Even for the most seasoned marketers, 2017 will be back-to-school time. Here’s your syllabus.
Spending on mobile advertising will grow at a projected compound annual rate of 26 percent through 2020. Facilitated by leading programmatic ad networks such as Google, Yahoo, and AOL, native advertising is projected to command a 63 percent share of those dollars over the same period. And while this opens new avenues for marketers to reach consumers, there are several factors every marketer should consider when planning a native advertising strategy.
First, the continued FTC scrutiny of native advertising has led a number of platforms, Facebook for example, to proactively create tagging and labeling requirements that clearly alert users to the commercial nature of the content. It is unclear whether the FTC will eventually standardize labeling requirements. But it looks as if any labeling may reduce consumer engagement levels and potentially, effectiveness.
Second, pricing models for native are changing. Where marketers once paid for creation and placement, they are now finding an increasing number of media outlets charging on a pay-per-view model. It’s a smart move by publishers who might otherwise be competing on price for creation and space alone. The downside for marketers is that unexpectedly successful content can drive up media costs quickly.
Third, and potentially the largest challenge for most marketers, competing in a growing native advertising environment requires a continuous flow of new, high-quality editorial content. Content is less marketing than publishing and requires resources that can meet those needs.
Ask most consumers for access to their metadata from across their devices to build a more detailed universal profile of their GPS data, preferences, and behaviors, and they will respond, “No.” However, show most consumers a truly customized and convenient experience fueled by that data, such as having your steaming hot pumpkin spice latte waiting for you the moment you enter a Starbucks, and they are likely to check the “Allow” button when the app asks for access to that kind of data. Consumers are increasingly demanding personal relevance in the services they seek in exchange for anything resembling loyalty.
Machine Learning/Artificial Intelligence
Big data was about processing voluminous data sets. AI is about divining the meaning and opportunities within it. And in the coming year, we will see an increasing number of marketing organizations turn to machine learning and artificial intelligence to improve product recommendation engines, clarify segmentation models, optimize pricing by segment and customer, analyze sentiment across social media outlets, create proactive and predictive customer service models using “chat” bots, improve ad targeting, optimize marketing messaging and design, and even create new marketing content from scratch.
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Since 1985, Magnani Continuum Marketing has made it easier for organizations selling in highly technical and complex markets to deliver the most effective and seamless traditional and digital brand experiences. We’re more digital than advertising agencies. We’re more strategic than digital marketing shops. We’re more creative than management consultants. And we’re a heck of a lot easier to work with than almost all of them.