A.I. for marketing is about automating simple tasks that allow us to free up more of our time to be strategic, effective, and less iterative. There’s nothing really artificial about it. It’s about saving time and improving processes.
I recently heard Andrew Ng of Baidu and Stanford University’s MOOC platform say that A.I. at its current stage is about automating the processes that take the human brain one to two seconds to complete. In marketing, that A.I. can be broadened to something more because it can bring efficiency to data collection, basic data observation and basic activation of the insights derived from that data.
Marketers can automate data collection if they can consolidate or limit the sources of data in, as well as develop a simplified, unified taxonomy for the data. This can be for audience data in targeting or measurement data for reporting.
If you can ensure a singular format, the data can be more easily pulled together. Then basic data analysis can be done — which means trends can be spotted, and simple decisions to optimize or not could be automated.
Basic activation refers to what happens as a result of those insights and that can refer to everything from the output of recommendations that require human implementation to simple optimization and reallocation of digital advertising.
All in all, A.I. in this context simply refers to giving you back time, since most of what I describe above is the role played by the agency in a typical agency-marketer relationship.
That means A.I. potentially has a huge role in the agency world, allowing agencies to get back to a more strategic function and focus on messaging and creative. After all, these are the ways they typically should be adding value in an era of consolidation for media (both in terms of where you spend your money and how you spend your money). A.I. actually allows agencies to refocus their staff on valuable relationships rather than treading water.
I would expect real A.I. involvement by an agency would mean investing in data science to automate reporting, which is a direct response to the pressure of cost-cutting and margin slashing in recent years. However, I’ve seen press releases from agencies touting their involvement in A.I., but most of these are simply releases to generate buzz – I don’t see much more than vapor slightly below the surface.
For brands, A.I. has a similar effect internally. If brands can harness A.I. to automate processes — ranging from offer optimization to customer journey mapping and message delivery — they can focus on broader, more strategic efforts to maximize customer relationships and acquisition. If you are simply trying to manually optimize every experience, you have too many people focused on the present and not enough on the future.
2014 was The Year of Mobile (again) and 2015 was the year of Big Data, while 2016 was the year of MarTech vs. AdTech. 2017 aims to be the year of A.I. Are you thinking of how to use the data once you have it? That’s simply what this is all about: leveraging the data for automation!