield:
1. Audit systems providers, to be sure you own your data
Ensure you have the right to use—and ideally own—your data. If not, revisit agreements and vendor relationships. When data is yours, you can clean it, manipulate it, keep it in the format you want, verify it (otherwise you’re leaving it up to trust!) and combine data from different places (like audience data and revenue data) to form insights. True partners want you to have access to and ownership of your first-party data.
2. Get all your data in one place
Not every media company needs to undergo a large-scale data migration project in order to get actionable insights to improve yield. But data related to your core business—in particular, sales, delivery and measurement data—must be in one place to provide mission-critical reporting, analysis and planning. Identify an outsourced partner or an in-house department to aid in gathering all your data in one location for mining.
3. Gain different perspectives from cross-trained partners
People with varied experience can bring a different perspective on how to solving yield-related math problems, which aren’t exclusive to the media industry. For example, airline ticketing companies have learned how to forecast prices to maximize how much travelers are willing to pay as the travel date gets closer. A ticket might be cheap several months out, go up in price six weeks in advance, and then be reduced drastically a few days out. An advertiser’s willingness to pay often follows a similar trajectory.
While cross-training is important, it’s key that your partners are first and foremost experts in the media business. Although algorithms might be similar across industries, those required to forecast and optimize for media require domain expertise and specificity.
4. Maintain control of your business
Algorithms are great, but they need human oversight to give them a “sense” test. Make sure you have the ability to override the output of all algorithms and systems, to prevent black boxes or the machines from taking over. Take part in shaping the business algorithms that power any yield management solution, whether built internally or with a vendor.
5. Don’t underestimate investment in talent
This goes for both building a yield management system in-house or with a partner. After all, you’ll still need people to interface with a partner, if you go that route. Or, consider the opportunity cost of revenue of the time spent building a successful TV advertising yield optimization function internally.
6. Keep innovating
Continue to seek new data inputs. Demand higher levels of accuracy and yield from your teams and partners, as well as greater automation, which can increase profitability over time.
7. Get creative with partner compensation
Ask your partners if they’d be willing to be compensated according to the additional yield or efficiency they deliver. True partnership is based on shared risk, so it never hurts to ask. Startup Rocketrip does just this by helping companies save on travel costs by incentivizing employees to spend less. They split cost savings with employees, which motivates them to skip the luxury hotel and choose a more modest option—creating a win-win for companies and employees alike.
To learn more, download the Furious whitepaper, “7 Rules for Superior Video Yield: AI and the Future of TV/Video Planning and Optimization.”