To Understand Audiences, You Need to Ask “Why”
Last year the world searched “why” more than ever. It’s human nature to want to understand context, particularly when faced with uncertainty and hardship. But “why” is always the most important question — not just in times of crisis. Often, it is the one that marketers forget to ask, not realizing that their success hinges on audience understanding.
The key to answering the question of “why” is with artificial intelligence (AI) and data. With more than 4.4B internet users, there is no version of the future in which brands and businesses don’t use artificial intelligence and machine learning to understand their audiences at scale. With AI, marketers can get to the WHY. Without it, they are stuck in the WHAT.
Let’s consider the value of “why,” and how marketers can rethink their approach to data to answer this question, thereby improving audience understanding — and their ability to authentically and effectively engage those audiences.
Why as a means to understanding the context
For decades, successful innovators have been using the five why technique to get to the actionable root cause of any problem, because “why” reveals context, nuances, and the next questions you should be asking.
Let’s say a tech company’s website crashes.
Why did the site go down?
Because there was an error in the code. Why was there an error? Because the software team released a piece of code that contained a bug. Why did they do that? Because they skipped the QA process. Why did they skip it? Because they were in a rush to release the software.
A-ha! Get through those five “whys,” and you can pretty much identify how to fix anything.
Using AI to decipher unstructured data
Most marketers use AI to monitor real-time telemetric data to recognize patterns. While noticing data trends and deviations is important, it doesn’t get to the root of why something is happening.
According to the IDC, unstructured, text-based data will comprise 80% of the internet by 2025. While unstructured data offers an array of unique challenges, it also offers marketers incredible opportunities to strengthen customer understanding and improve product and monetization strategies — if AI can be applied beyond just pattern recognition.
For example, game publishers monitor changes in-session behavior, user churn, ad engagement, in-game spending trends — the list goes on. But, let’s say that a video game creator announces an update to the game, and user behaviors change before the update is ever released. Why is this? A cursory glance at what is happening across headlines or viral posts might cause the developer to assume that the vocal minority represents the majority.
However, without a clear understanding of “why,” there really is no way to determine if their assumption is right or if it is wrong.
With AI, they could have analyzed unstructured data on the open internet — including indirect brand mentions in organic conversations, social media posts, fan sites, media coverage and more — to move beyond soundbites and attain a deeper, contextual understanding of the factors, the why’s, at play.
Why as a tool for innovators
Answering “why” creates opportunities to do better, as well as gives a genuine understanding of what an audience is thinking. Certainly, creatives don’t let audiences dictate their decision-making entirely. Part of an innovator’s magic is delivering the unexpected, and testing and challenging their audiences in inspiring, enjoyable ways. But without contextualized audience understanding, brands can make poor decisions about those innovations.
Asking “why” leads to fascinating answers with huge implications for brands. With streaming video and online gameplay reaching all-time highs, organizations should secure tools and strategies now to draw insights from the resulting treasure troves of structured and unstructured data.
Why should brands bother? Because doing so will lead to enhanced audience understanding, better decision-making — and ultimately, more successful products, brands, and businesses.
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