Forbes: The Opportunities And Challenges Of Putting A Brand’s Mentality Into Action

NEWS

Forbes: The Opportunities And Challenges Of Putting
A Brand’s Mentality Into Action

August 23, 2021

By Greg Garunov, EVP Business Development

In my previous article, I talked about the importance of a brand knowing its mindset — its unique mentality. This article explores the opportunities and challenges of codifying and putting it into action so that brands can respond to events in real time.

When Narratives Change in an Instant

All marketers want their messages to appear alongside content that’s relevant to what their brand stands for, but with the speed of today’s news cycle, that’s easier said than done.

Here’s an example: On February 23, Tiger Woods crashed his Genesis GV80 SUV. According to the police, he was “driving in an unsafe manner.” This wasn’t Woods’ first highly public car accident.

Then, on March 10, something very interesting happened: YouTuber and car enthusiast Elliot Alvis posted a video detailing how the many safety features of the Genesis GV80 saved Tiger Woods’ life. (Elliot Alvis openly acknowledges a relationship with Genesis.)

With that single upload, the story took a sudden, viral turn, doing more to promote the SUV’s safety features than a $5 million Super Bowl spot ever could. Consumers all over the world were suddenly talking about the remarkable ways in which Genesis protects drivers and passengers from harm.

YouTube video

Now, if you’re the brand manager for, say, the Subaru Outback or the Volvo V90, this story just became incredibly important, and you probably want to insert messages about your brand’s safety features in the conversation ASAP.

Here’s the upshot: We all know that brands tend to be naturally risk-averse, but sometimes bad news stories morph into golden opportunities. Stories are multi-layered narratives that can twist and turn. Tactics you once relied on (e.g., avoiding car crash stories if you’re an auto brand) can work against you if the narrative becomes core to your brand.

A Lack of Agility Kills the Moment

For the past 20 years, behavioral targeting and programmatic ad tech were the marketer’s primary tools for message alignment, but to respond to the Tiger Woods story, Subaru or Volvo would first need to realize that the story’s twist is relevant to its brand.

Sometimes bad news stories morph into golden opportunities

This begs the question: Is the brand manager even likely to see Alvis’s video until it percolates into the mainstream media? Possibly, but not probably, since the tools the brand manager uses — Google Alerts or some other keyword/regular expression monitoring tool — may not even be set to pick up stories or content related to Genesis.

Second, the competitive brand would need to notify its media execution team that this story has turned into an opportunity. Once notified, they would need to monitor and respond to the story in an automated fashion since this story twist will probably last only a couple of days. They’d likely create a set of keywords to target and then feed the revised strategy into their demand-side platform (DSP) or other platforms’ algorithms. That’s precious time lost.

And how will the media team even know who to target? In all likelihood, they’d build a proxy for consumers who are in the market for a car and are concerned with automobile safety. But is that even the right audience at that moment in time?

Many would say that the content people are consuming is a better real-time indicator of where their psyches are, and I agree with them. It’s critical to craft ad-placement decisions around consumers’ psyches because it’s the only way to really capture them in the right moments with the right message (ironically, all the promises that have been made over the years but never really came to pass).

Sometimes, content signals are just better suited to deliver on that promise than behavioral signals, as the Tiger Woods example shows. Modern content signals, when activated against strategic thought and speed, can deliver on this promise today in a significantly more effective way compared to the behavioral signals of old.

Data Science Delivers on a Brand’s Mentality

Can the industry get to the point where a marketer will know when a piece of content, somewhere in the universe, was posted that aligns with a brand’s messaging? To do this, we need to move beyond keyword detection and flag content based on a deeper level of context.

Fortunately, data science has vastly improved in its ability to read content signals. In the past, there was very little nuance to content data signals because all focus was on behavioral signs. But that’s changing. Today, data scientists have the ability to navigate content at a granular level, which makes it a much more effective tool for targeting than it was in the past.

Data science

To see how, let’s go back to the Subaru/Volvo predicament: What if the company had some kind of mechanism that told it instantly that Elliot Alvi had uploaded his video on the car that saved Tiger Woods’ life? Getting that information in real time would have tipped off the brand manager that the narrative around the accident had changed in an important way.

Getting data on content-origination points is only half the challenge. The other half is understanding a brand’s mentality — a filter that recognizes when a narrative changes to become a golden opportunity and helps execute the right message.

It’s Hard, but the Rewards Are Worth It

Getting a brand’s mentality right involves being sensitive to societal, psychological and anthropological thinking. It means translating business and marketing objectives and inputs in a way that aligns with how people actually think in the real world, not inside a marketing bubble.

At times, those inputs (story of a car crash) and outputs (we want to be part of this story) are off-kilter, and brands must learn to recognize that narratives change, quickly morphing between opportunities and challenges. This is how a brand’s mentality builds on brand suitability and brand safety, ensuring they go further and enabling them to respond in real time to fluid situations.

As you can imagine, that requires a lot of sophisticated analytics driving automation, which I’ll tackle in my next article.

 

See the original article on Forbes here.

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