DIGITAL STRATEGY IN THE AGE OF ARTIFICIAL INTELLIGENCE HOW TO TAKE ADVANTAGE OF AI IN ADVERTISING 15+ 2 3 4500+ EXECUTIVE SUMMARY:Artificial intelligence (AI) has changed what we can achieve in media buying and planning, how to achieve it, and the metrics used to understand success. This paper lays out what AI is, strategies to apply it to advertising, and the best methods for gaining expertise, evaluating partners, and working with them to leverage the opportunities afforded by AI to achieve the best possible business outcomes.AI, EXPLAINED At its core, artificial intelligence processes specific inputs then delivers specific outputs. Asked the right questions and given the right instructions, its algorithms will provide solutions and suggest actions that produce desired results. The problems addressed by AI are sometimes ones that people could solve without intervention, on a smaller scale. AI could, for example, match one facial image to another, predict next week's sales, or say whether someone's credit history shows they're likely to pay off a loan. By breaking the problem into component parts, each relevant input can be weighted and a solution derived. Recognizing a face, for example, is a combination of evaluating the curve of a jaw, the angles of a nose, the color of someone's eyes, and so on, with some factors being more pertinent to the solution than others. AI is like a spreadsheet on steroids, says Sara Robertson, VP of Product Engineering for Xaxis, and an expert in artificial intelligence. AI usually works in concert with machine learning so that algorithms get increasingly better at increasingly complex tasks like pattern recognition and predictive analysis. Machine learning takes the results produced from a round of instructions, compares them to the predicted outcomes, evaluates, then sends information back on how to adjust and optimize. Further enhancement comes from processes such as neural networks -- connected computing nodes working together to increase processingARTIFICIAL INTELLIGENCE: IMAGINATION AND REALITY In our imaginations, artificial intelligence often comes in blockbuster proportions: the computer's takeover in 2001, A Space Odyssey, battles for humanity's fate with multi-limbed robots in The Matrix, the meaning of love in Her. In reality, AI is more pervasive, if less epic. AI algorithms help IBM's Deep Blue and Watson win chess and Jeopardy! tournaments. Voice-activated assistants give information, entertain, and control devices and homes. Self-driving cars will go on sale to car services next year, General Motors promises.1AI is a computer's ability to choose and perform the right machine learning techniques at the right time, successfully, regularly, and with a minimum of effort.2power -- and deep learning, which helps refine the understanding those neural networks can produce. AI algorithms can work `supervised' -- with people indicating which results are closer to the desired outcomes -- or `unsupervised,' where they execute and adjust on their own, usually after a period of human instruction (see right). AI today is used in nearly every industry in ways we access every day. It helps search engines find their targets; executes complex decisions for financial trading; powers programming recommendations for services like Netflix2. It can also aid in content curation, enhance cyber security, improve warehouse inventory management, assist salespeople in generating better leads, and help fly airplanes.SUPERVISED VS. UNSUPERVISED, APPLIED TO ADVERTISING SUPERVISED UNSUPERVISEDTrain the model on data where the correct answer is included. E.g. What bid price is likely to win this impressionvsTrain the model on data with no answers and see what it comes up with. E. g. What do people who click my ad have in commonAI FOR ADVERTISING For advertising, AI is being used in a variety of ways to improve effectiveness. It has been used to find and define audiences, refine creative messaging (see graphic page 5), generate audience personas, and develop bidding strategies that optimize for clients' stated goals. AI has many seemingly small applications that currently deliver digital marketing efficiencies for companies all over the world -- from advanced consumer targeting and insights to highly personalized ad experiences, says Adam Grow, SVP of Display at Rakuten Marketing. 3At present, most advertisers aren't taking advantage of the full capabilities of AI. Instead, they deploy it to achieve simple goals. But it can do much more than elevate discrete performance metrics. When the many applications of AI are used in concert, they can add up to a significant transformation in digital advertising strategy that drives remarkably improved results. To accomplish that, new campaigns must be conceived and built around the unique opportunities and strategies afforded by AI. This requires advertisers to shift their perspective; to refine and expand their idea of marketing success and approach new campaigns in cooperation with the way AI works. The most powerful -- and largely unfulfilled -- potential of AI lies in the bigger picture, in its ability to optimize towards business outcomes rather than simple metrics. One car maker, for example, sought to increase sales. To do so, it evaluated the influence of individual performance metrics within the context of that larger goal. It weighted factors such as website interactions, brochure downloads, and showroom visits to determine messages that ultimately lead to that outcome, and used artificial intelligence with machine learning to continually optimize toward better scores -- thereby making its marketing evermore effective.43AI IN PROGRAMMATIC Programmatic advertising is exceptionally wellsuited for AI. A world with billions of impressions auctioned in fractions of a second and alwayschanging circumstances creates a scale of multi-factorial problems that can only be solved effectively with the help of AI. To achieve an objective becomes very hard without the help of an AI platform that can do a lot of the heavy lifting, says Xaxis CEO Nicolas Bidon. The amount of data, the combinations that can result, is growing exponentially to the point that a human will have trouble determining the right bidding strategy to buy media for a client.DESIGNING MEDIA STRATEGIES FOR AN AI WORLD It's a given advertisers want to reach the right person at the right time with the right message, and of course, at the right price.Determining the bidding strategy to achieve specific outcomes becomes very hard without the help of an AI platform.DIGITAL STRATEGY IS EVOLVING But, in the digital era, a lot of advertising media strategies have focused on targeting audience segments that seem to contain propitious prospects. Messages are tailored to them via medium, platform, and screen, and, when possible, factor in behaviors and locale. Advertisers run their messages, gather results, then try to optimize against marketing metrics such as completed view rates, time of exposure, clickthrough rates (CTR,) and effective cost per thousand impressions (eCPM). Yet, every one of those measurements is an imperfect proxy for what's actually desired: sales. By optimizing toward CTR among a target audience, for example, a media buyer may be getting a lot of the right people onto a web page, but that's not necessarily a measure of sales efficiency. By contrast, artificial intelligence algorithms -- correctly instructed -- can help optimize marketing plans toward better sales metrics. Audience segments based on demographic, behavioral, and geographic characteristics can be highly effective, but they will always miss a large portion of potential purchase intenders who deviate from the standard definitions. Digital media strategies that use AI to identify and locate prospects without bias or assumptions will find customers, not just segments. Take, for example, a high-end home appliances maker that may be willing to spend $100 to sell one machine. Articulated in that way -- rather than in terms of metrics like demographics or CPM -- data4。。。。。。