Clever Isn’t Enough: Why the Future of Marketing is in Machine-Learning
“With just the right copy, it’ll work.”“If we just tweak the color balance, this could go viral.”
What’s more, all marketing platforms are experiencing diminishing returns. With more eyeballs than ever, it’s simultaneously more expensive to reach paid and earned audiences, while even newer platforms fall victim to the law of sub-optimal clickthroughs faster than ever.
Focus on targeting
Copy and creative might spark increasingly unwinnable battles, but behavioral targeting and user profiling present exciting frontiers in digital marketing with new breakthroughs to facilitate unique competitive advantages.
Think about your last few campaigns: how did you determine key targeting terms? How did your data management platform (DMP) assemble an audience that matched your targets? In all likelihood, targets were created from user profiles built out of events (e.g. a page visit).
In this scenario, a human assigns a category to each event, which is problematic for three reasons:
- It’s subjective: it falls prey to the decision of a human
- It’s static: it’s part of a system that needs to be maintained by humans or it will quickly grow stale
- It’s information destructive, since there’s only one category per event and other information is lost to the ether (more about information destruction and how to avoid it)
A bigger and better picture
There’s a better way to do things. Through a machine-learning process known as natural language processing (NLP), Semasio automatically scans content and assign a series of terms to it, ranked in importance. Compared to the old process, this is:
- Objective: no humans are involved in determining categories, removing bias.
- Dynamic: the more pages analyzed, the more the system adapts to place the appropriate weight on various terms.
- Information Preserving: instead of reducing a page to one or more data points, here we preserve all the information on the page for use in target generation.
Your first real audience
Using NLP for behavioral targeting, we create a semantic profile of a user. Semantic profiling provides a comprehensive and dynamic picture of a user, giving marketers much more accurate targeting.
A semantically profiled audience is also one that is uniquely yours. Compared to “off-the-shelf” audiences that you may have experienced in the past, a dynamic audience derived from semantic profiling cannot be precisely replicated by the competition.