Digital advertising and marketing complexity continue to increase as the big ad players – Google, Facebook, LinkedIn and Microsoft – fight for advertising dollars during these uncertain times. The increasing complexity, combined with unprecedented consumer behavior, is going to separate the strategic thinkers and marketers from the snake oil sellers. Many are already wondering how they are going to navigate this unique and unexpected turn of events.
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Artificial intelligence (AI) is going to be especially useful in this regard. It’s more than automation – many of the most valuable applications are found in anomaly detection and forecasting. Both become imperative in a fast-changing and unknown market.
Not everyone knows what to do with the results AI can produce, however. A study conducted in partnership with Censuswide, “Agency Confessions,” revealed that 50% of digital agency decision-makers have more data than they can sort through and use. Forty-nine percent also say that they spend too much time sorting through all the data they have to find what is important.
These are critical revelations in a world where “more data!” is a common theme across most sectors. And it’s not as if there aren’t agencies that feel the same way – 40% agree with the “more data” sentiment. For everyone else, the combination of today’s challenging climate and the deluge of data could prove to be catastrophic.
Risks and consequences
The study also found that more than 43% of agencies spend between 6 and 10 hours monitoring their campaigns every single week. More than 31% invest 11 to 15 hours, while nearly 10% spend as much as 20 hours on campaign monitoring. This is an excessive amount of time, especially when there aren’t enough digital marketers to go around. No agency can afford to allocate a day’s worth of time – let alone multiple days – toward monitoring alone.
What’s more, mistakes are still getting through. Fifty-one percent of respondents encounter 6 to 10 mistakes every week, and 9% endure as many as 15. These blunders have real-world consequences, costing anywhere from $1,000 to $5,000 (53%) and as much as $10,000 (35%) per each individual error. One could imagine how a hard fought increase in media budgets and fees would be devoured by these mistakes, reducing the resources necessary to overcome unexpected events.
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Take control of digital data
Many agencies may be wondering how to cope with the swift changes in the global market. But instead of making drastic moves, a much more sensible approach would be to rely on AI to perform the tasks that are either too complex, too time-consuming or simply require too many individuals.
AI can quickly, efficiently and more easily measure, monitor and optimize a campaign. But this isn’t something that has to be developed in-house within each agency. They should instead utilize an AI solution that can help them take control of their digital data with invaluable information and unrivaled insight. A solution that is smart enough to serve individual needs but scalable enough to assist any number of industries, from eCommerce, fitness and education to healthcare, finance, insurance and more.
Embrace the future
Agencies need not worry about the “more data!” mantra or the “too much data!” backlash. With AI, it is finally possible to utilize every valuable data point while ignoring those that don’t matter. The technology can be implemented to automatically analyze data-driven decision making based on key performance indicators. It can also check for anomalies and potential mistakes, then quickly alert digital marketers so they can take prompt action.
This is an important step forward for marketers, who are no longer required to use archaic methods for error mitigation. Our study found that 42% still personally double-check ad platforms and/or use master spreadsheets to track everything. That might have worked at a time when technology was in its infancy.. But in today’s complex, confusing and evolving landscape, it’s time for a change. By taking advantage of AI, agencies can better optimize their campaigns and catch potential issues before they become a costly problem.
